Hey now, take a step outside and seize the day now, set aside your worries. Hey guys, welcome back to my channel. So today I worked all day long and I'm kind of looking for a quick and easy dinner this evening.  But before we get started, I wanted to let you guys know that this video is sponsored by ELEC HOMES and I've actually worked with them before. I have one of their professional grade high-power blenders. It works amazing. I've used it for quite some time now and it's definitely very good quality, especially for the price. I mean, you can't beat the price of their kitchen appliances and for the quality, they are awesome. So I'm so excited to work with them again and bring you another kitchen appliance. They just released their pressure cooker and I love pressure cookers. They are so convenient and so quick, especially when you've been gone all day and you didn't put something on slow cook. You can whip it up really quickly with these and this one has a ton of great features. There's so much you can do with this pressure cooker. Anything from making yogurt to cakes, you can hard boil eggs, cook rice, make soup. And one of our absolute favorites is we like to use it to make our ribs. This pressure cooker comes with so many different accessories and anything and everything that you'll need. I love the fact that it has a time setting on it so whenever it's finished, it goes right to warm. So even if you're away, you don't have to worry about anything burning. It also has a slow cooker setting so you can use it just like a slow cooker. ELEC HOMES just released this pressure cooker so you guys are going to get in on a great sale. They have an early bird special that is 40% off so check the description box for that code. You're not going to want to miss out on it. It is for a limited time only and I would highly recommend taking advantage of this deal. Alright, so let's get cooking. The first thing you're going to need is about three chicken breasts. I cut mine a little bit on the thinner side just so they were easier to cut up once I pulled them out of the pressure cooker. You're going to need a block of softened cream cheese, a tablespoon of everything bagel seasoning. A handful of cilantro I just chopped mine up. You actually wouldn't need to but I just thought it would be a little easier to eat this way. Next you'll need two tablespoons of spicy brown mustard and then I just used a hand blender to blend everything up and get it to a nice creamy consistency. Next you'll add about a cup of water to the bottom of the slow cooker with the chicken. Then I took my creamy mixture and just kind of dumped it in and smeared it all over the top of the chicken. Lastly, I took Romano cheese and liberally sprinkled it in over top of the chicken. I put it on the poultry setting for about 25 minutes and put the lid in place. Next I heated up some rice cauliflower in the microwave to go along with the chicken. Another quick side that I like to do on busy days is deviled eggs. They're so simple and everybody in our household absolutely loves them. Once you've peeled your hard boiled eggs you'll just take the yellow parts out and let the eggs cut in half on a plate. I mix in mayo, some Dijon mustard and just kind of mash it all together and whip it up. I don't have exact measurements so you can play with it to your taste. Then you refill the eggs with the mixture. Next I sprinkled some chili lime seasoning over top of the eggs. It was so good this way. And it wasn't long and my chicken was done. It was so delicious we dug in right away and I did not get a picture of my plate. Alright guys so here is a real life day. Sometimes I don't get my nighttime routine done and I end up crashing and falling asleep before all of this gets done.  Something I do pretty often is I kind of mop the area that the girls sit at their little table just because it gets a lot of sticky stuff on it. Next I grabbed the laundry and kind of got everything switched around. I try to fold about one load every night but again since I didn't do my regular routine the night before I was doing a little bit of catch up and decided to go ahead and put the second load into the dryer and do two loads in the same day. My dishwasher was already empty so I just went ahead and put all of the dishes from the night before into the dishwasher. With this dishwasher my friend even made a comment the other day. It cleans so fast and so efficiently. I don't know if it's just one of those old ones that will last forever and does an amazing job but I have definitely been enjoying it since we moved. 66 and we keep on driving we just do. The kitchen was done and actually this day we had some friends over so the kids were sitting on my bed watching a movie and I didn't want to bother them. They were enjoying themselves so I decided to just go ahead and pick up the toys in the living room myself. They ended up cleaning up the toys in their bedrooms later on in the day but because I wanted a fresh start to get my morning picked off right I just went ahead and picked everything up from the day before. I also know if you watch me often that this is pretty much my nighttime routine. If you're new around here don't forget to hit the subscribe button. Also don't forget to check out that great coupon code in the description box to get yourself a pressure cooker and I will see you guys in my next vlog.


Good morning, Hank. It's Friday. It's the final day of Pizzamas 2015. And what a ride it's been. We've laughed, we've cried, we've suited up, we've learned some art history, and perhaps most importantly, we have made the acquaintance of Cheez-Doodles' guy. YAAAAAAA! But all good things must end, even the excitement over Cheez-Doodles. In fact, come to think of it, everything must end. And this universe, to be, is to not always be. Or actually, maybe not. Maybe to be is just to change. After all those Cheez-Doodles eventually became poop. But anyway, the end of Pizzamas also means this is the last day you can order Pizzamas merch. My face and a nebula on your torso only available until midnight tonight along with the rest of the Pizzamas merch. Check it out at dftba.com, link in the doobly-doo. But if you leave Pizzamas with no physical mementos, fear not when Nerdfighter DC complained that they were too broke to enjoy Pizzamas' untapped ink well-replied. Pizzamas is just as much a state of being as it is a consumerist holiday. So true. So true of all consumerist holidays, actually, which these days is to say all holidays. But speaking of states of being, you talked about kind of personal stuff in your video yesterday, Hank, so I guess I'll do the same. I have a mental illness called obsessive-compulsive disorder which is often associated with anxiety and depression problems. I try to talk about that sometimes because I don't think there should be anything embarrassing about mental illness, but I don't talk about it that much because, one, it's personal. And two, I find it difficult to talk about my own experiences with chronic illness because the central way we imagine sickness as a thing that we must conquer and then put behind us doesn't really apply to chronic illness.  But for people living with chronic illness, it often isn't a question of getting well soon. Like, Hank, I hope someday they cure ulcerative colitis, but I don't expect you to get well soon. Instead, my hope for you is that you have a rich and full life and that you aren't marginalized because of your illness. Which is a big problem. I have a theory about this, Hank. I don't think we humans like to imagine our lives as random. We need human lives to be narratives that make sense. So if we can't find causation, we just create it. Like, people get depression because they're weak or they get diabetes because they don't eat well or they have heart failure because they don't exercise. All that stuff is either totally inaccurate or overly simplistic, but we want every effect to have a cause. And when we can't find that cause, we invent one. Anyway, Hank, as you know, I have been very sick the last several weeks as I've tried to figure out a new medication regimen. Over the years of living with my illness, I've learned a lot about how to make it tolerable. I've learned to celebrate small successes. I've learned to encourage myself without being cruel. And most importantly, I've learned that there is hope and that when I feel like there isn't hope, my brain is lying to me. But still, it is awful and after years of relatively good health, I have been reminded in the last several weeks just how painful and crushing this stuff can be. And that's despite my having all kinds of advantages that make it easier to live with an incredibly supportive family, total job flexibility, an excellent therapist and psychiatrist, money to afford medication, etc. Most people don't have all those resources and that worsens any kind of illness. Hank, I mention all this for three reasons. First, to tell people who may be living with mental illness that there is hope, that mental illness is almost always treatable and that how you feel when you are at your sickest is not how you will always feel. And down in the doobly-doo, you can find links to resources that I've found helpful and that people I know have found helpful. Secondly, I want to remind all of us that what we see in videos or on Instagram isn't the whole story. Like, my friends and family have known that I have been unwell the last several weeks because it is impossible for me to hide it from them, but it is very possible for me to hide it with jump cuts. And lastly, to say thanks. Thank you for watching these videos and Hank, thank you for the gift of Pizzamas, which has given structure and achievable tasks to my life at a time when I desperately needed them. I'm starting to feel better for a variety of reasons from medication to exercise, but the gift of Pizzamas has been surprisingly important, so thank you for being part of it. Hank, don't forget to be awesome. I will see you. No! No! You will see me on Tuesday.


From around the globe, it's theCUBE with digital coverage of enterprise data automation and event series brought to you by IOTAHO. Welcome everybody to Enterprise Data Automation, a co-created digital program on theCUBE with support from IOTAHO. My name is Dave Vellante and today we're using the hashtag data automated. You know, organizations they really struggle to get more value out of their data. Time to data-driven insights that drive cost savings or new revenue opportunities, they simply take too long. So today we're going to talk about how organizations can streamline their data operations through automation, machine intelligence and really simplifying data migrations to the cloud. We'll be talking to technologists, visionaries, hands-on practitioners and experts that are not just talking about streamlining their data pipelines, they're actually doing it. So keep it right there. We're going to be back shortly with AJ Vahora who's the CEO of IOTAHO to kick off the program. You're watching theCUBE, the leader in digital global coverage. We'll be right back right at this short break. Innovation, impact, influence. Welcome to theCUBE, disruptors, developers and practitioners, learn from the voices of leaders who share their personal insights from the hottest digital events around the globe. Enjoy the best this community has to offer on theCUBE, your global leader in high-tech digital coverage. From around the globe, it's theCUBE with digital coverage of enterprise data automation and event series brought to you by IOTAHO. Okay, we're back. Welcome back to Data Automated. AJ Vahora is CEO of IOTAHO. AJ, good to see you. How are things in London? Things are doing well. Things are doing well. Customers that I speak to day in, day out that we partner with. They're busy adapting their businesses to serve their customers. It's very much a game of ensuring that we can serve our customers to help their customers. And the adaptation that's happening here is trying to be more agile, trying to be more flexible. And there's a lot of pressure on data, a lot of demand on data to deliver more value to the business to serve that customer. As I said, we've been talking about data ops a lot, the idea being DevOps applied to the data pipeline. But talk about enterprise data automation. What is it to you and how is it different from data ops? DevOps has been great for breaking down those silos between different roles, functions and bringing people together to collaborate. And we definitely see that those tools, those methodologies, those processes, that kind of thinking, lending itself to data with data ops is exciting. What we look to do is build on top of that with data automation. It's the nuts and bolts of the algorithms, the models behind machine learning, the functions. That's where we invest our R&D and bringing that into build on top of the methods, the ways of thinking that break down those silos and injecting that automation into the business processes that are gonna drive a business to serve its customer. It's a layer beyond DevOps, data ops. They can get to that point where where I like to think about it is, is the automation behind the automation. We've come a long way in the last three or four years. We started out with automating some of those simple to codify, but have a high impact on an organization across the data lake, across the data warehouse. Those data related tasks that help classify data. And a lot of our original patterns and IP portfolio that we've built up is very much around that. I'd love to get into the tech a little bit in terms of how it works. And I think we have a graphic here that gets into that a little bit. So guys, if you'd bring that up. Sure. I mean, right there in the middle that the heart of what we do, it is the intellectual property that we've built up over time that takes from heterogeneous data sources, your Oracle relational database, your mainframe, your data lake and increasingly APIs and devices that produce data. And it creates the ability to automatically discover that data, classify that data. After it's classified, then have the ability to form relationship across those different source systems, silos, different lines of business. And once we've automated that, then we can start to do some cool things such as put some context and meaning around that data. So it's moving it now from being data driven and increasingly, well, we have really smart, bright people in our customer organizations who wanna do some of those advanced knowledge tasks, data scientists and quants in some of the banks that we work with. The owners is on then putting everything we've done there with automation, pacifying it, relationship, understanding data quality, the policies that you can apply to that data and putting it in context. Once you've got the ability to empower a professional who's using data to be able to put that data in context and search across the entire enterprise estate, then they can start to do some exciting things and piece together the tapestry, the fabric across their different system. Could be CRM, ELP systems such as SAP and some of the newer cloud databases that we work with, Snowflake is a great one. If I look back maybe five years ago, we had a prevalence of data late technologies at the cutting edge and those have started to converge and move to some of the cloud platforms that we work with such as Google and AWS. And I think very much as you've said it, those manual attempts to try and grasp what is such a complex challenge at scale quickly runs out of steam. Because once you've got your fingers on the details of what's in your data estate, it's changed. You've onboarded a new customer, you've signed up a new partner, a customer has adopted a new product that you've just launched and that slew of data keeps coming. So it's keeping pace with that. The only answer really is some form of automation. You're working with AWS, you're working with Google, you got Red Hat, IBM as partners. What is attracting those folks to your ecosystem and give us your thoughts on the importance of ecosystem? That's fundamental. I mean, when I came in sweet, Biotaho here is the CEO, one of the trends that I wanted us to be part of was being open, having an open architecture that allowed one thing that was close to my heart, which was as a CEO, a CIO where you've got a budget vision and you've already made investments into your organization. And some of those are pretty long-term bets. They could be going out five, 10 years sometimes with a CRM system, training up your people, getting everybody working together around a common business platform. What I wanted to ensure is that we could openly plug in using APIs that were available to a lot of that some investment and the cost that has already gone into managing an organization's IT for business users to perform. So part of the reason why we've been able to be successful with some of our partners like Google, AWS and increasingly a number of technology players such as Red Hat, MongoDB's, another one, we're doing a lot of good work with, and Snowflake here is it's, those investments have been made by the organizations that are our customers. And we want to make sure we're adding to that and they're leveraging the value that they've already committed to. Maybe you could give us some examples of the ROI and the business impact. Yeah, I mean, the ROI David is built upon three things that I've mentioned. It's a combination of leveraging the existing investment with the existing estate, whether that's on Microsoft Azure or AWS or Google, IBM and putting that to work because the customers that we work with have made those choices. On top of that, it's ensuring that we have got the automation that is working right down to the level of data at a column level or at a file level. So we don't deal with metadata. It's being very specific to be at the most granular level. So as we run our processes and the automation, classification, tagging, applying policies from across different compliance and regulatory needs that an organization has to the data. Everything that then happens downstream from that is ready to serve a business outcome. Now with our Tahoe being able to run those processes within hours of getting started and build that picture, visualize that picture and bring it to life. You know, the ROI starts off the back with finding data that should have been deleted, data that there's copies of and being able to allow the architect, whether it's we are working on GCP or in migration to any other clouds such as AWS or a multi-cloud landscape quite often now. AJ Vohorat, thanks so much for coming on theCUBE and sharing your insights and your experiences. Great to have you. Thank you, David. Look forward to talking again. Now we want to bring in the customer perspective. We have a great conversation with Paula D'Amico, the Senior Vice President Data Architecture at Webster Bank, so keep it right there. IOTAHO, data automated. Improve efficiency, drive down costs and make your enterprise data work for you. We're on a mission to enable our customers to automate their management of data to realize maximum strategic and operational benefits. We envisage a world where data users consume accurate, up-to-date, unified data distilled from many silos to deliver transformational outcomes. Activate your data and avoid manual processing. Accelerate data projects by enabling non-IT resources and data experts to consolidate, categorize and master data. Automate your data operations. Power digital transformations by automating a significant portion of data management through human-guided machine learning. Get value from the start. Increase the velocity of business outcomes with complete, accurate data curated automatically for data visualization tools and analytic insights. Improve the security and quality of your data. Data automation improves security by reducing the number of individuals who have access to sensitive data. And it can improve quality. Many companies report double-digit error reduction in data entry and other repetitive tasks. Trust the way data works for you. Data automation by IAO Tahoe learns as it works and can augment business user behavior. It learns from exception handling and scales up or down as needed to prevent system or application overloads or crashes. It also allows for innate knowledge to be socialized rather than individualized. No longer will your company struggle when the employee who knows how this report is done retires or takes another job. The work continues on without the need for detailed information transfer. Continue supporting the digital shift. Perhaps most importantly, data automation allows companies to begin making moves towards a broader, more aspirational transformation. But on a small scale that is easy to implement and manage and delivers quick wins. Digital is the buzzword of the day, but many companies recognize that it is a complex strategy that requires time and investment. Once you get started with data automation, the digital transformation initiated and leaders and employees alike become more eager to invest time and effort in a broader digital transformational agenda. Hi, buddy, we're back and this is Dave Vellante and we're covering the whole notion of automating data in the enterprise. And I'm really excited to have Paul D'Amico here. She's a Senior Vice President of Enterprise Data Architecture at Webster Bank. Paul, good to see you. Thanks for coming on. Hi, nice to see you too. How are you? Yeah, so let's start with Webster Bank. You guys are kind of a regional, I think New York, New England, believe of headquartered out of Connecticut, but tell us a little bit about the bank. Yep. Webster Bank is regional Boston, Connecticut and New York. Very focused on in Westchester and Fairfield County. They are a really highly rated bank, regional bank for this area. They hold quite a few awards for the area for being supportive for the community and are really moving forward technology-wise. Currently today, we have a small group that is just working toward moving into a more futuristic, more data-driven data warehousing. That's our first item. And then the other item is, is to drive new revenue by anticipating what customers do when they go to the bank or when they log into their account to be able to give them the best offer. And the only way to do that is if you have timely, accurate, complete data on the customer and what's really a great value or something to offer them. At the top level, what are some of the key business drivers that are catalyzing your desire for change? The ability to give a customer what they need at the time when they need it. And what I mean by that is that we have customer interactions in multiple ways, right? And I want to be able for the customer to walk into a bank or online and see the same format and being able to have the same feel, the same look, and also to be able to offer them the next best offer for them. Part of it is really the cycle time, the end-to-end cycle time that you're pressing. And then there's, if I understand it, the residual benefits that are pretty substantial from a revenue opportunity. Exactly, it's drive new customers to new opportunities. It's enhance the risk and it's to optimize the banking process and then obviously to create new business. And the only way we're going to be able to do that is if we have the ability to look at the data right when the customer walks in the door or right when they open up their app. Do you see the potential to increase the data sources and hence the quality of the data or is that sort of premature? Oh no, exactly right. So right now we ingest a lot of flat files and from our mainframe type of front-end system that we've had for quite a few years. But now that we're moving to the cloud and off-prem and on-prem, moving off-prem into like an S3 bucket where that data can, we can process that data and get that data faster by using real-time tools to move that data into a place where like Snowflake could utilize that data or we can give it out to our market. The data scientists are out in the lines of business right now, which is great because I think that's where data science belongs. We should give them, and that's what we're working towards now is giving them more self-service, giving them the ability to access the data in a more robust way and it's a single source of truth. So they're not pulling the data down into their own like Tableau dashboards and then pushing the data back out. I have data engineers, data architects, database administrators, right? And then traditional data reporting people and because some customers that I have that are business customers, lines of business, they want to just subscribe to a report. They don't want to go out and do any data science work. And we still have to provide that. So we still want to provide them some kind of, you know, regiment that they wake up in the morning and they open up their email and there's the report that they subscribe to, which is great and it works out really well. And one of the things is, is why we purchase IOTAO was I would have the ability to give the lines of business the ability to do search within the data and read the data flows and data redundancy and things like that and help me clean up the data. And also to give it to the data analysts who say, all right, they just asked me, they want this certain report and it used to take, okay, well, we're going to four weeks, we're going to go and we're going to look at the data and then we'll come back and tell you what we can do. But now with IOTAO, they're able to look at the data and then in one or two days, they'll be able to go back and say, yes, we have the data. This is where it is. This is where we found it. This is the data flows that we found also, which is what I call it is the birth of a column. It's where the column was created and where it went to live as a teenager and then it went to, you know, die where we archived it. In researching IOTAO, it seems like one of the strengths of their platform is the ability to visualize data, the data structure and actually dig into it, but also see it and that speeds things up and gives everybody additional confidence. And then the other piece is essentially infusing AI or machine intelligence into the data pipeline is really how you're attacking automation, right? Exactly. So you're able to, let's say that I have seven cause lines of business that are asking me questions. And one of the questions they'll ask me is we want to know if this customer is okay to contact, right? And you know, there's different avenues. So you can go online to go, do not contact me. You can go to the bank and you could say, I don't want email, but I'll take texts and I want, you know, no phone calls. All that information. So seven different lines of business ask me that question in different ways.  The other one says, you know, customer one, two, three, all these, you know, and each project before I got there used to be siloed. So one customer would be a hundred hours for them to do that analytical work and then another analyst would do another hundred hours on the other project. Well, now I can do that all at once. And I can do those type of searches and say, yes, we already have that documentation. Here it is. And this is where you can find where the customer has said, you know, no, you don't want, I don't want to get access from you by email or I've subscribed to get emails from you. I'm using IoTahou's data automation right now to bring in the data and to start analyzing the data flows to make sure that I'm not missing anything and that I'm not bringing over redundant data. The data warehouse that I'm working off of is not a, it's an on-prem, it's an Oracle database and it's 15 years old. So it has extra data in it. It has things that we don't need anymore and IoTahou is helping me shake out that extra data that does not need to be moved into my S3. So it's saving me money when I'm moving from off-prem to on-prem. What's your vision or your data-driven organization? I want for the bankers to be able to walk around with an iPad in their hand and be able to access data for that customer really fast and be able to give them the best deal that they can get. I want Webster to be right there on top with being able to add new customers and to be able to serve our existing customers who had bank accounts since they were 12 years old there and now are multi, whatever. I want them to be able to have the best experience with our bankers. That's really what I want as a banking customer. I want my bank to know who I am, anticipate my needs and create a great experience for me and then let me go on with my life. And so Paula, great story. Love your experience, your background and your knowledge. Can't thank you enough for coming on theCUBE. No, thank you very much and you guys have a great day. Next, we'll talk with Lester Waters who's the CTO of IOTAHO. Lester takes us through the key considerations of moving to the cloud. IOTAHO platform, automated data discovery. Data discovery is the first step to knowing your data. Auto discovered data across any application on any infrastructure and identify all unknown data relationships across the entire siloed data landscape. Smart data catalog, know how everything is connected, understand everything in context. Regain ownership and trust in your data and maintain a single source of truth across cloud platforms, SaaS applications, reference data and legacy systems. Empower business users to quickly discover and understand the data that matters to them with a smart data catalog continuously updated ensuring business teams always have access to the most trusted data available. Automated data mapping and linking. Automate the identification of unknown relationships within and across data silos throughout the organization. Build your business glossary automatically using in-house common business terms, vocabulary and definitions. Discovered relationships appear as connections or dependencies between data entities such as customer, account, address, invoice and these data entities have many discoverable properties at a granular level. Data signals dashboards, get up to date feeds on the health of your data for faster improved data management. See trends, view full history, compare versions and get accurate and timely visual insights from across the organization. Automated data flows, automatically capture every data flow to locate all the dependencies across systems. Visualize how they work together collectively and know who within your organization has access to data. Understand the source and destination for all your business data with comprehensive data lineage constructed automatically during the data discovery phase and continuously load results into the smart data catalog. Active DQ. Automated data quality assessments powered by Active DQ ensure data is fit for consumption and meets the needs of enterprise data users. Keep information about the current data quality state readily available for faster improved decision making. Data Policy Governor.  Automate data policy assessments with glossaries, metadata and policies for sensitive data discovery that automatically tag, link and annotate with metadata to provide enterprise-wide search for all lines of business. Self-service knowledge graph. Digitize and search your enterprise knowledge. Turn multiple silo data sources into machine understandable knowledge. From a single data canvas, search and explore data content across systems including ERP, CRM, billing systems, social media to fuel data pipelines. Focusing on enterprise data automation, we're going to talk about the journey to the cloud. Remember the hashtag is data automated and we're here with Lester Waters, who's the CTO of IHO Tahoe. Hey, give us a little background. CTO, you've got a deep, deep expertise in a lot of different areas, but what do we need to know? Well, David, I started my career basically at Microsoft where I started the information security cryptography group there, the very first one that the company had. And that led to a career in information security. And of course, as you go along with information security data is the key element to be protected. So I always had my hands in data and that naturally progressed into a role with IHO Tahoe as their CTO. What's the prescription for that automation journey and simplifying that migration to the cloud? Well, I think the first thing is understanding what you got. So discover and cataloging your data and your applications. I don't know what I have, I can't move it. I can't improve it. I can't build upon it. And I have to understand those dependencies. So building that data catalog is the very first step. What do I got? Okay, so we've done the audit. We know what we've got, what's next? Where do we go next? So the next thing is remediating that data. Where do I have duplicate data? I may have, you know, oftentimes in an organization data will get duplicated. So somebody will take a snapshot of a data, you know, and then end up building a new application which suddenly becomes dependent on that data. So it's not uncommon for an organization of 20 master instances of a customer. And you can see where that will go when trying to keep all that stuff in sync becomes a nightmare all by itself. So you wanna sort of understand where all your redundant data is. So when you go to the cloud, maybe you have an opportunity here to consolidate that data. Then what, you figure out what to get rid of or actually get rid of it, what's next? Yes, yes, that would be the next step. So figure out what you need and what you don't need. Oftentimes I've found that there's obsolete columns of data in your databases that you just don't need. Or maybe it's been superseded by another, you've got tables that have been superseded by other tables in your database. So you got to kind of understand what's being used and what's not. And then from that, you can decide, I'm going to leave this stuff behind or I'm going to archive this stuff because I might need it for data retention or I'm just going to delete it. I don't, you know, you don't need it at all. We're plowing through your steps here. What's next on the journey? The next one is in a nutshell, preserve your data format. Don't, don't, don't, don't boil the ocean here to use a cliche. You know, you want to do a certain degree of lift and shift because you've got application dependencies on that data and the data format, the tables in which they sit, the columns and the way they're named. So some degree you are going to be doing a lift and shift but it's an intelligent lift and shift. The data lives in silos. So, you know, how do you kind of deal with that problem? Is that part of the journey? That's, that's a great point to it because you're right. The data silos happen because, you know, this business unit is charted with this task and other business unit has this task and that's how you get those instantiations of the same data occurring in multiple places. So you really want to, as part of your cloud migration journey, you really want to plan where there's an opportunity to consolidate your data because that means it'll be less to manage. It'll be less data to secure and it'll be, it'll have a smaller footprint which means reduced costs. So maybe you could address data quality. Where does that fit in on the journey? That's a very important point. You know, first of all, you don't want to bring your legacy issues with you as the point I made earlier. If you've got data quality issues, this is a good time to find those and identify and remediate them but that can be a laborious task and you could probably accomplish it but it'll take a lot of work. So the opportunity to use tools here and automate that process is really will help you find those outliers. What's next? I think we were through, I think I've counted six. What's the, what's the lucky seven? Lucky seven. Involve your business users. Really, when you think about it, your data is in silos. Part of this migration in cloud is an opportunity to break down these silos, these silos that naturally occur as part of the business unit. You've got to break these cultural barriers that sometimes exist between business and say, so for example, I always advise there's an opportunity here to consolidate your sensitive data, your PII, your personally identifiable information and if three different business units have the same source of truth for that, there's an opportunity to consolidate that into one. Well, great advice, Lester. Thanks so much. I mean, it's clear that CAPEX investments on data centers are generally not a good investment for most companies. Lester really appreciate, Lester Water CTO of IO Tahoe. Let's watch this short video and we'll come right back. Use cases, data migration, accelerate digitization of business by providing automated data migration workflows that save time in achieving project milestones, eradicate operational risk and minimize labor intensive manual processes that demand costly overhead. Data quality, clean up a data swamp and reestablish trust in the data to enable data science and data analytics. Data governance, ensure that business and technology understand critical data elements and have control over the enterprise data landscape. Data analytics, enablement. Data discovery to enable data scientists and data analytics teams to identify the right data set through self-service for business demands or analytical reporting that are advanced or complex. Regulatory compliance, government mandated data privacy requirements, GDPR, CCPA, EPR, HIPAA and FERPA. Data lake management, identify lake contents, clean up and manage ongoing activity. Data mapping and knowledge graph, create EKG models on business enterprise data with automated mapping to a specific ontology enabling semantic search across all sources in the data estate. Data ops at scale, as a foundation to automate your data management processes. Are you interested in test driving the IO Tahoe platform? Kickstart the benefits of data automation for your business through the IO Labs program. A flexible, scalable sandbox environment on the cloud of your choice with setup, service and support provided by IO Tahoe. Click on the link and connect with a data engineer to learn more and see IO Tahoe in action. Hi everybody, we're back. We're talking about enterprise data automation. The hashtag is data automated and we're going to really dig into data migrations. Data migrations are risky, they're time consuming and they're expensive. Yousef Khan is here, he's the head of partnerships and alliances at IO Tahoe. Coming again from London. Hey, good to see you, Yousef. Thanks very much. Thank you, Dave, great job. So let's set up the problem a little bit and then I want to get into some of the data. I just said migrations are risky, time consuming, expensive, they're oftentimes a blocker for organizations to really get value out of data. Why is that? I think, I mean, all migrations have to start with knowing the facts about your data and you can try and do this manually, but when you have an organization that may have been going for decades or longer, they will probably have a pretty large legacy data estate. So they'll have everything from on-premise mainframes, they may have stuff which is partly in the cloud, but they probably have hundreds, if not thousands of applications and potentially hundreds of different data stores. So I want to dig in to this migration and let's pull up a graphic. It'll talk about, we'll talk about what a typical migration project looks like. So what you see here is, it's very detailed, I know it's a bit of an eye test, but let me call your attention to some of the key aspects of this and then Yousef, I want you to chime in. So at the top here, you see that area graph, that's operational risk for a typical migration project and you can see the timeline and the milestones. That blue bar is the time to test, so you can see the second step data analysis, it's talking 24 weeks, so very time consuming and then let's not get, dig into the stuff in the middle of the fine print, but there's some real good detail there, but go down to the bottom, that's labor intensity in the bottom and you can see, high is that sort of brown and you can see a number of data analysis, data staging, data prep, the trial, the implementation, post implementation fixtures, the transition to BAU, which I think is business as usual. The key thing there is, when you don't understand your data upfront, it's very difficult to scope and to set up a project because you go to business stakeholders and decision makers and you say, okay, we want to migrate these data stores, we want to put them in the cloud most often, but actually you probably don't know how much data is there, you don't necessarily know how many applications it relates to, you don't have the relationships between the data, you don't know the flow of the data, so the direction in which the data is going between different data stores and tables. So you start from a position where you have pretty high risk and if you can't alleviate that risk, you probably stack your project team of lots and lots of people to do the next phase, which is analysis. And so you've set up a project which has got a pretty high cost. The bigger the project, the more people, the heavier the governance, obviously, and then they're then in the phase where they're trying to do lots and lots of manual analysis. Manual analysis, as we all know, and the idea of trying to relate data that's in different data stores, relating individual tables and columns, very, very time consuming, expensive if you're hiring in resource from consultants or systems integrators externally, you might need to buy or to use third-party tools. As I said earlier, the people who understand some of those systems may have left a while ago. So you're in a high-risk, high-cost situation from the off, and the same thing sort of develops through the project. What you find with IOTAHO is that we're able to automate a lot of this process from the very beginning because we can do the initial data discovery run, for example, automatically. So you very quickly have an automated view of the data, a data map and the data flow that's been generated automatically, much less time and effort and much less cost of money. And now let's bring up the same chart but with sort of an automation injection in here. And now, so you now see the sort of, as Coach said, celebrated by IOTAHO, okay, great, and we're going to talk about this, but look what happens to the operational risk, a dramatic reduction in that graph. And then look at the bars, the bars, those blue bars, data analysis went from 24 weeks down to four weeks, and then look at the labor intensity. It was all these were high, data analysis, data staging, data prep, trial, post-implementation fixtures and transition to BAU. All of those went from high labor intensity, so we've now attacked that and gone to low labor intensity. Explain how that magic happened. Let's take the example of a data catalog.  Imagine trying to do that manually. You'd need to go into every individual data store. You need a DBA and a business analyst for each data store. They'd need to do an extract of the data, they need to do the tables individually. They need to cross-reference that with other data stores and schemas and tables. You've probably done that with the mother of all Excel spreadsheets, and it would be a very, very difficult exercise to do. I mean, in fact, one of our reflections as we automate lots of these things is it accelerates the ability to automate, but in some cases, it also makes it possible for enterprise customers with legacy systems, take banks, for example, they quite often end up staying on mainframe systems that they've had in place for decades and not migrating away from them because they're not able to actually do the work of understanding the data, dedubicating the data, deleting data that isn't relevant, and then confidently going forward to migrate. So they stay where they are with all the attendant problems of systems that are out of support. You'll know, the biggest frustration for lots of them and the thing that they spend far too much time doing is trying to work out what the right data is and cleaning data, which really you don't want a highly paid data scientist doing with their time. But if you sort out your data stake in the first place, get rid of dedubication, perhaps migrate to a cloud store where things are more readily accessible and it's easy to build connections and to use native machine learning tools, you're well on the way up the data maturity curve and you can start to use some of those more advanced applications. Massive opportunities, not only for technology companies, but for those organizations that can apply technology for business advantage. Yousef Khan, thanks so much for coming on theCUBE. Brilliant, thank you very much, appreciate it.


Hi everybody, I hope that you're all doing well. Welcome back to my channel. Thanks for coming to hang out with me for a little bit today. Today I'm going to be answering a lot of the comments I got on my last vlog to do my wavy hair routine on camera. I've been experimenting little by little and I think it gets better every time of just learning how to embrace the natural texture that my hair has rather than just flat ironing it all the time. And out of all the things that I've tried over the years, I think this one works the best. And like I said, it gets a little bit better every time. I will say though, I can't take credit for this totally. I think like a month or two ago, this girl on TikTok, her name is Greta Wilson, she went viral for sharing some of these products and how they work for her and how they could work on other people's natural hair. And so I took three of the products from her video and then some of the things I do are a little bit different, but a lot of it is from her. So I will give credit to her credit is due. But the first thing I will talk about is in the shower. I really don't have a lot to say about it. The one thing I will say is I don't brush my hair before in or after the shower. Anyone with textured hair understands the more you brush it when it's natural, the more it's going to expand. So I do not brush my hair in the shower. I will kind of comb a little bit of my fingers through my hair more on the top of my head just so that it kind of falls nicely into place, but I will not brush it with a comb or a brush. As far as shampoo and conditioner goes, some people will disagree with me. I don't think it makes that much of a difference. Some people will disagree, but I I've switched it up. I've used Tressame. I've even used head and shoulders and it always looks the same every time out of the shower. You're going to need a microfiber hair towel. This is the one I use.  So you're probably wondering why I have this on my head. So I keep this over my hair for a while while I'm doing my makeup, while I'm changing, whatever. And then for like five minutes before I do my hair, I will put this towel back on. I know it is not super gentle for your hair, but it does absorb the water a little bit better than this will. And for me, this won't work. This routine won't work if my hair is still like dripping dripping wet. So just for like four or five minutes, I will put this on my head before I do everything else. Okay, so let's let the hair down and it kind of is sitting nicely already. I told you I kind of put my fingers through it while I'm in the shower and it's still very, very damp, but it's not dripping. So what I'll do really quick is I will just again put my fingers through it lightly. I don't want to pull it apart because that's when it starts to get a little frizzier, but I just want to make sure that it's not like knotted together or that certain pieces aren't falling in a different way than the other pieces, if that makes sense. And that kind of just leaves me with this. So now, before it gets any more dry, because you definitely want it to be damp, I will show you the products that I'm going to use. And the next three products are the ones that I got from Greta Wilson. So the first one is not your mother's curl talk. This is a defining cream and you're going to put, or at least I put about that much on one side. So I'm going to do this side first and I'm just going to make sure that all the strands are covered first before I start scrunching. This is good for frizz and it also just helps your hair hold its texture. So now we're going and doing our sixth grade inspired scrunching routine. If anyone remembers in middle school, this was the thing to do, at least in my middle school. So you're just going to scrunch it, hold it for a couple seconds. I typically like to do this when my hair is a little more wet than it is right now, but I took a little bit longer getting ready today. So it's already starting to frizz. My hair will absolutely frizz and puff up if I don't put anything in it. So I'm just kind of trying to do this a little bit quickly. Okay, now that that's done, same brand curl talk, but this is the mousse. And this is where I was going wrong in the beginning. I was putting too much because as you'll see, this expands rather quickly. So you need a lot less than you think you do. Like even this, I feel like it's too much. And this is what it holds the curls and it makes them look a lot better. But if you put too much, your hair will have that wet look. You know what I'm talking about? Or even when your hair is dry, it looks like it's soaking wet and it's crunchy. And we don't like that. So actually, that wasn't a horrible amount. I used to put more and I was always like, why is it so crunchy? It looks awful. So you need a lot less of this than you think you do. And I'm going to show you an oil that I put in later to kind of get some of that crunch out. I like to put it up in my roots too, just to give the top a little more volume. Okay, this next thing is the thing that I think makes the biggest difference. And it's the kinky curly original curling custard. I got mine from Target, as you can see. One, this stuff smells heavenly. Two, this is the stuff that really is going to like hold your hair. So I take about just a little scoop on the back of my finger, spread it out on my fingers. It's really slimy, but this is what's going to really help your hair actually hold. Because I don't know about you guys, but just a little bit of mousse doesn't do it for me. So I think this is the thing that really makes a huge difference when it comes to the frizz and the hold. A little bit does go a long way with this stuff, though. So just keep that in mind, but always scrunching. I kind of spread it through first and then scrunch and kind of repeat, but you have to kind of help your hair find that texture, if that makes sense. So it looks a little crazy right now. Any residue I have on my fingers, I will lightly put on the top just because I personally do get a little frizz up there, but I don't want to make it oily. So I just put a little bit. Okay, and now it's time for the fun part. So it's time to dry a little bit. Normally I would let it air dry just a little bit before I did this, but because it's already kind of on the dryer side today, I'm good to just do it now. Some people will disagree with me here again. I don't think it really matters what blow dryer you use, but you will need one that comes with attachments that you can take on and off. This one is the Ginry J-I-N-R-I Paris Professional blow dryer. That's irrelevant. I'm going to take this one off and what you're going to need is a diffuser. It's huge. It looks a little scary, but if you have textured hair, it's going to come in handy. So before I turn it on, I'll just explain it to you. I do have it on high heat and I'm going to put it on high. Some people put it on low. It's up to you. And you're just going to kind of place it. Well, first I'm going to go and I'm just going to lightly go over and start to dry the roots, but then I'm going to kind of take the curls and diffuse them that way with the heat coming out. It's just healthier for your hair and it helps also define those curls. So let's do it. So here she is. She's looking a little wild. She's looking a little crazy. She's looking a little big, but we're going to go in with a little curling wand and I cheat a little bit. I like to add some curls on the top layers just to make it look a little more neat and tidy and not so big, but I could leave it like this too and own it and be cool with it. So it's really your preference. This is like a half inch wand. It does have a clamp. I don't use it for this purpose. I just use it like a wand. You can set your temperature to whatever you think it's best for your hair. I personally set mine to 383.  I've had this for years. You just use a little bit and a little bit goes along why that's why I have so much of it left, but I'm going to put a little pea size amount like literally like that one hand on each side and it's really more for the ends and it just helps it to not feel so crunchy. It softens it a little bit. So really whatever oil you use, I think it's fine. I'm not going to tell you to go out and buy this specific one, but this one does work for me and just like that instantly, it's not crunchy anymore. All right. So let's move on. Last step. Okay. So this is what I do without breaking the pieces apart too much. I take a little little pieces like skinny pieces. This is the key to make it look a little more natural and I'm just going to curl. I curl away from my face and then I let it fall naturally so I don't pull anything and it just gives it more of a defined curl. I think you'll be able to see it more when I do a few other pieces. So let's do another one and I usually wrap it three times but that of course will depend on your hair length. Three times. I don't really count so I don't know how long I'm going to tell you to hold it for. Just use your best judgment. Not too long though. You don't want to fry your hair and then just let it fall. You see that? So it's already starting to look a little more put together. So I'm going to keep going and maybe I'll show you the other side when I get there. Okay. So I actually just did my whole head because I'm running a little low on time but this is usually what it looks like and I'm going to hit it with one or two sprays of hairspray in a second. It's not going to be perfect. You don't want it to be. You're not going to get every piece on the curler because you don't want that either or else you know we're not curling our hair. We're just helping the curls along. We're cheating a little bit. I personally just like this look better on me rather than just having it go all crazy especially because when I go outside it usually tends to expand a little bit more which is normal but this is what it ends up looking and honestly it holds really well all day and even tomorrow it'll still have curls in it. So I don't really brush out the curls. I kind of like I said I'm going to hit it with hairspray which I'm going to do in a second and I just leave it. I leave the little ringlets and I think they look cute. All right guys. So yeah I put a little bit of hairspray in it and that is all she wrote so I thought this lighting may be able to show you a little bit better what it looks like but this is the current routine. If you do end up trying it let me know how it works for you. Let me know if you make any alterations because it's totally okay to do that. Everybody's hair is different. My hair personally probably dries completely different naturally than it does from the girl on TikTok because we just have different hair types. So let me know how it works for you. I hope this video was helpful. Thank you guys for hanging out with me for a little bit today and I will see you in my next video. Bye guys.


We are coming to you from the Okinawa Institute of Science and Technology on the beautiful island of Okinawa, Japan to celebrate the launch of ROS, the Rosalind Franklin Forum for Female Scientists, open to all. Viewers are invited to follow along with us at the website. ROS collects career questions from graduate students, post-docs, starting assistant professors and their mentors around the world. Renowned senior scientists also from around the world, from Asia, the Middle East, Oceana, Africa, Europe and North and South America so far, answer selected questions with humour, compassion and honesty. If you happen to work at the research base in Antarctica, please get in touch. With us today are Professor Paola Laurino, bio-organic chemist, originally from Varese, Italy. Erika Fukuhara, Protein Engineering graduate student, whose roots are here in Okinawa. Tato Mohotu, Neurosciences graduate student from Maseru, Lesothu. Sagnita Toledo Patino, post-doc in structural biology here from Morelia, Michioca, Mexico. And Professor Peter Gruess, distinguished molecular cell biologist, president of the Okinawa Institute of Science and Technology, German by birth and upbringing. In short, we are a microcosm of the United Nations Science Summit itself, and honoured to be with you. I am Amy Stanton-Gooch, a graduate student of OIST. I give you now Professor Laurino. Rosa is our lovely, loving nickname for Rosalyn Franklin, an eminent chemist and crystallographer. In our name we have created a career advisory website for graduate students, post-docs, entering assistant professor and their mentors. Rosa also offers inspiring downloadable posters for supporters and anatomy of a research report, a checklist guide to written and verbal scientific communication. On behalf of Rosa, I am so pleased to welcome and to thank you for joining us. We have selected five questions from the ROS website to consider today, and asked each of you to identify the answer you consider most meaningful and impactful. Nikte, would you kindly read question one followed by the answer you choose, and please let us know why you choose that answer. Sure. So the question I am honoured to read goes on impact, and it reads as follows. In your experience, it is more effective for a new professor to address incremental questions on one topic within her comfort zone, or a second one, to undertake more challenging and possibly more impactful big picture projects, or a combination of both. So it's a great question, and among many other of these answers, I selected one that I really liked, and it goes as follows. I was recruited as a lecturer, and I am now a full professor. Thus, I have walked the full path. As a department chair, I advise new researchers as follows. During the first years until you get your tenure, pursue two lines of research. One in which you have proven skill, and it's the reason you were recruited, and the second that is ambitious. The comfort zone creates a solid basis for publication, and I want your successful and secure tenure. The sky is the limit. Leave your comfort zone. I think this is a great answer because it's very complete from this professor, and it's a great piece of advice because I think we have to be all ambitious, of course, but sometimes taking a step out of our comfort zone doesn't really hit upon us. It's depending on our career stage, or depends on how much resources we have in the lab, etc. So it's very wise to also take it a little bit more wisely, especially for projects that can take, I don't know, 10 years, for instance. And yes, we have to frame well these projects. On the other hand, however, I have to think many times I encounter papers in my hand that I thought, like, why I think him up with that? It's so simple and so beautiful and so short. So, yeah, a little bit of intuition, a little bit of creativity is needed. So that's my opinion. Thank you, Nikita. Does anybody else comment on the first question and the first series of answers about impact? Yeah, I would like to maybe chime in a little bit. I think that that was a really good answer because it focuses on the two aspects of familiarity with something as well as really going out of your comfort zone, but also honing in on the importance of prioritizing which one is more important, especially at the early career stage. So I think that really critically thinking about that and reflecting as a scientist on where you are in the journey and then deciding what's more important, do I do something familiar and get tenure or do I go ambitious? Do I even have the resources, as she has mentioned, depending on which institution you are located? These are so practical that we have to consider everything to make the right decision. So I think that was a really comprehensive answer. I would like to add something also on this answer, which actually was also my favorite one for the first question. A little bit from my experience as a lab head. I called it a bread and butter policy because you always have people that you advise, but you also need to do research at the cutting edge, which is more risky where the probability where this will be successful is unclear. So the right thing to do is really to have a little bit of both the bread and butter policy. Yeah, I think it's also very important. I mean, I'm for the high-risk project. However, it's very important the small project also for the atmosphere in the lab because people grows together and it's important to publish small paper all together. Let's go for the second question. Tato, would you like to read to us the second question and also your favorite answer or what you found more meaningful and impactful? Right. Happy to do so. So the second question is about independence and it reads as follows. First projects are often related to postdoctoral research. How soon must I try to differentiate independent projects from my previous work? And so I posed through the very many answers that we received and actually saw that a lot of them do kind of hone in on very similar aspects, but I did choose one which was my favorite and this was from a person-initialed SI who is in the field of deep learning and artificial intelligence and their answer was familiarity feels safe but only unique research questions are made misgivings that your lab is less your own than an outpost of your advisor's lab. Try not to worry about formulating distinctive questions. They are already taking shape themselves at the intersection of your intuition, the current literature, exposure to professors and speakers and awareness of emerging technologies. Not forgetting the literature of a generation or two ago where pioneers identified then unanswerable, now answerable challenges. What you consider compelling is worthy of your best attention and effort. It will become synonymous with you. So for me this was really interesting and I think it kind of adds on to the first question as well. This answer for me brought home the fact that building one's own scientific identity from the early point is really important and to establish what it is that you are contributing to the field not just what your previous lab in your postdoc time was contributing to the field but at the same time it's also giving some practical advice about the fact that it can be difficult to do so. So they say don't worry about the creative part of how to come up with these distinctive questions. They are already taking shape as long as you are exposing yourself to the literature and to the presentations and such. So I find this aspect kind of encouraging because it's not only saying be independent, be unique but it's also telling you how to do so. And I think for me just on a last note the reason I identified a lot with this is that it kind of reminds me of my own lab. I'm not a postdoc, I'm a graduate student but my current PI is very specific about us owning our own work so when we go to conferences he's always saying if it's your project, you present it I'm not going to represent it for you because I want people to associate your work with you and your face. And at first I found this a bit intimidating when I attended my first conference but I understood afterwards that now people want to know me because they associate my work with me rather than with my boss. So I value this a lot. Thanks so much. Does anybody else want... I think this is the real right attitude. No matter where you come from or what you need to establish and that's why I like this advice to go out to conference you have to establish your profile as an independent researcher that profile may build on your previous work it should ideally not compete with your previous boss but it will, in the context of your independent work it will help you to be visible to the scientific community as the one who is doing this line. That's very important. Does anybody else want to add something or comment something? You know, I think that's just a bit of a silly question. It's a great answer. Yeah, I like the answers that was my favorite for this question and I like that because as a first year student I feel really pressured to be able to come up with my own projects and my own ideas and the fact that as long as you expose yourself to new ideas and continue to read literature things will just come to you naturally and then you have the support of your professors and everyone around you to help you formulate new ideas and to be able to have the courage to explore new areas and really enjoy that. Thank you. Would you like to read the question number three and the answer that you found most important? So the question that I have the privilege of answering or reading today is the states I consider collaboration a source of inspiration and collegiality as well as functionally important at the beginning of my career and my better off seeking collaborations avoiding them in the name of independence or placing myself somewhere on a continuum between the two. And while there were so many wonderful answers that I got to read the one that really stuck out to me the most and the one that I really resonated with the most was a response from a professor researcher from India who goes by the initials RA and her response goes on the one hand do not collaborate automatically a young PI learns by venturing into the unknown to some degree acquiring new abilities instead of immediately turning into colleagues. On the other hand, highly specialized experiments outside your area call for collaboration but consider the big picture do not depend on collaboration for most of the project. So I thought that this answer was the most appealing and the one that resonated with me the most because she gave some really insightful advice for those starting their research career whether it's your graduate student or if you're a professor and I really thoroughly enjoyed that she suggested that it's important that you develop your own foundation that you make your mark that you have to explore unknown areas and that you venture into unknown disciplines and tackle new ideas yourself before seeking the help of others and then when you've established yourself and when you feel a bit more comfortable and you've done a lot more research then collaborations are probably going to be a lot more attractive whenever you want to get into more cross-disciplinary work because seeking the support of others is undoubtedly going to be helpful whenever you come across a time in your project when you need skills and techniques that you don't have and you need the support of others to help you and so I also really liked how she ended her response with saying that you shouldn't depend on collaboration entirely for your project because at the end of the day this project is your own you have to make sure you maintain your independence you maintain the vision throughout your project because you don't want that credit to be taken your ideas, you want to maintain that credit yourself and as a PhD student I feel like I can take this advice currently now and apply it to my graduate studies and continue to carry with me in my future I hope you don't mind if I comment on this as well but this is very short because there are literally today compared to 50 years ago no single author papers anymore so if you look at publications most of the publications demonstrate what you just said you need collaborations for OIST just to give you a number 65% of the OIST's publications are written with an author that is outside of OIST so it tells you if you want to be competitive you have to have the personality go out and engage people engage people with specific expertise to help you in your research yeah I can comment a little bit we cannot be the one man orchestra or the one woman orchestra so I can just agree that we cannot be experts in everything so we need some help and I really enjoy these papers in which you see people using machine learning get another paper, apply to another thing and it's just great so why not? it's just really clear to me that it kind of goes both ways one hand you establish yourself and your expertise and then bring on other people who have their own expertise but also at the same time because you've already established yourself in the field you are going to be sought out too by other people who want to collaborate with you so it is really making yourself more competitive in the field that way so I think that's really important yeah I would like to add something about collaborations of course collaboration is fun and we have to keep science enjoyable Professor Gross as we call here a toy Peter would like to read the question I would like to elaborate on thank you do you agree that interdisciplinarity is the way of the future approximately what percentage of time did you invest in cross disciplinary work as an assistant professor versus today my assistant professorship is long time before I come to the answer that I think represents a certain aspect I'd like to point out that I counted the answers there were 24 answers all of them positive but everyone is supporting the use and the value of interdisciplinary research I give you one from my own background I was almost 20 years working in a Max Planck institute for biophysical chemistry everything under one umbrella this institute has produced four Nobel Prize laureates the prize within the institute and I will mention two the one prize was driven by neuroscience and was given to two people working in the neural department at this institute one was a medical doctor and the other was a physicist and both worked together to develop a method called patch clam patch clam is a method where you have a very fine capillary and you can measure everything through one receptor on the surface of the cell so you can this is important for drug development this is important for science because all kinds of receptor you can test as to what opens the receptor how is the flow of information through the receptor so that's the first and second thing the second Nobel Prize more recently was given to a person who is a physicist but has again worked with a neuroscientist and this person has developed a method that is called stead microscopy you have to understand that in light microscopy so if you want to look at biological material the light microscopy has a certain limitation of resolution which is according it's called abbey barrier has nothing to do with the previous prime minister the abbey barrier is 200 nanometers so you cannot go below a resolution of 200 nanometers but this guy has developed a method called stead stimulation emission depletion which means by means of fluorescent molecules he could go down to 90 nanometers and by now it's in the single nanometer range so you get the message without an environment that is conducive to bring together experts from a variety of areas these Nobel Prizes would not have been worked out I should also say I think you had to set this at the beginning this was only possible because they had a stable funding this would not this would not have been possible with the NIH or a JSPS type grant so after this long introduction after this long introduction the answer the answer that I picked was because it also gives you a little bit of the current thinking in the mainstream research inter-disciplinary has various facets it lends more tools to bigger problems but it can stretch an individual researcher a bit thin though ever present in the biosciences it can lead to falling through disciplinary cracks in reviews try to ensure the right people see and champion your articles and propositions I consider myself 100% inter-disciplinary but because I was also known in a defined area I doubt that others saw me that way again inter-disciplinary is subject to interpretation so this I thought is a very smart answer because it outlines the use, the value but it also outlines the danger many scientific fields are streamlined through the refereeing process so let's say if you are, I don't know what your discipline is so sorry but let's say you are your neuroscientist you are talking about okay and then all of a sudden you are working with a physicist to do something completely different you will have a problem with studies that have seen you as a neuroscientist all your life that this may be valuable for a young person this is even worse because your career is also tracked with what we just discussed you have to get a profile in the young stage of your career in a certain area this profile is added but if you completely move out you will get a complete new profile and you have to consider yourself whether you have enough time to establish this profile having said all of this you need to do what you think will address the scientific question most profitably that's the only thing that matters trust your gut feeling but as I said watch out for the pitfalls yeah the gut feeling is a good point we have to develop a little bit of intuition for approaching people and exactly not deviating too much from our projects because of course we are not experts so it might be dangerous and perhaps this intuition comes with time and experience within the field to know what to look out for and what to watch out for because I think it can be a little bit difficult just entering the field yeah you might learn all the technical words and all it takes time it takes a lot of time so you must be willing to give this time and not be patient and not rush what I do appreciate when it comes to OIST and the setup of OIST if I can talk a little bit about that just the way that our labs are structured it is very easy if you're a person who is pro-interdisciplinarity to actually form those meaningful connections with people who are outside of your lab because we are not divided by departments so we have a neuroscience lab and there's a molecular biology lab right there and there's a chemistry lab right next door so at lunchtime you're talking to these people we have internal seminars for people of different fields and they are presenting in such a way that the information is accessible to you so if you do find some common interests it does make the pathway to making this conversation happen a slightly more easier platform so that the initiation can happen so I think that this is something that other universities might not have that we do have here at OIST yeah there is I think two plus points of OIST of course the support and also the fact that we are not so big I think a small community can interact easier and better rather when it becomes too big probably it's more diluted yes to have interaction with someone really out of your field I'm going to read the last question question number five and I've chosen also one answer which was the most one of the most meaningful actually all of them are very meaningful question five is about advisors and networking the question reads like this how did you build a network of male or female colleagues and mentors who helped and advised you on to the path you took how and where do you interact with these friends today I found particularly interesting the answer of SI she specializes in deep learning and artificial intelligence some curiosity is unusually penetrating well-trained and always on highest alert some people question their own thinking they probe what they encounter or create they make unexpected connection they can summon enormous concentration they express themselves elegantly with economy and evident enjoyment in person and in print we value these colleagues whether senior contemporaries or younger and form life-long association with them I have eight groups I have yet to experience an effective one but certainly consider myself part of a movement promoting inclusivity in science well I found this very interesting actually these and few others I think because she point out that we should not limit our advisors or supporters to collegue in our own field as curious she says well-trained or question their own thinking that can be someone we want to connect and keep connection there is something that many of the senior scientists actually point out is the importance to have collaborator in younger scientists I think often people underestimate this but this is very important and I think also very enjoyable and there is something else that I identify myself I also found difficult to have a mutual eight groups rather I think about advisor as single person this can be a friend from elementary school or senior scientist in another field or someone very close to my field or maybe my direct advisor and another things I identify myself is the fact that yes probably initiate I mean I'm sure initiate Ross because I wanted to promote inclusivity in science does anybody else want to comment or other answer on advisor or networking do you find difficult networking? now I don't find it too difficult but I have to admit that when I was an undergraduate student especially it was overwhelming to approach senior scientists something that I particularly found very useful was that my previous supervisor would help me for example we go to a conference and she would say oh look this is Nikta and she works on this and that I want to talk to her about this and this so it was you know like the big step is done and now you just have to fill the gas so that must be useful and I think the more you do it the more naturally it becomes and you have to forget about being shy I think you want to build a network I agree with having connections with people outside of your scientific circle because it's important to make friends to make colleagues who understand what you're researching but I think I've made a lot of connections with those who are completely different from a field I still have friends who are like in psychology or not even in research at all but they provide me a lot of emotional support to help me get through my graduate studies like going from an undergraduate degree to straight into my PhD it's been extremely difficult but to have friends who can support me overcome all these problems anybody else wants to comment if not we can go on ROS exists to promote scientific inclusivity and diversity through equal full access to important information it should never be necessary to guess or intuit it the custom and criteria of academia there will always be a safe place to ask questions you are never alone ROS is there for you in that light and in closing I call your attention to a second future of ROS we call it anatomy of a research report it is sentence by sentence word by word guide to the scientific presentation and writing you will have to constantly do Nikte did you have a chance to have a look at the research report would you like to call yes I found it very useful I think I think structure in everything brings something useful even when you read an email and somebody writes an email structure you enjoy reading it because it respects your time and everything so it's the same when you have a research report not only you can formulate it better for your supervisors or probably future colleagues that are going to be working on this project but also for the reader in general like for example a paper when it's well written then it's much more easier to get an idea for instance so I think it's very useful and very important to introduce some structure to the research report do you have any advice on scientific writing or communication you better learn it the writing is how you establish yourself for eternity actually in the German language we have the same those who write stay translated so in other words our world is fast and if I go back to the 19th century for example people who are very well known and did fundamental work they published a book or two in their life this is all so you need to learn structured writing and from our point of view I think always it's going to support this we really have courses for for writing, I mean scientific writing hoping that at the end of the day you cannot and will not leave this university without having written your own papers at least the first laugh then go to your 15th I think this is a very considerate approach and I'm really happy that we have it and people can access it because as she said it can be a really overwhelming transition if you're going from undergrad to postgrad and knowing what is expected by the field and the standard and the level of writing this gives us this kind of guideline and I think that it will make life much much easier and will save a lot of time for people to know exactly what's the point of this paper what am I trying to communicate with the aspects that are important and just cut out all the fluff and just say what needs to be said I think it's really important I hope lots and lots of people gain access to it I was actually quite excited to see this because I just started my second year and so now I'm going to have to start thinking about my thesis proposal so being able to communicate all my ideas what's important what's not important how I structure everything how do I organize everything really will take the load off of things help me better communicate my ideas Lastly in addition to question and answer and to our invaluable guide anatomy of a research report ROS also provide a photographic sampling of our strong determining inspiring international support anyone might download their poster in value size and display them on their bench door always or even take them to conference we are proud of this poster to finish I ask you if you can think of any person apart from your doting mother a colleague who gave freely of his or information knowledge skill support to you an helper Tato do you have someone in mind you can just say the first name apart from my doting mother your mother doesn't count you shouldn't say your mom with a someone who provided me freely yes yes knowledge skill support I can say few names for myself I can say recently for a long time Danny Erika for me the first person that always comes to mind is Amy she's been in my life she's helped me immensely since I've been here and she's been super helpful, super impactful she's given me so much guidance and I really appreciate all the support that she's given me since I've been here currently support support because ok this is not my mother, it's close to the mother of my father, my grandmother she gave me so many advices not research related but academic related she always she had no she didn't have the opportunity to study so she told me you better do that to be independent from any man and be independent, I mean she's almost 90 so you can imagine that this is the thinking of the past so yeah that was a good advice I think for me I can think of two people the first postdoc I worked with at OS this was an Abutnaut unit and she's no longer at OS because the lab closed down but her name is Teresa and she's from Mexico and she was the first person to actually teach me a lot of the techniques that I now know in neuroscience because at the time my PI didn't really have the time to be in the lab he was more doing administrative duties and I really relied on Teresa for all of the experimental work but also I remember a high school teacher of mine who once told me that if ever you're given an opportunity to be the first at something to volunteer for something or to initiate something don't ever be shy to raise your hand always be that person who says me and then figure out the steps later but always say me and honestly this has been one of the motors I've used throughout my life and it's gotten me to where I am now because I've not been afraid to just take the plunge when no one else had laid the foundation in front for me I never had to say oh but I don't know anyone at this university how am I going to go I was the first person at OS from my country because of this kind of mindset that I'm not afraid to be the first and this is because of what the high school teacher once said you want to tell us well I can you know of course it's a bit outdated if I talk about my mother but I can talk about other things that I find important throughout the course of your careers and the two elements that we should never forget is be courageous and be critical and the reason I'm saying this is you are now many of you I mean sorry I don't know what state you're at but many of you are learning the trade the trade is experimental the trade is theoretical it gets you ready to be yourself and that's why I'm saying be courageous and be critical so a great poster but if you have advising you sorry but if you have the feeling you have an idea that is different don't be dissuaded that means in science very often it's the path where you pick that is different from the route others take so be courageous be critical you can accept training but at some point you got to find your own way so I ask you for an advisor because Ross wants to be that person for you at Ross you are welcome anytime, any day wherever in the world you are on the clock you are always welcome to visit the Ross website and the answer again I thank each of you for your generosity in participating today we are fully grateful for countless form of encouragement and assistance given by OIST and we are honored to have taken part in this United Nations Science Summit bye for now bye


The first item of business this afternoon is Time for Reflection, and our Time for Reflection leader today is Dr Rose Riley, MBE. Presiding Officer, members of the Scottish Parliament, thank you for letting a wee lassie from Sturton address you today. Today, female football players still struggle for equality. I had my own struggles. At school I wanted to play fitba, but that was not allowed. I loved football, so I played every day anyway, and I was belted for it. My headteacher said to me, Rose, you're not learning. I replied, no sir, it's you that's not learning. I never held a grudge. I moved on and tried harder.  During my career I experienced name calling. Today this would be considered a hate crime. Back then it was just a bit of banter, but it was wrong. It was horrible, it hurt. When I got older to turn professional I went to France and then Italy to develop my career as a football player. I was seen as a pioneer back then. Seeing all the cities of Europe, winning cups, trophies and medals, living in the best hotels, it must have seemed glamorous. It was difficult at the start until I learned the language. I had no support network, but football kept me going. My reward for my pioneering work in football was to receive a lifetime ban from the SFA. Instead of being supported I was rejected. Where I could have been used as a positive role model to inspire females I was disowned. Those challenges I faced were wrong. Horrible and it hurt. I'm not bitter. I forgave the SFA and I moved on. I believe what I did back then has helped young girls in Scotland realise that they can do whatever they want as long as they work hard to follow their dreams. Today I support young girls to get involved in sport and physical activity so they don't face the same hurdles as I did. I am grateful that my work has been recognised in Ayrshire, where I have a sports centre named after me in Sturton. At Ayrshire College I have a football academy for girls, which provides free football and free kit to all participants. I am fortunate that I have been able to give back to the community where I was born and raised. The look on the faces of those wheel asses playing for fun is as good a feeling as any goal I scored or any trophy I lifted. The awards were great but the rewards are greater.


Hey Psych2Goers, welcome back to another video. Healing is not easy. There's a lot of stigma regarding going to therapy and doing any independent inner self-work. It's still seen as something that either weak or crazy people do. That's just not true. It might not be 100% easy, but healing is a journey that leads to deep fulfillment that nothing outside of you could shake or take away. This process is very humbling, but with high risk comes high reward. During this journey, you will start to feel the growing pains of change and self-integration. Keep moving forward. This discomfort is helping you move into a beautiful life in which you have a deeper sense of inner peace. Here are nine uncomfortable signs that you are healing. Number one, you allow yourself to feel your emotions. When you're still stuck in survival mode, you're mostly focused on logic and what you see because emotions are painful for you to feel in process. It's hard for you to take the time and make room for your emotions to just be acknowledged and validated because it reminds you of hurt that you would have liked to keep buried. When you heal, you start acknowledging your negative and positive emotions because you realize that extreme focus on one is detrimental to your whole being and that you are a whole person. It's uncomfortable at first, but as you are no longer suppressing or denying them, you see the value of your emotions and feelings and of just letting yourself sit with them and allowing them to pass. Number two, you're getting better at expressing and maintaining boundaries. When you're not healed or in the process, you struggle with stating and enforcing boundaries because you're afraid of rejection, feelings of shame and guilt from putting your own interests first or saying what's on your mind. It's unusual to set firm boundaries when you're not used to it, but once you start, it creates more healthy interpersonal dynamics because you stated your opinions and emotions. You have the mental and emotional clarity and you are more capable of making your own decisions. Number three, you accept that you've been through difficult experiences. Life is hard and unfair and instead of suppressing all of the experiences that you have been through, you acknowledge and accept that they happened. You accept that these people, places and things had life-changing impact on you and probably still do. Once you have accepted that these uncomfortable events impacted you in their entirety, they actually start to hurt you less because you've accepted the truth and are in charge of the narrative of your life again. Number four, you're less reactive and more responsive. When you're in survival mode, everything and everyone is a threat and is treated as such. Nothing is trusted and you don't have time to sit and logically think things through because you are pure action, meeting to defend yourself constantly. Once you start healing, your natural response of lashing out, shutting down, running away or people-pleasing is tested and slowly makes way for questioning your feelings and reactions regarding things. You even find yourself asking, why do I think this way? Where does this thinking come from? You start practicing emotional self-regulation, self-analysis and responsibility. Number five, you realize that healing is not linear. Healing is uncomfortable because you're unearthing and confronting things you would have preferred to keep suppressed. Once you get into the rhythm, you realize that part of that healing is that this distress is okay and normal because it's not a straight road to inner peace and healing. You understand and have experienced the highs and lows of healing and know that the feeling of today will not match the feelings of tomorrow or even later on. Number six, you begin to step out of your comfort zone. Here's the thing about healing. It's not something everyone will do. However, if you decide to, it actually has far-reaching benefits beyond the acceptance and acknowledgement of the traumatic experience.   Scared of making a living situation change? You now are redecorating your bedroom and experimenting with pink colors you never thought you would. Going to a party you don't know before you would have recoiled at the thought. But now it's a little less anxiety inducing and you have a bit more confidence. Number seven, you easily accept disappointments and take them in stride. Life is a balance of success and failure, light and dark, ups and downs. When you're not healing, disappointment hit you like a freight truck to the chest, knocking all of the motivation and passion out of you. With healing, you understand that bad days do happen and can't be avoided but are also temporary. Any disappointments or unmet expectations are accepted and taken in stride. You respond in better, healthier ways that are less reactive. Number eight, you have more inner peace. Healing brings about self-integration.  And if you're not a fan, it's like taking inventory of all of your experiences, painful or not, and seeing yourself as the whole person. You develop this inner peace because you deeply forgive yourself and you can readily forgive others too. By having this peace and integration, you are less likely to self-sabotage because you're no longer a warring country within yourself with conflicting desires and emotions. You reconcile your inner differences, you no longer criticize and dismantle your character in your mind. And number nine, you welcome help and support. The independent survivor has a don't ask for help mentality, maybe because they never got it when they needed it or because of the harsh rejection when they spoke up. They shut down to get by and decided to do it by themselves because they had no choice. With healing, you start to realize that as strong as you are, you can't carry and do everything by yourself. You do need help. We all do and it's available out there for you. You are more open to support and less afraid of having this need for assistance met. The pride and shame you might feel for asking for help are gone because you know that it's okay to let go of the heavy burden on your shoulders and have someone to lean on. Did you relate to any of these points? Do you feel that you are beginning to heal as rewarding as the first step of healing is you will run into the discomfort of your healing and this will try to make you stop to lessen or ignore the pain, but whatever you resist, you prolong. If you are in the healing process, well done. I'm proud of you for doing this work and I hope you can find peace through it. If you're not, that's okay because healing is a long process that takes time. You're still living and doing what you can, applaud yourselves. Did you find this video valuable? Tell us in the comments below. Please like and share it with friends that might find use in this video too. Make sure to subscribe to Psych2Go and hit the notification bell for more content. All the references used are added in the description box below. Thank you for watching and see you next time.


We have a new dashboard for the freedom family. Look behind me. Today we're going to talk about the sponsorship app as well as the small channel spotlight app. But first, we still don't have the dashboard in beta for you to play with and so you get to choose the punishment appropriate for the developers. In the comments below, start your comment with the word punishment. We will use the heartbeat chrome extension to find all the comments where you suggest different punishments. In yesterday's video where we first gave you a sneak peek on the dashboard, click the video right here in case you missed that sneak peek. It'll show information that I don't show in today's video. In that video, you suggested two punishments. Eat raw eggs for every one egg for every 12 hours that the dashboard is late or two more pushups. So let's get creative. What punishments can you devise for the developers? Tell me in the comments below with the word punishment, which we will use heartbeat chrome to find onto today's sneak peek for sponsorship app and spotlight app. Look at the sponsorship app behind me. You will see all the sponsorships that we have gotten for you to help you grow. Each one has an application form where you can sign up for the sponsorship or see the requirements in order to get sponsored. We're making it easier for you to get a sponsorship based on the size of your channel. The second app is the channel spotlight app where we help small channels grow to become bigger channels by spotlighting deserving ones. And here are the current list of channels that we have chosen to spotlight. We will be spotlighting more. I hope you enjoyed this second sneak peek at the new dashboard. I am actually heading out now to meet with an executive who's flying in from Hong Kong. And we may do a deal which I will keep secret for now, but if you get a new announcement on the next George show about a new shiny deal that we have for you, you'll know it was because of tonight's meeting. And I apologize for not having yesterday the $100,000 sponsorship video because of tonight's meeting. I may not get to making today's episode either, but in the comments below, treat this like the $100,000 sponsorship video, help each other grow, give each other tips, graphics, music, anything to help channels become bigger channels because we do notice all of you who help people grow. Alright guys, who am I? My name is George, founder of Freedom and you've been watching Let's Discover Freedom. Click the first video to learn what is Freedom and how it helps you grow. Click the second video to learn about sponsorships for all Freedom Partners, even if you have just 10 subscribers. And click the other videos like How Do I Leave Freedom? to learn more. Click Get More Views to learn how to build your audience faster on YouTube. Click Get More CPM to learn how to make more money from your channel. And click Get More Music to learn where to get more music to spice up your videos. Click the first playlist to watch the George show on Freedom. That's my show. Or watch the Anthony show or the Alex show also on Freedom. And we will grow together as a family because this is the Freedom family. You are part of it. We are all part of it. And we're all growing together. So grow with us and partner with Freedom. That play now button right there on the video bar is all you need to click to get started.