We never thought about it, but being a patient in a hospital can be very lonely. And for a lonely patient, mealtimes can be a highlight of the day. Providing all those meals is a big job and an important thing. Because to help the patients get better, they must get the right food. The food that the doctor and the dietitian ordered. So your job isn't like in some restaurant, no indeed. It's got a lot more to it than that. You're one part of a whole complicated system that it takes to get the right food to every patient at every meal. It all begins when a new patient is admitted to the hospital. For example, this lady just checking in. Mrs. Taylor's ulcer has been acting up, so her doctor has put her in the hospital for some tests. And because of her ulcer, she'll need special food. From now until the time her first meal tray arrives, a lot of things will have to happen. The doctor starts it all when he makes up his orders, saying what he wants her to have in the way of medicines and food. He's like the head of a team. And the team is, doctor, patient, dietitian, and you. From the doctor's orders, the nurse sees that he wants Mrs. Taylor to have a bland diet. She adds Mrs. Taylor's name to the ward diet roster. Meet Mrs. Meadows. At this hospital, her job is called diet aid. In other hospitals, she might have a different title, but the duties would be similar. She's one of the people who comes around to collect the diet roster from each ward. At some hospitals, the diet aids don't need to do this, if there's a pneumatic tube system or some other way of collecting the paperwork. One way or another, the rosters all go down to the clinical dietetics branch. The diet aid checks the rosters against her file cards. She has a card for each patient. These are called dietary history record cards. She checks each name on the roster. If the doctor has ordered any change in the patient's diet, Mrs. Meadows enters it on the card for that patient. When she finds Mrs. Taylor's name on the roster, she makes up a card for her. The diet aids go through every patient in the hospital like that. Every single one, to make sure they have all the diet information all up to date. It's not just paperwork, either. It has to be done right, or the patients won't get the right food. The doctors are counting on them getting the right food so they can get better. Now, what's Mrs. Taylor going to have for dinner? A lot of different menus to choose from. And it's important for the diet aid to pick out the right one. You remember Mrs. Taylor is on a modified diet. Don't afford to make any mistake about it. There's a menu plan that one of the clinical dietitians works up for every meal. The plan lists all the different kinds of food that will be prepared. The diet aid uses it to make up Mrs. Taylor's menu for supper. By the time she's through, the diet aid has checked to see that she has a menu for every patient and that everyone is correct. And she's made up Trey ID tags to go with them. Meanwhile, other members of the team have been busy, too. It would be easier to feed all those people if everyone was eating the same thing. But that's not the way it is in a hospital. Some patients have to have food with no salt.  And the patients are all depending on you to make their food good, and cook it right, and serve it right. There are a lot of good cooks in Army hospitals, and many of them started out in low-level jobs and moved up. Moved up to better pay and more responsibility. It takes a lot of teamwork to get all those meals out three times a day. Teamwork. Not just to get the meals done, but to get them done the way the doctor and the dietitian ordered, the way the patients need them. When you're doing so many trays, it might not seem to make much difference if you get things wrong now and then. But if you were sick in the hospital, you wouldn't want to be served food that made you feel sicker. Every tray, every dish has to be just what the menu slip calls for. Maybe you never thought about it, but you have an important part in helping patients along on the road to better health. It'd make things a lot easier if there weren't always those last-minute changes. But a hospital isn't like that. There are people who arrive just around mealtime, before the doctor sees a patient and decides to change her diet. And every time that happens, it means a change in the meal service. The nurse phones down the new diet information to the clinical dietetics branch. Nobody likes to redo things in the middle of getting a meal out, but part of your job is giving the best possible service to the patients. And the best possible service means there are going to be changes at every meal. So you may as well learn to live with it and don't let it give you an ulcer. As she does her work, the Diet Aid has a good chance to meet the patients and to talk to a lot of different people. Patients that aren't on a particular diet get to select their own food from a number of choices. While the Diet Aid is going around picking up their menu slips, she can talk to them. It means a lot to the patients when somebody from food service asks if everything is all right with their meals. And then she can pass any problems or complaints on to the dietitian. This kind of thoughtfulness is the difference between just doing a job or really being part of a good team. The thing else that you might want to tell me about your food tolerances that I've not asked already. Of course, the dietitian talks to patients too. Do you happen to dislike any food right off hand that you can think of? I don't care for liver. Don't care for liver? No. She has a big job, making up the overall food plans for the entire hospital. But she takes the time to find out the patient's likes and dislikes. These will be entered on Mrs. Taylor's card and the Diet Aid will use them in making up her menus. This is an important part of seeing that each patient is as comfortable and well looked after as possible. Now, if you should have any problems with your diet, there will be someone around to see you at least once a day. OK? Thank you very much. Thank you. Goodbye. Bye. Naturally, the dietitian isn't going to let any patient have foods that aren't good for them. She talks to the doctors about the proper menu whenever there's a question. You know, they say you get out of a job what you put into it. I guess that's as true of food service work as anything else. Dishwashing is a part of food service work too. It may seem routine and unimportant, but it isn't. The machine has to be operated properly and the temperature can't just right up. And you've got to know when something's wrong and take responsibility for telling the supervisor. Because if the dishwashing isn't done thoroughly, germs from one sick patient could spread around the hospital. So the dishwashers are as much a part of the team as anybody else in food service. For Mrs. Taylor and for the sergeant and all the other patients in the entire hospital, you are part of the behind-the-scenes work they don't get to see. But they know you're there working for them. They appreciate what you're doing every day at every meal. They're depending on you to do your job well. Mrs. Taylor says it for all the patients. Thank you. Thank you very much.


Hello and welcome. My name is Shannon Kemp. I'm the Chief Digital Manager of DataVersity. We'd like to thank you for attending Database Now Online, the first occurrence of this online conference produced by DataVersity. We're very excited about today's event and have already heard some great presentations and continue to have a great lineup of sessions for you. And of course a special thanks to all of our sponsors today to help make it all happen. Just a couple of points to get us started. Due to a large number of people that attend these sessions you will be muted during the event. For questions we will have a short Q&A at the end of each presentation today and we'll be collecting questions via the Q&A in the bottom right-hand corner of your screen. Or if you'd like to tweet we encourage you to share highlights or questions via Twitter using hashtag DB Now. If you'd like to chat with us and with each other we certainly encourage you to do so. Just click the chat icon in the top right-hand corner for that feature. For this event we will send a follow-up email next Monday to all registrants containing your unique login to access the recordings and slides from today's presentations. Now let me introduce to you our keynote speaker for today William McKnight who will be discussing selecting a data platform in 2017. Just to give you a brief background William is the President of McKnight Consulting Group. He is an internationally recognized authority in information management. His teams have won several best practice competitions for their implementations and many of his clients have gone public with their success stories. His strategies from the information management plan for leading companies in various industries and William is a mentor in information for a startup accelerator and taught at Santa Clara University UC Berkeley and UC Santa Cruz. And with that I will give the Florida William to get today's keynote started. Hello and welcome William. Hello Shannon and everybody thank you for that and congratulations to everybody really for the wisdom in taking time out of your day today to get some great education here. The speaker list is impressive and I'm proud to be among them and without further ado I'll launch right into my subject here because this is a lot of what I do selecting data platforms for our clients. Not outright selecting them maybe it's recommending maybe it's creating the process by which a selection will occur. That has to be mobilized every client's a little bit different every one of you is a little bit different in terms of how you approach this subject but I want to give you some knowledge for that for that process and I think all of you probably would have heard about all of these platforms I'm going to talk about but maybe seeing them here in one place will help spur some of the proper activity around platforming your data out there today. So okay that's a little bit about me I think we got my my bio down there and top performers realize they need data. I think this is a foundational principle that everyone in data must adopt. If you don't believe this then maybe this is not right for you because we need to be pushing data out to our clients internally as much as they're asking for it and I know that's hard when you're underwater and maybe the the requests are more than what you're able to deliver right now but that's a good thing right that's the you have more more demand than you have supply and I want to keep you in that situation frankly maybe not to an overwhelming degree but we have to be leaders we are sitting on the gold asset really of our organization we're sitting on how our organization is going to compete and get competitive advantage and really sustain or not over the next decade it has to do with data all strategic objectives of your company can be supported if not outright solved with data and so they don't always know all the possibilities but you do or you should and we're going to expand that envelope a little bit today because like I said the top performers realize they need data and I've done some maturity studies otherwise and I have noted that the highly mature with data companies are the highly successful ones in the marketplace there's a strong correlation actually and those industries that are doing more by data are actually doing better than the ones that are not and the companies within those industries obviously that are doing more with their data are doing much better like for example big data you've been staring at this little study here for a bit that's one of many one of many out there the average performers are thinking about big data but the top performers are expanding their big data implementation but we got a platform this data correctly and we have to have the mindset of let's give them all data fast and effectively I've lived through all three of these pillars that you see here many of you have as well but hopefully we've moved our mindset past just give me some data and give it to me fast give me good data but do it efficiently and now it's give me all data fast and effectively and again if your user community if your applications community or is not asking for data that's a problem right there they need to be asking for data we need to be helping them ask if you will that's the leadership and so I will always leave that out there I think that leadership goes a long way in this business of data but we're here to talk about platforms so there are three major decisions when it comes to platform today there used to be fewer than this I'll put it that way and those of you that are doing the same old same old with your platforming decisions a same old same old that you've been doing for the past decade really it's time it's time to think outside the box and time to do something differently I can almost assure anybody that would be on a call like this that you have problems in your organization that can be fixed with something other than the one or the two or even the three that you've been kind of rotating maybe for the past decade there are other possibilities out there and I'm not trying to overload you with technology you know take on these 12 platforms not necessarily but today's world is we got to get the platforming correct for the workload and part b to that we got to make it all work together with data integration data virtualization I'll come back on that a little bit later but those are the two big things it's not about the data warehouse for example being the center of the universe everything goes in it all processing happens there then we didn't quite achieve that we've really backed off strong on that especially since our warehouse is typically on our database and we have these non-relational platform possibilities today that actually have a lot of value proposition for you so the first decision is the data store type do we want a scale out system a file based scale out system or do we want a database yeah it used to be everything with database that was the default that was clearly what we're going to do for everything and we can loosely call these scale out systems databases if you want but technically down at the bit and bite level they're not databases because they don't have the same framework around the data they don't have the same data page formatting and stuff like that going on I'll come back on this a little bit later but then this is a solid decision that you need to make in terms of what's best and I will give you some pointers as we go along how about data store placement emerging over the past I'd say five years we have a real viable possibility here to not necessarily put the data store into our data center you know what that you can walk over there and touch and feel and whatever it's the cloud option that's very viable today and I'll come back on this too because there's different clouds so that is definitely a major decision a third major decision and we're starting to lose sight of this but we should keep it in mind is is it an operational workload or is it an analytical workload now I know you're thinking maybe that well these are blending together and you know the lines getting blurred maybe a tad in my view but there's still distinct there are still distinct workloads and that means distinct platforming solutions for operational and analytical workloads there are they are architected differently to support those different architecture different workloads so these three or three major decisions and three is a nice number for a slide but heck number four decision I would put up here is the split between HDD SSD and in memory because we are starting to be able to exploit a lot more in memory these days so that's becoming much more prominent in the decision-making process so it's not about okay you know what have we been doing for the past few years let's just do that again for this new workload let's think about it at some point you've got to stop and think about it and bring some process into that maybe you maybe you get one or the next one or two wrong but let's start building to where you start getting them right because it has a lot to do with success of the platform of the application and of your business now this slide is a bit of an eyesore especially when I just kind of you know put it up here all at once as opposed to building it but my point is not to go through all the details on here but to show you in context that there's a lot of different platforms that make sense inside your organization if you're a mid-sized organization if that's what you call yourself or above obviously yeah a lot of these platforms are going to make sense so you need a good data architecture you need a good data architect you know one that is looking out for this that knows what I'm talking about here today in detail across the board understanding the cloud dimension to these things understanding what the value proposition of a multi-dimensional database is versus a data warehouse which would be a relational database versus Hadoop versus a columnar database which might be your data warehouse maybe not and then there's in-memory databases so having a tiered architecture especially on the analytical side is very important and knowing what platforms sit in the same tier that's pretty important as well so here's a little exercise for you I like to do this to my new clients come to a meeting and give everybody 10 minutes and a blank sheet of paper let's sketch out our data architecture here and you can you know if you haven't paid attention to date architecture you can see some pretty weird stuff coming back and some pretty disparate stuff coming back and I like to see some even if it's bad a bad architecture I like to see everybody on the same page because then we can start moving forward together so that's a pretty important exercise let's sketch it out and obviously we got start building towards what our future architectures going to look like now on the operational side of things over here where you see no sequel some relational database legacy sources operational applications and so on we have master data management that's pretty important for your so-called enterprise dimensional data and it's pretty important that that be in the operational side of things not over here in the data warehouse so master data management although I'm not talking about it a lot today because we don't put large amounts of data in there it is great for mastering I shouldn't use that word but for organizing the data of that is so important throughout your enterprise your customer list your product list and so on and I'll move on because I'm going to zoom in here on the data warehouse and help you make some of those some of the decisions around that ecosystem as we go along but further on this theme of data our information is exploding our business is real-time all the time and if it's not or you say it's not you need to work on that because your competitors other businesses out there the possibility to exist for you to be real-time all the time as well and we got to get there our information differentiates us our information quality impacts our clients I'm not spending a lot of time here on data quality I know some other speakers have yeah that that is very important throughout everything I say throughout all the platforms I'm talking about all the data you're putting in there and pushing out it's got to be of high quality and that high quality by the way and I'm sure the other speakers talked about this but it needs to be it needs to come from the business in terms of you know what the rules are that you're measuring that quality by we call that a data governance program right so one of the first things I want to do no matter why I'm out of client is to lay down at least a mini data governance program something we can build on over time but something where I'm going to get that business input to what I do because I do want the requirements coming in although that's not the only criteria I'm going to use to platform a workload and we'll get into that so we're in the business of data and we're all measured out there as data professionals our success is measured based upon a finite set of things obviously obviously obviously user satisfaction is very important user satisfaction in our work giving them what they asked for yeah that's all part of it but many of us stop right there as if that's it we've done our job check the box we're done today it's important for a data professional to also spur business ROI and growth through maybe data projects maybe ideas about applications that are in place today for maybe bringing more analytics maybe bringing machine learning and artificial intelligence into some of the things that we do as a company but bringing ideas to the table and taking them for than just the idea but starting to lay out some plans to get to some higher planes in terms of data maturity and finally we are measured on data maturity and what is data maturity is this is it some feral thing that you know we just we just sort of talk about in academic circles no it's about long-term user satisfaction and business ROI it's about being efficient it's about creating an efficient environment that we can add on to without starting all over again every time and obviously many many companies are doing that with their data they don't get any leverage out of what they built before the starting all over you can't do that for very long so data maturity and I have a whole presentation on that this is not that but it is a thing and it is something that's well worth you measuring knowing where you are acknowledging that acceptance being the first step to change right and and starting to get on a path to grow that because that will be highly correlated to your success and to your business success and then of course there's other things that were measured on that I won't get into here but don't forget about our obligation to our business to bring ROI and maturity too often we focus on the I we focus on the tip of the iceberg that's above the waterline we're not focused enough on the data platforms how to how to how to get real leverage is to focus on the data platforms you should be able to put any bi tool on top of a great data platform that has data that has been put into the proper platforms and you should be able to get value out of that immediately the data if well done should be screaming out hey here's what to do with me I'm telling you what to do with me you don't have to get in here and do 10 steps obviously you know we'll get more sophisticated as time goes on and we'll figure out what what else we need to be baking into our data infrastructure but for today many of us are upside down in terms of where our priorities should be let's bring it back to our data platform when I'm platforming I want to know the data profile and I want to know the usage profile I can get a lot out of the data profile though if you can tell me you know the size of the data the profile of the data in terms of you know is it structured or unstructured what some of some sample records what do they look like how frequently is the data coming in where's it coming from how frequently does it need to be accessed or what's the quality of it etc things like that if you can tell me that I can pretty much say without knowing you know the usage pattern of that data where it belongs in an organization because a lot of organizations over time at least they grow their usage capabilities they grow their desires for what they want to do with the data so to platform it correctly you got to look at the profile of the data and too many of us are just looking at the usage profile and I'm telling you that the data profile says a lot about where to put that data if it's unstructured big data and we're into Hadoop in this organization you believe as I do that Hadoop or whatever that you know ecosystem matures into is going to be around for a while that's where it belongs that's where it belongs and the data science of your organization will grow over time as we make more data available you see one thing I do with my clients is we look at all data in the organization and we say is it under management or not and how well is it under management if it's not under management that means that the data is happening but we're not storing it it just happens and it goes away it's very operational and maybe too much too much data is actually going through that process but if you're like let's say you're highly mature with that piece of data it's not only under management it's in the best platform for it to succeed and by the way you can do this across the board with all your data it's under management or not you still wouldn't have done the full job because there's all this third-party data that you can utilize as well it needs platformed as well and so really the there's not a lot of boundaries around what data you can use the only boundaries are your imagination and your data science because when you talk about third-party data there's a lot of data available so as we make our data platforming decisions we are obviously trying to get success out of the workload right okay so what determines the success of the workload performance is number one provisioning how quickly can you get it up and running that's the world today how agile is it scale can it can I start small and grow and not have to you know monkey with that process too much and cost of course of course costs we don't want to overdo the cost equal part of the equation right but performance can override a lot of things if we can give our users better performance out of our platforming decisions they can grow in their capabilities with the data they're not going to be limited because all this query is going to take five minutes and I've only got a half an hour here so this is you know I'll run a few of these and that'll be it they'll get to deeper levels if those queries are popping and that's not going to happen if you do the same old if you haven't thought about it for a while so I'm encouraging you to think about your platforming so that you can give your users performance quick provisioning high scale and relatively low cost I know it's a lot I know it's a lot so there is an increasing probability that platforming selection leads to success again I keep saying same old platform you might as well be throwing a dart against the wall in terms of whether you're going to have success today I know I look at our portfolio of deliveries over the past few years the requirements have gone up tremendously in terms of the number of users the performance expectations the amount of data the complexity of the analytics and so on right isn't that you too well we need to think a little bit differently we need to get into the best category for example if it's a dupe it's a dupe okay if it's for Hadoop data that's the best category for it I didn't say that well if the data profile says put me in Hadoop then the category is Hadoop now there's obviously different distributions of Hadoop if you get it into the right one for you and there is a right one for you you have maximized your probability for success if you get that wrong you still got a pretty good pretty good odds of success but there is an increasing probability that platform selection leads to the success as I've defined it now what about cost what I did is I looked at our the PO's that we've solicited for our clients over the past two years and looked at cost per gigabyte or terabyte or what have you storage level and I cross-referenced that with the functionality and value which is obviously much more subjective now don't take this to say that speaker said put everything in a graph database because it has great functionality at low cost that's not what I'm saying there's a place for all of this in your organization but you're going to but there are some things that are more specialized these are the things that that that these platform categories really tout like for example in memory super fast performance it's it's unparalleled in terms of versus everything else on here now is that important sure I just said it was important right but is it important at all costs are you going to get that exponential value out of it yeah maybe maybe not so for selective workloads you will so it has high special functionality that you're not going to get anywhere else master data management mastering that organizational metadata if you will yeah it's specialized for that it's specialized for that so that's high functionality then you get to things that don't give you a whole lot extra like I do but it is very cost-effective and obviously it's going to grow in its capabilities but keep in mind all these possibilities and we'll drill in here a little bit now let's look at the data warehouse ecosystem something that's been near and dear for me you know for a couple decades now so we got that source data stuff going over there obviously that's a complex ecosystem in and of itself but we want to bring that data over into analytics right so there's the there's the good old data warehouse and it's sort of I don't mean this in a disparaging way we need a data warehouse really pretty much every client needs to put more energy more more dollars really into their data warehouse and they'll get more back out of there than just about any place else in the company you know that's still where we are with their warehousing however however it is sort of the lowest common denominator in many organizations and what I mean by that is you already have 10 workloads in there 20 what have you however you want to count that you got a lot going on in your data warehouses out there I know that well it gets hard to add another one it gets really hard because you got this committee basically now going on that you have to impact and that slows things down a bit like who's going to want to step up and say okay yeah I'll jump in on paying for that that in memory database making our data warehouse in memory that is or I'm good for you know if you want to take a weekend and spend the data warehouse to be columnar or move it off SQL server move it into an appliance yeah I'm good with that no that doesn't happen so the data warehouse becomes kind of a bottleneck in some cases now that being said it's probably best for about good a good 80% of your good old reporting requirements but I want you to get away from just good old reporting all right and get into some other things so at the same level of the data warehouse we've got Hadoop looks pretty big it can be big it's not necessarily bigger in importance but for many of you Hadoop is going to be by far much larger than your warehouse in due time if it's not already then you got other appliances for specialized workloads like I said I've got some very specialized requirements now that I haven't had to deal with for quite a while so exponential uptake in terms of performance expectations concurrency etc you may or may not get that in whatever you put your data warehouse on five ten years ago that may require a separate appliance if you will maybe and obviously we have our data mart later and some of you are looking at going but my data warehouse is on an appliance yeah that's cool as a matter of fact no two shops are the same when it comes to this I am only saying that the interplay here between warehouses and mart and maybe some some some marked at the same level as the data warehouse and Hadoop should look something roughly like this all right we try to bring our clients usually more complicated architectures because of sprawl into some sort of architected fashion and it would look like this moving on you want to consolidate to right fitting right fitting platforms and so within the data warehouse you've got the data warehouse you've got these oldies but goodies they're still relevant and for younger folks that aren't exposed to some of this maybe this theory of behind data warehousing it's still relevant data mart have talked about that an operational data store a staging area an analytical application with specialized needs so the point of this is if you have a sprawl thing going on with your data even though we're trying to platform data correctly going forward you might want to rein in some of that sprawl that you have and put the databases into their right context and the right utility within your organization if it's really a staging area not a data warehouse let's quit calling it a data warehouse let's call it a staging area and then let's build a data warehouse because we all need one and data warehouses belong in on relational databases okay to be sure but what about some specialized workloads okay in-memory databases the benefit speed speed speed speed all day long and also that open speed just opens up the possibility of doing more doing doing whatever you're trying to do on a limited set of data to all data and hopefully that opens up many more possibilities for return on investment from this platforming decision so the considerations are really what data to put in RAM what processing to do in RAM how does the solution handle fault tolerance and how will it integrate with other systems so without going into you know the architecture of these in-memory databases I'm just saying that you probably have a workload or two that you know a single digit number of terabytes let's say but it has performance expectations off the charts and in-memory databases could be a nice solution for that got to make it all work together of course but here's some hardware perspective on that SSD yeah here's some rules of thumb to walk around with your mileage may vary but we're a lot of people out there are still hooked to their HDD this is that fourth decision I was talking about earlier SSD and memory yeah that's sort of the way to go without reading all the numbers that's sort of the way to go and so really open up your mind a little bit or open up the possibilities here to what more memory can do not I'm not talking about an in-memory database here necessarily but just using of using more memory than ever before because of the lower cost that it now has for us and the demand for performance I always want I want to wind up my sales when I'm making these platform decisions I'm not wasting money but if there's better performance to be gained it's not ridiculous to think about I want to do it and I want to do it because that puts the wind at my sales gives me a little more room for error as we go through our design process let's go maybe a little faster which is pretty important as well not that we don't need a great design etc but I just like that wind at my sales now when it comes to cloud that's that other dimension of the selection and this looks a little messy but cloud architectures can be that way you might have for example just honing in on the data warehouse side of things you might put your data warehouse in the cloud well what about your BI might you put them in the cloud what about four systems what about data integration could that be in the cloud what about MDM could that be in the yes to all of the above now is that right for you I don't know let's get let's break that down here in a few slides but I do know that the possibilities exist for all to be in the cloud and all to work together in the cloud and many are making the decision today that their data gravity is in the cloud maybe it's third party apps maybe software as a service apps that they are particularly you know kind of circling the wagons around as key parts of their company well that's in the cloud and so maybe other things in the cloud wouldn't be so bad as well and where do we start though you know I say start with the data now every client different obviously we have on-prem data warehouses with cloud BI with cloud data integration we've got it all going on all of the above right but when a client gives me greenfield we're thinking hard about the data starting with the data putting the data into the cloud and the other things will follow and I think a mature architecture not only has some cloud but has a lot of cloud in it today those are the leading organizations they figured out a way to make it work now there are different cloud models and it's pretty important to get into the right one for you here now private cloud and I kind of have to put I should put quotes around that actually because the term is sort of thrown around pretty loosely I know what you're talking about I think we all need the benefits the true benefits of the cloud and if you're getting that from your private cloud that is great if you're getting elastic scalability if you're getting rapid provisioning if you're getting great charge back if you're getting access to a wide variety of resources then good for you great keep on doing that but so many so-called private clouds don't give you all that that they used to be the system administration group and now they're exercising more control and I guess giving themselves a different label not to be too cynical about things but if it's done well a private cloud gives you control because it's yours gives you the ability to customize you don't have to worry about you know if every other client on this cloud gives you data residency that you can localize as good as possible and it gives you perhaps false but nonetheless trust in your IT organization and the cons of this are the cap X part of this obviously pretty important you got to bring your own dev ops to the private cloud yeah that's a big con to it in my view bring your own back up in recovery etc and I think it can be a con to place a lot of trust maybe misplaced trust in your own IT versus that of a cloud so that is some that is you know an equation to really look at and many are looking at that very intensely when they start to make their decision about private cloud versus public cloud let's talk about the public cloud we know what the big three or four or five are right pros true cloud benefits all the things I mentioned before you got it scalability in spades provisioning very quick operational expensing software as a service application you're already there great cloud gravity going on sharding across the world into all the resources of the public cloud if you need if you need and a big one to me is the dev ops all the non-functional requirements the availability the backup in the recovery the performance etc now cons with the public cloud sprawl so easy to get into anybody with a departmental budget can be getting into that and creating sprawl the long-term cost studies have shown that the long-term cost of the public cloud if it carries out from today linearly into the future would be prohibitive at some point in the I'd say you know upper single digit numbers of years I don't know anybody thinking too much about that because some think that it that will change and it will be it will be actually long-term cost benefit to the public cloud but stop when it's not at that point because if you're just thinking about the storage cost that's not enough that's not enough you've got to think about all the pros of the public cloud so are we leaning that way yeah we're leaning that way for a lot of things you know if the workload dictates that now there's also hybrid and the pros and cons really depends upon where you are in terms of exploiting the benefits and the cons of the private cloud in the public cloud because hybrid can be all over the place but one use for a hybrid cloud which I found pretty interesting is cloud bursting which is using the cloud resources as a failover if you will or as a peak workload type of resources that you can bring to bear you know that late in the month when you have the you know the the mass of processing or whenever it's tricky to set it up that way but many are exploiting that benefit of being hybrid cloud so cloud models it depends think about public don't write it off distributed file systems now this is what no sequel database is so-called database and Hadoop clusters are they are distributed file systems some of us have been around long enough to remember the older file systems pre-data pre-database okay yeah it's kind of like that and you got your data blocks that are spread out across your nodes which are low-cost commodity computers with everything built in but the the value of the distributed file system is it makes it all work together seamlessly now there's no raid and stuff like that the blocks are spread around and if the node goes down which does happen one of the secret sources of these things is that they'll pick up a new node that might be in the same IP range as these nodes and obviously as you can see it can restore all the data so there is a separate piece of understanding to have about how this platform works such that if you are contemplating platforming a new workload can you live without the benefits of a database which has an ID map on the page and references to where the records begin much better at random access and things like that so distributed file systems definitely lower cost but maybe not as good on some of the DevOps and some of the other things today Hadoop is a distributed file system it is the quintessential distributed file system there are many patterns that make sense some before some after the data warehouse we particularly like the data lake and we are architecting data lakes for our clients and finding great utility for them when the client has great data scientists or an emerging data science program I'll put it that way and if you don't you probably should you should work on that so it makes sense in that data science lab pattern for you but some of us are using it as a data refinery which is you know taking off some of the ETL workload which is great we use it for that as well some of us are using it at the back end of a data warehouse or other systems to archive off some of the colder data get it on lower cost platforms where it's still available it's much more available than tape okay so Hadoop is better than tape in this context and it's so much more than that but you know it is it is meeting that pattern quite a bit as a specialized application store one that needs all your unstructured big data your Spencer data your clickstream data your social data your server logs your smart grid data your electronic medical records videos pictures geo location data etc all this data all this data belongs in Hadoop where most of my clients are where most of you guys are I think probably is you got one or two applications going on for that data and so it's not exactly a data warehouse it's a specialized application store we'll learn more to do with that data but we might be summarizing some of that data off bringing it back into our relational database data warehouse which brings me to my final point Hadoop is the data warehouse I'm going to just quickly say no to that idea and move on to the data lake now I'm not going to go through the architecture of a data lake here I talked a little bit about it and one of the nice things of the data lake is it can serve a dual purpose it can also be the staging area for your data warehouse but it can be so much more than that once you get your data scientists involved it actually becomes the place where of course you've got big data but you have all data that the data scientists can utilize because this is their playground now I like to say one step ahead of my users I like to understand exactly what they're going to do with their bi etc I like to offer them data on a silver platter I have not figured out quite yet how to do that for the data scientists and I don't think that they want me to they want access unabated to all data and this would be the place for that in the data lake so we're having fun architecting the data lake and putting that in that ecosystem now there's also no sequel data stores some of you may have been waiting for this and thinking well when they want to talk about that isn't that pretty viable yeah yeah really is you've got key value stores you got columnar stores you got document stores okay they're all twists on the same idea these are scale out file systems for unstructured operational big data and here are some of the use cases for that personalization profile management catalog management that's a big one getting that customer 360 view in play in real time that's huge etc a lot of these things that you see on there now I can't forget about graph databases now if your workload that you're thinking about platforming if you would describe it with the words network relationship object even properties you know these are sort of key words to me to say oh we might want to think about a graph database here and I we think of sort of the quintessential one of these is like Twitter with everybody connected etc well that the nodes so-called nodes in the graph don't have to be homogenous they can be heterogeneous like you see here we've got people we got cars we probably got other things graph graph is great for that as well as a matter of fact if you need super high performance even if it's not you know complex web of a billion nodes you may consider a graph database and finally here's your saving grace if you will here's your catch-all for a case you made a mistake otherwise and you put data into the wrong platform or you spread it around maybe a little bit too much you got data virtualization if you if you accept what I'm saying here today that many platforms are viable within your organization you need the capability to do data virtualization because you're going to have those cases where you got some data over there on Hadoop got some data in MDM maybe some in your warehouse you got to bring it all together are you going to physically move that data maybe for the long term but for the short term I know many are turning to data virtualization to get those reports out etc you need this capability now some of you are going to work in some queries into data virtualization to be just sort of normal that's okay too you don't want to overdo it but it is for those edge queries and for some things that you architect into this pattern and for that catch-all because let's face it we can't put all data everywhere just in case we put data in the best place or two sometimes to succeed and that's it so sometimes that's not enough so you've got all your traditional selection vectors for selecting a data platform here's some new ones these are not to you not your table stakes anymore table stakes yeah do that what kind of indexes do you have you know what your SQL etc but robustness of SQL means more than just you know which SQL version do you have there are some newfound capabilities within SQL that makes a lot of sense for you which I don't time to go into but it's but SQL is still very important built-in optimization across the cloud across data virtualization the optimizers have to do a lot more work today we've been keeping them busy and we're going to keep them busy on the fly elasticity we talk about elasticity do you really have it you need that dynamic environment adoption are you going to be able to take on concurrent usage different patterns of usage at the same time eventually a lot of data platforms will go there so that is something to look at separation of compute from storage very important for the cloud so you can scale those two things independently that is great support for diverse data because obviously we have it today JSON XML other forms of unstructured data coming right down the pike Avro etc so my conclusions for you many data platforms are viable today get the platforming right start with a data store type placement and workload architecture that narrows it down right there you're going to have a handful instead of a whole army of possibilities at that point use the data profile as a strong determinant of the correct platform is it unstructured how big is it what's the frequency of that data etc make sure it will perform now and for unspecified requirements so you might want to get some help at looking ahead where we where we probably going to go with this so that I don't want to I don't want to undo what I'm doing right now in three years it's too soon so let's make sure we get into something scalable analytic platforms should be either staging ODS data warehouse data mart or Hadoop now what I mean there is when you look across the spectrum of your analytic platforms you should be able to label each one of them with one of these labels and if you can't it's not playing a proper role because those are the proper roles for platforms in the analytic ecosystem and finally the cloud now offers attractive options with better economics but there's different flavors of it so you want to get into the right one information is the next natural resource our economy is entirely dependent upon it it's just like sunshine it's just like water we need it it's not going anywhere just keeps replenishing we're not going to run out of it but we may be overwhelmed by it if we don't get our data into the right platforms which brings me to Shannon and I think it's time for Q&A William thank you so much for this great keynote appreciated as always if you have questions submit them in the bottom right hand corner in the Q&A section of your screen and to answer the most commonly asked questions we will be sending a follow-up email on Monday to all registrants with a unique login containing links to those slides and the recording of the section of these sessions and so William why is OPEX a pro is it is easier to have CAPEX project approved than an OPEX project did you say is it easier to approve one versus the other it they are saying that it seems to be easier to approve CAPEX versus OPEX so why is OPEX a pro I guess it would depend on the environment in terms of whether you know which one is easier to approve as I get into the financing of a lot of these options I find that many companies they they don't want to deal with the opera capitalizing the expenses they would much rather operationalize them and and this is sort of the the cloud model right you're going to pay as you go and you're going to be able to expense it as you go as opposed to large capital outlays at the beginning and and it being over thresholds that make you put that on your on your finance financials over the course of years some sometimes it's seven sometimes it's nine depends on a lot of different factors but I know all my clients are pushing me to operationalize expenses as much as possible and I guess it's just sort of the mindset we have going forward trying to bring things in line with you know the quarterly idea and so yeah it just makes a lot of sense that way and if you look at software beyond platforms I know we talked about platforms here but if you look at software software is really good in the same way in terms of their their new pricing models so I think it's just something worth that we need to get used to you know and William but this presentation is really you know it talks a lot about medium and big business and not necessarily micro and small business but for micro small data storage usually decided by application do you have comments on that I think that that's a that's a good observation I think that a lot of what I had to say may be overkill for a small company but the principles are probably still true still hold true they just may not have as many platforms ultimately as a mid-size to a larger company they still compete on data they still need to platform data appropriately within their budget etc etc but yeah that's a good observation I mean they're not all going to be you know maybe deploying in memory databases or even deploying Hadoop you know at least not today I'm this this this presentation is about making a selection today this isn't a futuristic kind of presentation we're you know 10 years from now we really don't know what the platforming possibilities are going to be we can come back and have this presentation look it probably look quite different but we're nonetheless we're making decisions for today and small businesses need to do the same thing and have all the same criteria in place whether they know it or not great and you know what about trust of public cloud the control of your data yeah I mean that's that's number number one or two consideration as people think about the public cloud there's the trust factor you know will my data be secure we need data to not only be secure we need to be compliant and one of the things that you get with a private cloud is you get control over that data you know that it's not going to be you know on a whim Alyssa let's store that data over here in a different country which would for example which would obviously big problem be a big problem today so but I think trust in the public crowd cloud is growing in terms of the security aspect I think occasionally the availability of the public cloud takes a black eye but if you look at it in context you've got it you've got to consider the cloud in context with your in-house capabilities and are they truly any better when it comes to even trust even trust is it truly any better and that's those are some things that you have to look at is it truly better performing are you truly more compliant in-house versus in the public cloud sometimes that when you really look at that equation you find the answers no William thank you so much that's perfect it brings us right to the end of this session and but I'm afraid that is all we have time for and thanks so much to you and for sponsoring and thanks to all of our other sponsors who have make today possible we now have a 10-minute break where we encourage you to network with each other as you hear us get the next speaker set up the next session will begin at 3 30 p.m. Eastern time where we will hear Tim Bergman talk about graph theory you need to know William thank you again so much and thanks to our attendees for joining us so far it's been a great event so far thank you William thank you


Hello, I'm Sun Wei, Project Manager of R.S. Spacing Office. Now we are in much better situation. So here I would like to share with you some of my observations on impact brought by the coronavirus and also some critical reflections. As for the impact on public nutrition, first of all, I would like to say that public trust towards the Communist Party of China has been consolidated. At the very beginning, we ordinary people felt very much confused, worried and even hopeless. But once the government started to mobilize all necessary sources and provide free medical treatment to the people who get affected, we feel more and more relieved and comfortable. Secondly, the term national ecological security was created. The government has announced that the national security or ecological security system will be definitely established in coming years. Also National People's Congress has decided they will seriously discuss the amendment on the law of protecting wild animals. Actually, the trade on wild animals has been shut down right now nationwide. Lastly about the medical care system, the current medical care system in China is insurance based. But this time during the battle against the virus, now medical treatment to the people who get affected is covered totally by the public fund. So we are very much looking forward to the medical care system reform will go into the direction of providing a welfare kind of medical care towards ordinary people. About reflections, public debates on such topics as relationship between the current economic development mode and environment, data transparency, decentralization of decision making on public health emergency, and also reflections on all complaints about slow progress of scientific research and innovation in China, especially on medical care.  Now we are very much used to wearing masks whenever we are outside and we try to reduce the opportunity of dining out, even at the restaurant we are provided with so-called public shared chopsticks or spoons in order to not to mix things up. And also syndication scale has been much more increased. Of course, cleaning things with alcohol always is kind of troublesome but we are very much used to it and we feel confident, especially we feel confident about the future. Thank you.


So this video is actually a video of an animated GIF that's in Blackboard and The reason I'm making this video is just in case any of my students have difficulty viewing that animated GIF I still want you to be able to get the information you need I'm not going to go through and specifically point out, but you're looking for the stars that are moving Noticing where they are in the overall image About how far they're moving and in which direction they're moving So that when you get to the next step, you'll be able to figure out which stars are the matching stars That show that movement so you can measure their parallax So again, this video is just in case your animated GIF is not working for you


A lot of people think that the word discipline for a lot of people has a bad connotation when I'm talking about Self-discipline self-discipline is actually an act of self-love Today I'm gonna be teaching you the five steps to be more self-disciplined and to get shit done today So we're gonna talk about how to build the discipline muscle the discipline habit the way that I see discipline is I don't think anybody is born with discipline. I think that it's something that is Programmed into us whether it's our parents that program it into us or whether we program it into ourselves And I think that I see it as a muscle I see it as a habit and I see it as something that anybody can bring into themselves no matter how lazy or Unproductive they are at this moment and I really got into this because I was talking to my fiancee about it last night when I was driving my truck And we were talking about someone that that she knows that's really discipline and she goes It's really it makes sense though because both of his parents are really disciplined Her mom his mom's real success real successful. His dad is real successful They're both very driven people and it makes sense why he's so driven and I said well What about his brothers and sisters and she said yeah, that's interesting because all of them the entire family is Driven and so it's something that you can learn whether it's learning it from your parents or something that you can instill in yourself As well And so I see it like a muscle the more that you work your discipline muscle the more it's going to grow the more You work a discipline plus and more it's weren't going to grow at this point in time If you don't have a whole lot of discipline it might just be because you got weak discipline muscles It's like you haven't been to the gym Maybe your entire life But if you just decide to start going to the gym and decide to start lifting weights and show up and show up and show Up and show up consistently eventually your muscles will grow your muscles are just going to grow That's the way that your body works. It's the exact same way for discipline for me I was a very undisciplined person for a long time in my life for the first 19 20 years I was completely undisciplined. I didn't like doing any work any of that stuff and Now it's hard to not be disciplined. It's hard to not be driven to get something done And so I know from myself and from other people that I've worked with discipline is something that can be built into you It's not something that you're born with But it's something that can be developed. You don't need discipline for easy things. That's the funny thing about it You need discipline for the hard things. You don't need discipline for you know Sleeping in you don't need discipline for not going to the gym. You don't need discipline to eat a pizza You need discipline to actually do the things that you need to do to move the needle in your life And before we dive into the five tips, I want to tell you something about discipline I think is super important a lot of people think that the word discipline is for a lot of people has a bad connotation if Your child does something or your does something wrong you discipline them if they don't get good grades or they don't act the way they're supposed to if your dog poops on the floor you're going to discipline your dog But when I'm talking about self-discipline self-discipline is actually an act of self-love. It's not a an act of doing something bad It's an act of self-love because you always need self-discipline to do the things that are good for you You don't need self-discipline like I said to sleep in you don't need self-discipline to not work out You don't need self-discipline to eat a pizza you need self-discipline to wake up early to work on yourself You need self-discipline to eat the healthy food You need the self-discipline to get yourself to the gym and so self-discipline is an act of self-love It's not an act of you know something negative, which is a way we usually think of the word of discipline So I want to tell you that before we we dive into it, but it's also not about being perfect You will never be perfect and so you don't need to worry about that It's not about being just like this badass productivity machine all day every single day It's about making sure that you're the majority of the actions that you take are The actions that need to be taken to get you to where you want to be and to move the needle So it's not about being perfect all the time because one of the things I see with people as I start to work on themselves And they start to try to get better is They will be really good for a couple days and then they'll fall off and then they start to judge Themself and they start to feel guilty and then the judgment and the guilt and the shame and the negative self talk Knocks them off path, and they don't do anything to be done. And so I want you to realize you don't have to be perfect It's about winning more than you're losing That's the way that you really get get to move the needle in your house and you're in your life Okay So number one is to challenge yourself to finish every single thing that you start challenge yourself to finish every single thing As you start no matter what it is Challenge yourself to make sure that you get done if you make yourself a salad you have to finish the salad And then if you made the salad you have to put everything away before you can go on to the next thing One of the things that's really interesting that I have a new coach I guess you could say I'm learning how to fly a plane and so I have a certified flight instructor It's funny because he's not teaching me life skills But I see life skills coming through as he's teaching me so he's kind of I like to call in my coach One of the things that you have to do and is when you're about to pre-flight your plane And you're going through the plane you're looking at everything is you have to check the fuel on the plane And you have to go through and in the plane that we have There's five different places where you have to literally take the fuel out So two different places where you have to take the fuel out of the further out on the ends of the wing further and closer to the cockpit and The fuselage and then actually one actually coming directly at the engine where you actually have to literally get the the gas out of There and actually check to make sure that it's good gas and one of the times I left the cup that you put the gas in on one of the wings And he goes this is an important part that you need to learn to learn about aviation is you don't do something else Until the thing that you're doing is done And so even if you're on you know where I've put my gas away The little cup is on the left backside of the plane The where I always am at though is the right wing of the plane So the complete opposite side of the plane And so what he says is even if it's on the other side of the plane You don't do anything else until it's completed So you have to walk all the way to the other side of the plane And you have to put it away and the reason why I love this is because he says in aviation You have to make sure that the thing that you're working on gets done before you move to something else because if you happen to Forget something because you go on to something else because you're distracted that can be catastrophic And so you've got to start to think about yourself in your life in the exact same way And this is what I love about coaches in all different aspects of life Is that no matter how big the thing is no matter how small the thing is Challenge yourself not to do anything else until that thing is done You hear me say it all the time when you wake up in the morning make your bed when you You know have your coffee just clean the coffee mug Whatever is it you're doing if you if you brush your teeth and you happen to you know Brush your teeth and get a little bit that's on the mirror wipe it off when you go when you're deciding What you want to wear for the night and you're changing through all of these different outfits Don't leave all of those outfits on your bed and then go out What you do is you literally figure out what outfit you're going to wear put it on and then hang up again and put away every single article of clothing You've heard me say it over and over and over again, and I just said in another podcast The way you do one thing is the way you do everything And so if you can force yourself to be self-disciplined for the little teeny tiny things like making your bed putting your clothes away Making sure that you wash the dish every single thing that you do You're going to translate that into all of the big things in your life as well And so make sure that you're disciplined in getting every single teeny tiny thing done and finishing what you start Don't allow yourself to stop early because stopping early is also a habit And so if you're trying to develop a habit, what is the habit you're trying to develop? Finishing what it is that you started. So that's the first one step number two is to plan ahead If you want to just be more self-disciplined and get more stuff done start being better at planning ahead It it really boggles my mind How few people plan out their week And then they don't plan out their day in the morning if you take five minutes with yourself Every single morning and ask yourself. Okay, look at my schedule What I have going on today and you take five minutes and you close your eyes and you say hey What do I want my day to look like today? How do I want to feel? I'm going to go through Driving to work being at work the presentation I have to give Lunch the conversation I want to have and you just visualize what the perfect day would look like to you and you plan ahead You'll be so much more productive and it'll it'll be so much easier to be disciplined Whenever you've gone through that another idea of planning ahead if you're trying to lose weight You're trying to get in a better shape. Why don't you just start meal planning? Like plan ahead every sunday create all of your meals And then you don't even have to think about what it is that you got to eat every single day You've already got it made That's what planning ahead looks like to be more self-disciplined if you've got to work out four times a week And that's part of your self-discipline. Why don't you plan out your on sunday? What workouts you're going to be doing day one day two day three day four and plan out the workouts so that when you show up to the gym You don't even have to think you just have to take action And so sometimes one of the biggest resist pieces of resistance that we have towards doing things Is the mental energy that it takes to get ready and prepared for those things But if you can make it easier by preparing ahead of time and already having those things done It'll make it much more easier much easier on yourself to execute what it is that needs to be done And so make sure that what you're doing is you're planning ahead for all of the important things that are coming up in your life as well That will help you be so much more self-disciplined That's number two. Number three is to design your environment. What do you want your environment to look like? How can you create an environment that makes it easier for you to take action or makes it easier for you to Accomplish your goals. So let's say that you want to lose weight Okay, well in your environment of your house in your car where you work all of those things How can you design your environment to help you in accomplishing that goal of being more disciplined for me? I love sugar I think it's amazing and if I have sugar inside of the house It's being eaten by me and I'll probably eat all of it in one sitting And so what I do is I don't allow any candy any of that stuff to be inside the house because I know I I'm weak when sugar's around. It's like the animalistic part of my brain takes over and it's like Go find the sugar and just do it. So to make it easier on myself and to have more discipline I just don't have sugar inside the house makes it easier on me. So if sugar is a thing for you How can you remove the sugar if alcohol is a thing for you? How can we have alcohol? I had a friend that I just spoke to and we were on a zoom call a couple hours ago And I haven't talked to him about three years and I hopped on a zoom call with him and I barely recognized him And I was like, man, what what happened to you like how much weight did you lose? He's like I've lost about 40 pounds. I haven't seen him in three years It's like I've lost like 40 pounds. Like you look amazing. What did you do? He goes, do you want another crazy thing man?  I was just telling you about Then don't go around your friends at a bar because that's going to make it really hard to be less disciplined And so you've got to design your environment to be the environment that you you would want to help you in facilitating your Help you facilitate the accomplishment of the goals or the action that needs to be taken To get you to where you need to be. So number three is to design your environment Number four is to work and to focus on progress not perfection. This is huge for a lot of people Progress not perfection done is better than perfect. So focus on progress not perfection. So, you know, when you mess up, which you will Don't beat yourself up make adjustments That's all you have to do one of the things that really holds people back the most is that when they screw something up they literally drag themself on glass And and just like literally it's like dragging themself on glass of guilt and shame and negative self-talk and being terrible to themself And so many people If they would just stop guilting themselves It would make it so much more so much easier for them to be more disciplined But also get things done that they need to get done, right? So when you mess up, which you will let me say it again You will mess up over and over and over and over again That is part of being human realize that it is about progress And not perfection when you mess up make adjustments. Take a step back and ask yourself what happened and what could I have done better? So if you look at that and you go, okay, well my goal is to not have any sugar Okay. Well, what could I have? I just ate some sugar. What could I have done to have gotten away from that? Well, I probably could have shared my goals with my wife so that she would have known That I don't want to have any sugar and then she probably would have bought that ice cream And I wouldn't have you know pounded that quart of ice cream. Well, okay Now we know we take a step back and we look at it and say, okay Now what I need to do is I need to share my goals with her and say, hey If you want ice cream, you can get it But do me a favor, you know either finish it before you get to the house Or you know hide it from me so I can't see it Whatever it is that you need like literally this I'm not kidding when I tell you this my fiance If she has candy, she hides it from me because she knows that if if I find it, it's gone like it's done It's just it's cashed not happening.  Why? Because it helps me when I don't know that it's there So my environment is is designed in that way But also if I do have a piece of chocolate or do have something Then I don't beat myself up over it because I would say the majority of the days I don't have any and so I'm not going to try to live a life that I don't enjoy And so it's about progress and not perfection or anything else. So that's number four and number five Is reward yourself like it's okay to reward yourself if you have a really good week And let's just let's just stay on this fitness thing that we're talking about And you have a really good week of working out and you have a really good week of eating healthy Have a cheat meal. I remember when I used to be really really big into I was about 20 pounds heavier than I am now And I was had way more muscle I'd still have it if an interval of these injuries that I've had over the past few years I'm sure but I would have one cheat meal a week and it was like the most glorious cheat meal ever I would look forward to that saturday. It was saturday evening I would have that cheat meal and it was like I would go get a pizza And I would eat the entire pizza and then I would have a massive bit of ice cream And then literally almost every single week I would pass out right after because my body was like shut down There's too much going on My body needed to digest all of it But it was so glorious to literally have like this one meal that I could look forward to and then I ate So much all of those things that I didn't I didn't feel the need to cheat the entire rest of the week because I was like Holy crap That was a lot I need to kind of chill out and so reward yourself If you are trying to stay away from sugar reward yourself a little bit of sugar once a week Whatever is you need to do design your environment to help you be more successful to help you get done Whatever is you need to get done if you need to make 100 phone calls every single day in your business Okay, well on the end of friday when you get those 500 phone calls done for the entire week How are you going to reward yourself so? Enjoy your life and what you're doing. Don't be so disciplined that it just becomes Uh monotonous and not fun You've got to have some sort of way to when you do succeed Have a cheat meal if you make 100 calls you get a bag of skittles Whatever it is that's going to help you to reward yourself so that therefore you want to go and be self-discipline again Because you can't be self-discipline all of the time But when you have a reward for being more self-discipline it makes it easier to go ahead and be more self-discipline the next round Hey, thanks so much for watching this video if you want to learn even more about master your mind Click right here and watch this video as well. It's so ridiculously simple how simple life is But we make it so hard


Have you been looking for a Linux distribution that tries to mimic the look and feel of the Apple iPad? No, me neither, but there is a distribution out there that does try to do that. It's called Jingo S. It is a Chinese based Linux distribution. It is based on Ubuntu and it really tries to capture that iPad kind of look and feel. As you can see from the website here at jingo s.com, you know, it looks like it's a really gorgeous kind of interface. Obviously, it's really meant for a touch device, a touch interface. I don't have such a device to test this thing out on. I don't have any touchscreen monitors or anything. So today, I'm just going to take a look at it inside a virtual machine. I'm just going to use the keyboard and mouse to play around with this thing. It's beta software anyway. They just recently put out the first ISO that the general public can take a look at. It's Jingo S version 0.6. So it's not a 1.0 release yet. I will say I know some people are going to have problems with the fact that this distribution is a Chinese distribution, but it is free and open source software. The one kind of sticking point with it, though, is that to be able to get the download link to grab the ISO, they do want you to sign up for a mailing list. They do want you to give an email address in order to then receive an email to get the download link for the ISO. Most people I know are going to have a problem with that. To be honest, I have a problem with that. If I wasn't taking a look at this distribution for purposes of this video, I would never give somebody out my personal email. What I suggest doing, there's a million services out there on the internet to set up a one-time temporary email just to quickly do something like this. So go to one of these temporary email services, grab a temporary email, sign up to get the ISO, and then you never have to worry about them potentially spamming you or selling your address or anything like that. I definitely wouldn't give them a real email address. So let me switch over here to a virtual machine, and this may take a minute or two to load up here in the VM. I'm using Vert Manager here, and I'm using the Vert IO drivers as far as a graphics driver inside Vert Manager. I found that to work quite a bit better than the QXL drivers, the default driver that Vert Manager uses. As you can see when it first booted up, it was running some kind of check disk there. It was checking for errors. And then finally, of course, we get to our, I guess, kind of a login screen here. It's very mobile-like in its interface. Let me move my head out of the way. See, we got the time and date here. And if I, I don't have a mouse, I have this circle, I guess that's imitating, you know, the point of a finger, you know, if I was dragging, for example, this arrow up like you would on a mobile device, you know, we get our keypad here. And from here, we need to unlock the screen. Now I'm just doing this off a live ISO. And the default password is 123456. So I'm going to type 123456. And then you get the welcome screen. And user experience means a lot to jingling. It's asking, do we want to agree to give jingling the company information about our system? So they're going to get, I guess, the type of device we're running this on, information about our hardware, our MAC address, and various things by selecting agree you consent to the collection of your information by us. I'll go ahead and agree for purposes of this video. Then I get a congratulations stating that I am the 1847th user of Jingo S.  And I guess I'm 1847 in the list. So I'm going to click get started. And here we are really inside the interface. The first thing you notice as soon as you get into the actual desktop environment here is that it's a very mobile kind of interface. You see, you have the dock here at the bottom. I'm not exactly sure what Linux dock they're using. Could be something like a docky or maybe latte dock or something like that. And of course, you can drag over or back to the left. So that's dragging to the right, dragging to the left, you have, I guess, two virtual desktops or the most common application anybody's going to use on a computer, whether it be a standard workstation computer or on a mobile device. It's of course, the web browser. And it looks like we're going to use the Chromium web browser here. And let me launch this. Let's see what version of Chromium we are using. This is an Ubuntu based distribution. So it's not rolling release. So Chromium version 90.0.43. I'm not exactly sure how recent of a version of Chromium that is. And how do you close out Chromium? Well, we did have the close buttons on Chromium. But being that this is for a mobile interface, a lot of applications I don't think will have any kind of window direct decorations that you would traditionally click on with using a mouse, right? It's designed for touch. And on a mobile device, what you would do, I think is just drag these out of the way. No, dragging from the top gets you your notifications and dragging back up swipes them away. But if I click on the dock down here, assuming this is my finger, I believe the applications should just disappear. They don't actually appear in the dog, but they do go away. Other than the browser and the calculator, we have our calendar app, we have a clock app, we have a media player, we have MPV media players, we have two different media players. So what is this one? I know what MPV is, but this one here, I am not sure what kind of player this is. Doesn't look like an application that I'm familiar with for Office. We have WPS Office, we have presentation spreadsheets and writer. That's interesting that they're going with WPS Office because that is proprietary software. And you would think they would probably try to stick to free and open source software where possible. So I'm not sure why they wouldn't go with Libre Office or some other free office suite. But WPS Office, I believe the company behind it is also a Chinese based company. So that may have influenced their decision to use the WPS products there. I switched back over to this workspace here. We have Curigami Gallery, KDE Connect. Of course, that's to connect your mobile devices as for syncing between devices, Dolphin. So KDE Connect and Dolphin, KSysCard, KWallet. So these are all KDE applications. And I'm assuming that is what the desktop environment actually is. It's just a very highly customized KDE. If I open a terminal, and I do have the terminal app docked down here in the dock, it was not here originally. How I discovered the terminal originally was I just did a Control Alt T because on a Buntube based systems, you would expect Control Alt T to give you a terminal. And it does this pulls up console, console with a KDE default terminal application. If I do a uname space dash R, we are running kernel 5.4. So that's an older kernel, but that's an LTS kernel. So it should be very stable. Do we have anything like H top installed on the system? No, we don't. It tells us we could do a pseudo apt install H top or a pseudo snap install H top because a Buntube uses the apt package manager. It also has snaps enabled by default. So let's do a pseudo apt install H top. Because we do have the KDE system monitor, the graphical system monitor we could look at. But I like to use the same tool for every single Linux distribution I take a look at. So it makes sense just to check everything in H top, just to make things kind of fair. I gave this VM two threads of my 24 thread threadripper for the CPU. And I gave it four gigs of RAM. And it's not really using much CPU as expected, we're not doing much. It is using though, a lot of RAM, a lot of RAM, 1.8 gigs of RAM of the four gigs I gave this thing. Also notice we have some Wayland stuff going on. So it is using Wayland as the display server, I guess we're rather than Xorg that is interesting. And we have the plasma shield running, pulse audio is running, really there's not much running system D plasma, a pipe wire is running. That's also interesting pulse audio. Yeah, let me quit out of H top. So it's definitely not lightweight, right? This is not going to be a lightweight Linux distribution. But again, this is not for old machines anyway, you can tell this is a much more modern touch kind of interface and it's designed for a modern machinery, of course, I go to the info center, this is KDE's info center will actually tell me what version of plasma they are basing off of yeah, plasma 5.20.2. So and KDE frameworks 5.78 the cute version is 5.15.2. And of course, we would have got the kernel version as well. If I just open this program rather than the terminal and closing this program, once again, there's no window decorations, no traditional clothes buttons or anything. So again, I'm just going to click down here on the dog, and it will go away. Now before we got the notifications by dragging from the top so we can get our notifications, can I dismiss on my can very cool and then just swipe it back up to the toward the top. I will say this actually does work. Like even though it's beta software, I really like the interface like it's very intuitive. I really didn't read any documentation on how to do anything in this. And you don't have to that. And that's kind of the design. That's these mobile designs. Anyway, they're typically very easy interfaces where you just touch something with a finger and it opens and you slide it out of the way when you're done. It's got that that traditional kind of mobile interface. We do have some icons up here. I'm not sure what they do. I think I have to drag them. Okay, so we get not notifications here, but this looks like a, I guess, preference settings for Wi-Fi, Bluetooth, the ringer. Of course, this is a VM, but you know, so we're not really going to get any kind of effects. Audio playback, I guess if I was playing something, if I actually had audio file to play in the media player, it would give us that information here brightness. But I actually just open the sound settings here. Okay. So if you click on, you know, some of the settings, it will actually open up your settings manager. This is the KDE settings manager thingy. For those of you familiar with the Plasma desktop, I don't use Plasma very often. So I'm not not that familiar with a lot of this. But here's where you could change the KDE theme right now. I'm not sure what theme we're using theme. We have choices between air breeze, breeze dark, breeze light and oxygen. Let's see if I go to a dark theme, will I actually respect that? Yes, it will. Very cool. I think that's really all I want to play with here in the settings. We could change the pin for the lock screen if we wanted to. Let me click on the dock to make the settings go away. Looking at the applications in the dock, the first one is the settings manager that we just took a look at. That's just another way to get to it. This icon here that has the GING OS logo on it. I'm not sure what that is. If I click on it, it's our software center, also our update manager. We have 32 updates available. This looks like one of the standard KDE software centers. Is this discover? I believe this is discover. I go to settings. Now how about let's go to about and this is discover 5.20.80. So it is the discover software center. We can do settings installed. It did look like when it gave me the 32 updates. I don't know if you guys saw it when I first opened it. There was an error or something. I don't know if there was an issue with one of the repositories. But then again, this is beta software. So this is not ready for prime time. This is really more of a preview release. And honestly, that's really about all I can show you with this. I mean, it's really just a heavily modified KDE plasma desktop, except it's simplified, right? There's not much to it. You have two virtual workspaces with some some icons on each workspace. You don't have a ton of applications installed by default, but you have enough. You have what you would expect on a mobile interface. I've got to say it does look attractive. And really, once you get the right video drivers working, at least here inside Vert Manager, the performance is actually not bad. Like these animations and everything, they're pretty smooth. Again, considering that this is beta quality software, I'm pretty impressed. I think once this thing reaches a level of maturity where they can put out a 1.0 release, I think people will be pleasantly surprised at how good this particular Linux distribution is. Again, I know some people are going to have a problem with it because it is Chinese based distribution. I don't like the fact that they do include some proprietary applications like the WPS office suite, when really you probably could have found open source alternatives for that. And again, to at least right now, in order to download the ISO, you actually have to give an email address. You have to give them your email address and then then they immediately email you the download link. What I strongly suggest you guys do again, use a temporary email address for all of that. Now, before I go, I need to thank a few special people. I need to thank the producers of this episode. I need to thank Absi, Dallas, Devonfran, Gabe, Lou, Corbinian, Mitchell, Akami, Arch 5530, Chris, Chuck, David, David, David, David, the other David, more David's, Donnie, Dylan, Gregory, Lewis, Paul, pick me up, Scott, Wes, and Willie. These guys, they are my highest tier patrons over on Patreon. Without these guys, this first look at Gingo S would not have been possible. I also need to thank each and every one of these ladies and gentlemen as well. All these names you're seeing on the screen. These are all my supporters over on Patreon because we don't have any corporate sponsors here at DistroDTube. This channel is sponsored by you guys, the community. And if you'd like to support my work, look for me over on Patreon. All right, guys. Peace.