Hello everyone and welcome to our next EDW session called a case study standing up a data governance program and data capabilities during a global pandemic which we presented by Rachel's data governance director at KPMT US and Karam Mahmoud the director of digital management at KPMT US as well. All audience members are needed during these sessions so please submit your questions in the Q&A window on the right-hand side of the screen. And our speakers will respond to as many questions as possible at the end of the talk. Please note that there is a linked form at the bottom of the page titled EDW conference session survey. This is where you can submit session feedback and we encourage you to do so. So now let's begin our presentation. Thank you and welcome Jenny and Karam. Thank you for that. Good morning from Arlington, Virginia where it is in the mid-60s and full of pollen in the air. My name is Jenny Schultz. You heard I'm the director of data governance at KPMG. I started there a year ago or started here a year ago during at the height of the global pandemic and I'm joined by Karam. Karam, do you want to say a little more about yourself? Yeah, hello everyone. Good morning also from Virginia. I've been with KPMG about two years now. I'm a director in our data services practice. Jenny and our peers and we're happy to take you through our case study today. Thank you. So welcome. Thanks for joining. So I'm going to start by talking a little bit about our data journey, how we began, kind of what we've done to stand up our data governance program. And then I'll turn it over to Karam to talk about the data capabilities that are needed to support our data program here at KPMG. And then of course we'll have time for Q&A at the end. So what is KPMG? We are a group of global firms that provide tax, audit, and advisory services to many types of clients. We Karam and I are focused on the United States member firm and it is large. We have, there's over 30,000 people and as you can imagine, lots of data. So where did we start our data journey? It started back in 2018 where we spent quite a bit, quite a bit of map time interviewing dozens of stakeholders to understand what were their challenges with data. Where were they, where were we falling short in either taking too long to meet a client deliverable and maybe we could have done something better or just how do we work better internally to the firm. And this slide is the output of what we learned from all those stakeholder interviews. So why do we need a program, a data program at KPMG? Let's growth, right? We want to be able to increase speed to market. We've got, we want to beat our competitors, you know, get more clients and also potentially provide additional services to our existing clients, right? We want to grow and expand our services and products. And let's talk about, you know, reducing costs. You know, how can we automate all of the data that we have here at KPMG? KPMG has been around over a hundred years and many, a few different forms but in total over a hundred years. And you can imagine that our technology journey started earlier and we've been collecting lots of data for decades.  And we needed a way to, you know, automate some of those cleansing and standardizing activities so that we could spend the time actually providing insights to either our clients or to help us make better decisions internally. And we also wanted to increase the transparency of the data we have and, you know, make sure that folks can get what they need when they need it to do their jobs, right? Enhancing that self-service. And lastly, risk management, right? We don't want to under control our data or over control our data, right? So how do we master our data so that we have good data quality here at the firm? You know, our data is organized. We know what needs to be retained. As you can imagine, you know, we're here not only to provide value through our data, right? And think about data as an asset but also about, you know, again, managing risk. It's kind of that defensive position. We are a highly regulated firm and we have a lot of external bodies that we need to meet their needs. So we want to make sure, again, that our data quality is fit for use and that we are only exposing the data to those who need to know. So this is what we heard from our stakeholders in 2018. And that led to the creation of the department that Karam and I are in. It's called Data Strategy and Operations. And it led to, you know, the hiring of a chief data officer, you know, determining, you know, what did we need to do to help solve these problems and meet the needs of our stakeholders? So this is a view of our data strategy and at a glance here on one slide and I'm going to start from the bottom up. So again, I talked about our group as data strategy and operations and we are here to, you know, implement the data strategy, build a data supply chain from source to, you know, source to target or consumption and everything in between that needs to happen, right? Governance processes, tools, technologies and that you can see kind of in the middle here, all the things we're working on to help and help our stakeholders meet their needs. We've got a literacy program. How do we make sure that we talk the same language? Data governance, which is my bread and butter, right? Making sure that we are treating data as an asset and doing all those wonderful things like, you know, checking for quality and metadata and confidentiality rules. Again, you heard me say we're a highly regulated industry. How do we make sure that we are protecting the data we have we have a lot of data about our clients and we're making sure that we're complying with all the regulations, laws and regulations out there about our data. Data quality accelerators, right? How do we enhance the completeness and accuracy of our data? Again, making sure that our quality is fit for purpose. Creating a metadata source of truth. So again, tools, technologies and processes around enhancing the transparency of our data, mastering our data. Again, we have a lot of data and it's all over. So how do we make sure that there's one golden record so that folks know where to get the best data from? We buy a lot of data at KPMG. So we have a group dedicated to making sure that we comply with those vendor contracts and use that data the way it should be. And then we have a group also focused on building those things that we need at the center, right? So an enterprise data warehouse, a data lake to again provide that one stop shop for those who need the data. And you can see here, moving up from that, the data supply chain, again, from sourcing, just storing that data, using it for advanced insights and analytics and then consuming and reporting off that data. So our goal is to make this kind of a seamless data supply chain that's standardized, consistent and as efficient as possible again so that folks can get the data they need to generate those insights for themselves or for... And again, you already heard me talk about why we're doing this, right? Crease speed to market when we want to protect the firm, decrease costs and make sure that we're managing our risks appropriately. So I view a data program or a data governance program as kind of a culture change initiative, right? This is, yes, somewhat of a data problem, but it's really about culture change. How do we get the firm thinking about data differently? And so we've done this through a couple of ways here. We have training that we deliver again to teach everybody, like what is data governance and management? What are the best practices in the industry? What do they mean? We might be doing them here, but we might call them something different. How do we get everybody speaking the same language and understanding what these principles are? How do we know who our supporters are? Who our detractors are, right? Understanding who our stakeholders are. Again, I said I started a year ago. I have met with everyone and anyone who would accept my meeting invite and just like this, right? Through a computer on a laptop with video, just understanding who they are, what their needs are. Are they going to be able to, are they going to work with us and help us, you know, change the culture of the firm around data? Or are they going to be that, well, I've always done it this way person, right? So really want to focus on those early adopters who will work with us to, you know, again, get these things complicated throughout the firm. So we have targeted communications that go out. We started a newsletter. Again, we are so large. So we have to get creative about how we communicate with folks. You know, one-on-one meetings are the best. But, you know, I can't, I can't meet with 30,000 people one-on-one on a monthly basis. So we have, we've gotten creative presence as well. And we have working groups and a data council, which I'll talk about on the next slide. But it's really about, you know, collaborating as much as we can, understanding what folks need. How can we help them and making sure that the things that we do and accomplish for the firm, we can map them to their business priorities and show them, hey, we've got this new thing, this new data capability or new tool implemented. And here's how it can help you. And then, you know, measuring progress, showing progress, making sure we're transparent at every single stage of everything we're doing goes a long way, right? It builds, it builds adoption. And we've also been working with folks, you know, to be their arms and legs, right? So some of these data concepts are new to the firm. And so we are educating them, again, through large things like training, large efforts like training, but also in a more kind of intimate setting, like talking to them about their area, their data asset. You know, let's talk through, you know, what it means to adopt these data governance and management principles for your area. And here is a view of kind of who we work with in the data governance space. So I mentioned the data council. We set up a data council, again, with leaders across the firm. So we've got, you know, profit centers, right in our advisory tax and audit businesses. And then we also have groups like finance and HR. And so we have a group that gets together monthly to talk about where is the data strategy? You know, how are we doing? You know, where do we need to focus next? Our current effort right now, we just did a data capability assessment. So we're working on getting those results together. And then we're going to be showing them to the data council and saying, okay, help us make a decision about where you want to focus, right? Resources are not unlimited. So we've got to prioritize. Like, what can we work on that can provide the biggest bang for the buck at the firm? And then we also have a data governance working group. We meet every other week. And that is, I would say, kind of more boots on the ground. And they are the same kind of in the same areas as the data council members. But we use them for more of an opera, from an operational perspective. Like, how can we implement these things in the firm? And, you know, they'll be the ones doing that, right? They also make recommendations to the data council on decisions that need to be made. And we have a federated data governance model. So again, we are large. And my team talks about the what, right? What are the rules of the road about data for the firm? And the federated data officers who are most likely some of the same folks in the data council are there to say, okay, here's how we're going to implement this thing in our function. And here's how it'll be most meaningful to our people. Because every business line is different. Everyone kind of has a different mindset in this area. Our ICPMG.  And again, I consider them, they are really helping us, again, adopt and execute what needs to get done to implement these data governance and management best practices. And you'll see over on the top right, we've got some, we have some little icons about how we work together. Now that we are in a global pandemic and, you know, we do have a lot of meetings with folks, but we've been trying to condense meeting times, you know, give people a break, you know, time to step away and get a glass of water in between meetings. So we're doing our part to make sure that it's not, you're not, you know, virtually running from meeting to meeting to meeting. And the data governance standard. So how did we develop and publish the data governance standard?  And I could have said, you know, put a gavel down and said, here have a nice day. Here are the rules. We didn't do that. We took kind of a, again, a shell of what good data governance industry standard, data governance and management best practices are, put them on a piece of paper. And then we went through them with the data governance working group, word by word, line by line. Yes, it was tedious, but we heard the concerns, the questions of the group, they felt bought in because they helped create this document with us. And then that document was also reviewed or ratified by the data council as well. And it took, you know, a fair amount of time, at least six months, if not longer, right, to go through this process. And because there was some education that had to get, had to come with this process. Right, like, why do we need a section that talks about metadata in this document? And so we had a lot of, okay, well, what is this going to mean to me? How is this going to work? So a lot of, you know, a lot of whiteboarding sessions about what this document should say, you know, how it should say it. And so it's, again, my, what's worked well is creating things with this group. And then we did the same thing with the training, right? So once we got the data governance standard with those, again, industry, you know, guiding principles together, we created a training deck and we piloted it with those data governance working group members, right? Ask them for feedback. Tell us what you need, you know, you need to understand more of so that we make sure we meet your needs. And so now we're training on a quarterly basis and, you know, getting the word out about kind of the basics of data governance and management. All right. Now I'm going to turn it over to Karam who is going to talk to you in more detail about, okay, so I've talked to you about our data journey, our data governance program, how we've set it up, who our stakeholders are, how we work together. And Karam will tell you about the supporting tools and technologies that help make this, again, a robust data program. Yeah. Thank you, Jenny. So as Jenny talked about the overarching data governance structure that we have put around, what we also wanted to do from the center, right? Again, coming from the CDO office, we wanted to set up some enterprise data services that we can provide as a foundational capability to our stakeholders. And again, our stakeholders are different functions of KPMG, right? So as Jenny spoke about our functions such as audit, tax, and advisory. So I'll go around this slide. We have four services that we want to talk to you about today that we'll zoom in on in the next 20 minutes or so. So I'll start on the far right top, right? So metadata management is at the heart and the foundation of everything, right? So once we have identified the data owners and a lot of the roles that Jenny talked about, we want to make sure that we understand the business context of the data, right? And this is where we define the business context of the data as well as the technical context, right? So we get the business context and we tie it to the technical information to get a full picture of where our data resides and what does it mean, right? And that's why the value that we're adding to our stakeholders is that we're making our stakeholders and our professionals in the field, we're making them data intelligent, right? We're giving them more awareness of where the data is and also other features that we provide are that, you know, they're able to get their hands on the data. We provide a provisioning service as well where they can get their hands on the data from the metadata management tool. If you come over to the left side on the top, data quality, which is a natural next step after gathering metadata. So once you have identified your critical data elements, we want to make sure we're able to measure and monitor the quality of data in our firm, right? And a lot of the data that we deal with is internal data, business operations data, but it's also our client data that we ingest into the four walls of KPMG and we want to make sure that it's protected and the quality upon transfer is correct. So the value we provide here to the firm is the data health and also the exception monitoring, the root cause analysis, the remediation of the data issues. So that's in essence data quality and we'll zoom into each one of these in a second. If you move over to the right side bottom, we're talking about master data management here. So Jenny hit upon that a little bit, right? So if you have disparate sources across the firm about some of your master data, right? So your client entities, your contacts, your employee data, your vendor data, these are all master data sets that should not have multiple versions of the truth. So master data management attempts to combine this data to create golden records and becomes a single provisioning source for the firm. So we have done that and we have provided customer 360 views to the rest of the firm. And if you come to the left side, last but not the least is policy engine, what we're calling a policy engine, but essentially what it is is data privacy and protection. So if you collect with the metadata, you measuring data quality and health, you're creating single version of the truth from a golden records perspective, then the last part is that you want to protect your data. So if our professionals are trying to use the data for whatever purpose, right? It could be their client engagements, it could be a research assignment. We want to make sure that they use the data according to the policies that govern the data. So as you know, KPMG is a large firm. We have client contracts, we have vendor contracts, we have our own risk policies, our CISO policies, and we have laws and regulations that we have to abide by. All of those can be very cumbersome for a person who wants to just use the data. So what policy engine does is that it provides the transparency of what the data governing rules are and how can you get your hands on the data while staying in bound with the rules. So I've given you an overview of the four services. What I'd like to do now is zoom into each one of them and kind of talk about how we progress them through the pandemic. Thank you, Jenny. So the first service we're going to talk about is a master data management. As you know, the biggest, I would say, foundation of a successful master data management program is building trust with your stakeholders. Because essentially what you're doing is you're going to different stakeholders saying, well, you know what?  And as you can imagine, in a global pandemic, it's very hard to have those face-to-face conversations where you can build the trust, right? And, you know, not all the time we have our cameras on.  She has her cameras on 99% of the time, right? But not everyone has her cameras on all the time, right? But the way we build this trust during the pandemic is that we had to do, I mean, myself, I had to personally do a lot of, I would say, pre-meets and post-meets, right? So you can imagine a lot of those hallway conversations before you go into a meeting room, right? Or after you come out of the meeting room, you debrief for like two, three minutes, right? So those actually turn into, and Jenny talked about condensed meetings, right? Those turn into five-minute, 10-minute meeting calendar invites on the calendar. So that's how we pivoted to building trust with our stakeholders as we wanted to bring them on board with the master data management solution. And if I were to just talk a little bit about what we have on this slide in the middle, I mean, you guys all probably heard people process technology. So again, no bringer here. It's built on people process technology, as well as data domain. So we made sure that we did not start off with systems or applications, right? We started off with domain. So we want to fix our customer data. We want to fix our contacts data or entity data, right? So that's where we started. And, you know, we interviewed folks. We talked about who are all the people involved? What are the current technologies? What are the current processes? And the way we turned that into a value was that, well, a lot of the inefficient processes will go away, right? A lot of the folks who are doing non-value-added work, they can now do value-added work, right? Which is post, I would say, match merge, which is the deduplication process of MDM. So we were able to convey this value to our stakeholders in the pandemic, doing those pre- and post-meetings, having a lot of virtual sessions, and we were able to deliver value. And something I didn't note earlier, around all these data services, we're heavily Informatica-slash-Colibra a shop here. So we're using Informatica solution for our MDM solution here, and it's working great for us. And the other point I want to mention is that we're maturing, right? So we are in our year, I would say, two of our foundational capability, and now we're maturing to some of the next steps, right? So we're introducing new technologies. All right. So we'll move on to the next service. So the next service is data quality. So again, what is data quality? We touched upon this already, but if you look at the slide here, we want to make sure that we put data quality in a fit-for-purpose model, right? So what you're looking at is our framework, which says that, you know what, in any data supply chain from acquisition all the way to storage, all the way to consumption, we want to make sure that we hit five types of data quality controls, which you see at the bottom here, right?  And the reason I mentioned fit-for-purpose is because that became very crucial for us when we were implementing data quality one by one across the firm, right? Because we wanted to make sure that the riskier data, right, or data that has a lot of consumers, right, or that has already identified issues, got heavy data quality versus something, you know, which wasn't hitting any crucial reporting, right? Or, you know, the data wasn't that large or didn't have too many data quality process or existing processes on it. So that helped us implement data quality in a wide area of systems and applications rather than zooming in on one system application. The other point I'd like to mention here is that standardization is very important, right? So you see on the left-bottom side that we have VQ dimensions. So we at KPMG, our data strategy, we have aligned ourselves with the EDM council. Now, if you go outside in the industry, there may be about three, four, five data quality frameworks or dimensions out there. And at the end of the day, most of them say one or the same thing, right? But you have to... The point is that you have to pin yourself to one of the frameworks and dimensions and go consistent at it. So we have picked EDM council, which is pretty comprehensive and we're happy with it. And those are the dimensions that we cover when we implement data quality. Again, so how did we pivot to the pandemic while implementing data quality in our environment? So I would say, of course, the pre-meets and post-meets were important here as well. But in data quality, what became more important for us was virtual sessions because there are a lot of demoing abilities here, right?  So here, the way we pivoted was that we had a lot of virtual sessions, a lot of demos. We memorized our demos and spiel by the end of the day, right? But we were doing a lot of roadshows, a lot of some one-on-one demos, right? Some large demos. And that was very helpful to get the capability understood out there. I think we can move on to the next service here. All right, so the next service is the metadata marketplace. So we have coined the term internally. We call it metadata marketplace. But essentially, this is the metadata management solution we talked about in the original slide. And like I said, this is the foundation of all the services, right? So we have a metadata management solution. It's built on Calibra. And it provides the business context for the data, right? So we're able to define data sets, logical containers. We're able to define business elements, the enterprise definitions. We're able to identify high-level classifications of data. We're able to identify critical data elements as non-critical data elements. So all that is done in the metadata marketplace, which becomes the foundation of that implementing data quality or master data or policy engine that we'll talk about in a second. Again, this is again one of those tools that required visualization, right? Because this is a self-service tool that's available to our entire KPMD US practice. So we did a lot of virtual sessions here. We did a lot of demos. And something creative that we did is that we recorded short videos, right? How-to videos. How do you filter? How do you navigate? How do you search, right? And then we put those short videos on our metadata marketplace training videos page. So that helped alleviate a lot of the one-off questions that we would get. And the last one I'll make on this is that we've also provisioned this tool to request access to the data. So again, some of the data can be accessed, or at least the request form can be initiated from our metadata marketplace tool. I'm getting some questions here on the left. So let me cover this last slide. And I think what we'll do is we'll tackle the questions towards the end because we have about 10 to 15 minutes at the end. So the last service I'd like to talk about is a policy engine. Again, the internal term that we have coined for this solution is policy engine. But in essence what it is is a data privacy and protection solution. So as I talked about, right, that data can be governed through our contracts that we have with the owners of the data. It could be vendor, it could be clients. It could be our internal risk policy, our CISO policies, our risk framework, right? Or it could be laws and regulations. It could be GDPR, CCPA, or our favorite these days, tax center to 16 law. So what we have done in this policy engine solution is that we have brought all those different policies, if you will, and we have centralized them in a very easy to read and easy to process rules. So the rules are on data access, rules are on data usage, rules are on data storage, right, that contractors cannot access this data. Or you cannot take this data offshore, right, to your offshore team. You cannot use this data beyond the original engagement team or something. So what we have done is that we have centralized the rules and we have then applied the solution to different applications at KPMG. And what we're able to do is we're able to classify and tag our data with easy policy rules. So our professionals, before they get their hands on the data, they can see, can I share this data with my offshore team? Can I use this in my data lake for secondary analysis, right? So that has helped tremendously our professionals in provisioning the data and also where they store the data. So another use case for this is that when we store our data, we have different environments, you know, highly secured, medium or less secure. So we're able to use these policy rules to inform our application owners in which area of the application they should store the data. So that has helped us a lot. And again, policy engine, I would say, is one of the very unique solutions we had to actually stitch together multiple industry products from Informatica and build a solution that works for us. And we are in our year one of this journey and we're going to continue to elaborate on this. The point I'll make on this solution from a pandemic pivot perspective is that since this was a large solution which required a very large cross-function, cross-discipline team, we had some turnover, right? So I don't know from folks on the session today who experiences, but COVID was, we experienced some turnover because people were moving locations, folks were more fluid in their destinations. So one point I have there at the top is getting personal, right? So in order to keep the team engaged, keep the morale high. While of course we did that, a lot of that at the top from our CDO and everything, we made sure that we spent time in the beginning and end of our meetings to get to know people, right? We had a lot of new folks joining the team, joining the firm directly on the project. So we got personal with everyone on Zoom, right? On teams. We were asking family questions, house project questions, health questions. So a lot of that helped us retain, I would say, talent and keep up the morale on some of these large projects. I think, Jenny, we have one last slide where we summarize our pandemic strategy. So my throat is dry, so I'll turn it over to you. Thanks.  And when you're standing up a new program, it's even more difficult to build relationships with stakeholders, you know, to Karan's point. Not everyone is on video. You can't interpret their nonverbals. So I try to be on video as much as possible in hopes that others will do it too. So I can get to, again, see their face and know, like, are they scowling? Are they smiling?  Again, to get to know people, get personal, you know, because work and life has just become kind of, you know, one big blended activity now, right? Who does laundry while they're on the phone, how do they fold clothes? It's just part of kind of our daily life now. And again, and working, you know, working virtually, having those meetings with our stakeholders to help, you know, solution things together has been really important, right? Let's brainstorm, let's figure this out together, right? Having that mindset and not just kind of dictating things to people has been helpful. And again, you already heard me talk about condensing meeting times, you know, 30 minutes for that touch point, or could you have a 15 minute? Do you really need an hour, or is it something you could cover in 45, right? So I'm constantly challenging myself and my team to think about, okay, yes, we need to be more intentional about communicating with each other, but can we reduce the amount of time? Because people are, you know, there's just meeting fatigue, right? And staring at a screen all day, you know, by the end of the day, I'm sure you're tired, like I'm tired, so how do we, how do we, you know, get the job done, but think about others at the same time?  Help build that trust, you know, community, you know, follow through on anything that you've promised, you know, again, you know, meet the people, really understand your stakeholders' needs, ask questions, right? And, you know, having those coffee chats and sometimes there were happy hours too, there still are, having those one talks, you know, sometimes people don't feel comfortable in larger meetings, you know, bringing things up, they're more introverted or they wanna take something away and think about it. And again, you know, it really does help, you know, smile, turn on your camera, I know you're not always camera ready, I'm not always camera ready, but when I am, I try to do this as much as I can. So, we call these our pandemic pivots and they have really helped us, again, you know, build relationships, get things done, enhance trust and move our data strategy forward. So, with that, I will open it up for our question part of our session. Thank you both so much. We've got a lot of great questions coming in. We'll get to as many as possible here in the time left. So, I'm just gonna dive in. Thank you for the helpful presentation. Our data governance program was launched this last January, just four months ago. You spoke about training programs. Do you have an, or can you send us some information about your training programs? Yeah, I'll have to see, I'll have to check in to see what I'm allowed to share and what I'm not allowed to share. But yes, we've, you know, we took our data governance standard and said, okay, what are the main topic areas?  What is, again, and by role too, like what does a data owner do? What does a data, what does a data steward do? So, yeah, it's, let me check in and see if I'm allowed to share or what I'm allowed to share. I love it. And may I recommend people connect with you in the spot me app to follow up on that? Is that okay? Sounds good. Awesome. I love it. So how do you provide KPIs on data governance to provide business justification for budgeting and project planning? This was always a tough one. Oh, it's always a work in progress, right? Especially when you're in build mode, right? Which is where we still are from my perspective. So what we did with our data council, every, we run on a fiscal year, right? So September to September. And what we do at the beginning of every fiscal year is say, okay, data council, here are the things that we think we should work on, right? We create kind of a view into a roadmap and we say, okay, do you think this, these are the things that will help you the most, right? Move your function forward or help you with an enterprise service, whatever it is. And we get there by and before we even start working on things because there's no point in us delivering something that no one's going to use or care about. And then we track progress to the items on those roadmaps. Governance is, again, it's difficult to show value quantitatively. But eventually, once you are kind of past that build mode, you can show, hey, there are so many critical data elements identified and so many that have controls on them. Or we have metadata and lineage on them. So it's easier to do kind of after that build phase during build, which is where we are. It's what's the status? What's the progress of this initiative? Are you green, yellow, red, 90% complete, whatever it is. Awesome. Thank you. So have you dealt with archive data, particularly the metadata and decision to load data up to which year? Oh, gosh, because I mentioned how old we are. So it is a, we're taking a risk-based approach.  We are starting with what data is critical to the firm. And that is a conversation with our data governance working group members, our data council members. Which data assets are you leveraging for kind of your most important uses? And that's where we're starting, right?  So that's how we tackle it. How do you handle the debate on data privacy? Any experience with that? Can you say more about the debate? Which debate? I feel like there are a lot of debates. Well, what's the most common debate you've had?  How do you balance making sure that we are complying with those while also you're trying to generate as much value as you can out of the data? There's, there's, it's usually case by case basis. And that's why Karam and team are working hard on that policy engine so that we can create a framework so that it's not always a case by case basis. We don't have to come to the well every single time users and say, do we need, can we use this data for this purpose? It's like, no, let's create a, let's create a standard set of rules as much as we can and say, okay, you know, can you use this data for this purpose? Yes or no? Or yes with some stipulations. And Karam, I'm just assuming that you're, you're letting Jen answer.  We have tons of questions that I got a lot juicy ones after that as well. So yeah, I agree with what Jenny said. I mean, yeah, I mean, not knowing exactly what debate we're talking about. I'm good with that answer you. All right. So then do you adopt tools prior to start of your journey or in the middle of the way? I can take this one. So, so again, strategically, not right in the beginning, right? So we always start with some sort of a data strategy around our services, right? So whether it was MDM or metadata marketplace or data quality, we always start with a data strategy that tells us, defines what the service is, what the problem statement is, what the solution is, which is too agnostic. And then we do vendor landscape. We do a product evaluation. So we have pretty rigid, I would say, processes. And even sometimes if we know of some of the A1 marketplace leaders, we still like to prove out some of these evaluations, right? Because again, we are a very regulated, heavily regulated firm, and we always want to make sure that we have the strategy and the evaluations documented before we jump into any tools, right? So we do our homework basically. So we don't decide tools right in the beginning. It's part of our strategy. I love it. And have you guys done some work yourselves to showcase the significance of true and trusted data? I'm guessing if this is related to maybe MDM. Yeah. So again, the part of our data strategy is some level of data profiling and showing the impact and the extent of the problem, right? As I talked about MDM, there's a huge component of buying and trust. And what we have done in the beginning or what we had done in the beginning was that we picked a few problem areas and we actually profiled the data. We actually pinpointed where the issues were and then we showcased, right? If you clean this data or de-dupe it, what are some of the advantages, right? So yeah, we did do a lot of the work ourselves. And even once we deploy these services, right? I don't know if the question is geared towards that, but we are involved, right? So my team does a lot of the initial false positive reviews, whether it's data quality or MDM. We facilitate with the data owners and the data stewards in diving in the data, right? And approving de-duplication results or root cause analysis, all of that. And I'll just jump in to any of these questions.  So just let me know. Same one from question to question. What tool did you say you used for metadata? Colibra. Colibra, yes. Okay. Did you think KPMG has entered the era of AI machine learning? I can start with that, Jenny, if you want. So as we said, we are, I would say, two years now into our data strategy, right? The Chief Data Officer data strategy. So now we're getting to a point where we're embarking on those, right? So we always had that vision in our data strategy for AI and machine learning. So the tools that we procured, the architectures that we set up, we set up with that in mind that that was coming, right? And now that we are at a point where we have deployed some of the, I would say, foundational capabilities, now we're maturing our services with a lot of the algorithms and a lot of models that help us either in data quality, right? Helping us, nudging us towards some data quality rules that we may have missed or some match merge algorithms or rules that we may have missed from a match merge MDM perspective. So we're definitely embarking on that now that we have deployed the basic foundational capabilities. All right. We have time for just a few more questions here. So I'll sneak in as many as I can. Is KPMG now using cloud computing? KPMG is a hybrid multi-cloud strategy firm. So yes, we have a lot of solutions that are on the cloud, a lot of lakes on the cloud. So we have a solution, but the way we're set up because of our client base, we will always have need for some on-prem data. So that's why our solutions are hybrid. So we're able to support a lot of the cloud platforms, multi-cloud, as well as on-prem solutions. So yeah, we are set up for that. So in regards to the policy engine, is the policy from the engine automatically applied or is it up to the user to actually follow the policy? For example, is it just a reference or does it enforce the rules? Yeah. Do you have a sneak preview or example? Yeah. Good question. So it's actually both. So we have the ability to, for a data owner to fill out a survey and manually classify the data. So I would say semi-automatic where we need some input from the data owner in terms of what they know about the data. But the policy rules are already ingested in our library. So based on that survey, we can automatically hit the survey against the policy rules and the logic we have and then it automatically applies the policy rules with the data set. So again, we're applying it to the metadata. So we're applying it at the data set level and sometimes at the data attribute level. And we're also building a capability where multiple applications can do an automated service call to the policy engine. So again, this is a centralized utility that's set up as a service for other KPMG applications where they can call on the policy engine and classify their data. The manual part is a little bit of the policy rules. They have to be hydrated in our library. But there are some automation, some manual steps there. Right. Well, that just is bringing us to the end of our session. Thank you, Jenny and Chrom for that wonderful presentation. We just want to note again that there is a linked form at the bottom of the page called EDW Confidence Session Survey. This is where you can submit feedback for today's session. That wraps up the session. You are welcome to continue networking with each other and within the SpotMe app. So we take a quick break between sessions. We look forward to seeing you then. Again, Jenny and Chrom, thank you so much. Thank you. Thank you.


Our first caller is Olivia from Florida. Hi, Olivia. How can we help you? Hi guys. Thank you so much for having me on. I'm really excited to be here. Um, I just wanted to say thank you and a quick testament to how awesome you guys are and how much you know your stuff. My fiance was a long distance runner for years ran for a D one school would run like 100 miles a week. Said he would never give up running.  I was like, let me get, let me get you hooked on mine pump and weight lifting. So I converted him over. We ran anabolic together and this guy just hit 225 for bench and like three months of training and I'm still struggling to do a plate. So, but it's fine. Wow, that's awesome to say. Thank you guys for that. Cause now I don't have to go on runs with him. Awesome. No problem. Okay. So I'll give some background info with my question cause I think it'll make a little bit more sense, but basically my questions is how I can train around a busy schedule while maintaining strength gains and compound lifts. So I'm 23 five to about 125 pounds. I ran anabolic from January to March and I loved it increase my strengths and all the big three lifts and definitely put on muscle, especially my quads and glutes cause I need to get new scrub pants and jeans now. I'm a veterinary medicine student and I'm starting clinical rotations and we rotate through different specialties in the hospital every two weeks. So starting Monday, I'll be rotating through our medicine specialty, which is pretty time consuming. The hours are about 6 30 a.m. or earlier to like 7 7 30 p.m. or later depending on the caseload and I'll be on that for four weeks Monday through Friday and possibly weekends. And then I get a four week break of a more normal schedule like eight to six and then I'll have another four weeks going through surgery, which is the same as medicine like kind of six a.m. to like seven or eight p.m. So I won't really have time to commit to foundational workouts on those days. I wanted to start performance because I know the flow is typically in a ball like performance and then aesthetic and also I haven't trained performance style and probably about a year and a half, two years and I've been training full body style since January and before that I spent a whole year training split style. So I feel like my body probably would benefit from that challenge, but I just can't really start that until later in the fall and then I figured I could do aesthetic and spring when my schedule lightens up a little bit. So for the time being, I wanted to get your guys' advice on how I can continue to challenge my body in new ways, especially while not losing strength in my compound list because I'm kind of worried about that a little bit. Yeah, this is easy answer, Olivia. We have a program that would be perfect for you. Maps 15, do the advanced version. Basically you'd be doing about 20 to 25 minutes a day of compound lifts and exercises. So you show up the gym or if you have a barbell at home about 20 to 25 minutes every day, you're doing maybe two exercises and you're not just going to keep your gains. You're probably going to get stronger by following that as long as nutrition is good and as long as you're getting good sleep. I know it's stressful what you're about to do. So that could always throw a wrench, but you'll love it. You're going to be and then when you're ready to do a more traditional workout, then I would switch to mass performance, but mass 15 advanced version done deal. It's centered around two compound lifts a day basically. And so and the way you can run it. So if it's a really busy, stressful week, you can keep the workouts just short the 15, 20 minutes. If you find a day where you have a day off or you're well rested, you can actually combine the next workout together. So if you want to run it for 40 minutes, we wrote it in a way where you could stack it too. So it's like you can have that flexibility of when you're in a time crunch, when you're not quite as rested, you can run just the 15, 20 minute version when there's times where you're like, Oh, I got a whole it's a weekend and I don't have any work this weekend. Like I want to do a full hour type of workout. You can combine two of the workouts and run it like that. So there's some flexibility in it, but running that and since you already own performance, the only other thing that I would say potentially to add if you have like these days where you got some days off or you're really rested and you're like, I want to do a little more. It'd be mobility stuff because you recognize that you've already been running kind of a body builder and split type of routine in full body. You're probably neglecting some, some mobility work. And so we have that in performance. So if you want to, you know, add an extra day in there or something where you're doing something, I would do the mobility sessions that are in performance to compliment maps 15 until you get back to your kind of normal schedule. Yeah. How long have you been working out consistently with strength training? Probably about three years now. You're going to probably get stronger with math 15 then. Yeah, you're probably going to, this is going to, it's likely to be not just something that keeps you strong, but you probably are going to see yourself get stronger. That happened to me when we created the program and I ran it. I hit new lifts, new lift PRs and I totally did not anticipate that. So that's probably going to happen at the very least you're, you're going to just, you're going to feel good. Yes. The frequency element. Yeah. I think people don't realize like how effective that is and just how much you can get just enough and then recover and then just keep that momentum going. But it's definitely not just a preservation type of a workout routine. It's definitely something that a lot of people have gained from. So yeah, the only, the only thing I'd say is just decide if you want to do it in the morning or after work. That's it. Yeah. I'm definitely like a morning movement type of person. I'm so used to like getting up at like 5 a.m. and going to the gym and I feel like if I don't get that movement and if I don't feel like I'm lifting as heavy or pushing myself the way I want to, I'll tend to like freak out and I'll want to over correct for it because I have some bands at home. So I didn't know if I should just switch to bands to save time in the mornings. Like if, if there's a morning where I have to be there at like 5 30 or 6, I was like, well, maybe I could do some bands, but I know like long term, I would just be itching to get back and like lift some heavy stuff. Olivia, literally, this is what you do. Okay. Literally you shower. This is a 20 minute workout. Okay. So you're not even going to sweat much shower. Get, get everything set up. Drive to the gym. Do your 20 minute maps, 15 workout and then go straight to work. Okay. Yep. Yep. That makes sense. And for those, um, the massive team workouts, I also have prime. So I do like a couple of movements beforehand before I've been doing my lifts and sometimes that takes me like 10 to 15 minutes. Would I just be able to cut that out and just go straight into the lift? Depends how good your movement patterns are. Um, so if you've got really good movement patterns and the exercises are not ones that are like really challenging for you to get into, you could do one or two warm-up sets of an exercise and then you're going to be okay. Um, the people that that we have people that wouldn't work. If you're like, man, when I squat, I get hit pain or I really need to make sure I could deadlift, right? Cause I tend to hurt myself in that case. I would say, you know, make sure you do the priming, but if you feel good and you're okay, like one or two sets of warm-up and get into the workout, you can even just reduce it down to one of those mobility exercises and do that beforehand. You know, the most effective one that you need and then, um, to like throughout the day, it's going to be just as effective if you find a moment, uh, to just perform that like for five minutes or something to break up, you know, whatever you're doing throughout the day, that's going to play, uh, that's going to do very well for you. Okay. That makes sense. I'll probably be able to do the, um, like warm-up sets, maybe just like drop the weight a little bit to connect to the muscle and then go for it. That's it. Yeah. Exactly. Cool. So if you don't have mass 15, we'll send that to you. Okay. Oh, awesome. Thank you guys so much. No problem. When are you getting married, by the way? Oh, um, 2025. I want to graduate that school first and get all my ducks in a row. All right. Good for you. Smart. Yeah. Congratulations. Get it. Thank you. Thanks guys so much. You got it. Yeah. You know what's funny? We wrote mass 15, right? And, uh, how many DMs do we get from people who are like, I didn't think I'd hit PR. I didn't think I'd build muscle. Like this is crazy. All the time. Yeah. Yeah. Yeah. I keep getting them. Yeah. It's strange and again, I think that people underestimate, uh, the frequency component. I also think it highlights something else that we have communicated on this podcast and we've admitted ourselves that we're guilty of this is obviously if you listen to a fitness podcast, you probably like fitness. You can do it, right? You're probably, I hope so. And probably a good percentage or even probably fitness fanatics like us. They could benefit from it. And we tend to, we tend to overreach, uh, and over train, uh, and not count all the other stress in our life. Family member dies, school test, work grinding like crazy. Oh, and then I'm crushing the gym too. And it's like, you know, I think a lot of people didn't realize, uh, that maybe scaling back the workout that would not hinder the results infected and accelerating a lot of people. You know, she brought up something else that we, we don't talk too much that about like an example of like where I cut out like my mobility stuff and I think you guys answered it, uh, perfect. And it's like, so if I'm, if I'm going to squat, uh, and you said it's not like that's a movement pattern where I have to do combat stretch. I've got to do like a quick zone one thing and prime my upper back to, to perform a really otherwise my low back will be feeling it. My hips will be feeling it and I'll pay for it afterwards. It's like, it's a non negotiable that, but I can go into a deadlift cold. I can go into even over it. Now, does that mean that I wouldn't benefit from doing prime movements? Absolutely. I would benefit, but I could go into those movements. You can warm up with the movement. That's right. There's certain movements that are just, I absolutely have to prime in order to get myself in a favorable position. Then there's other movements that I can, it would be ideal for me still to prime. And if I have the time, I'm definitely doing it. But if that's something where I'm like, shit, I'm crunched on time. It's okay. I'm deadlifting today. I can get right into that movement. So.


Chapter 1 of the Epistle of Paul the Apostle to Titus, American Standard Version. This is a LibriVox recording. All LibriVox recordings are in the public domain. For more information and to find out how you can volunteer, please visit LibriVox.org. Recording by Sam Stinson by hisfaith.com. Chapter 1. Paul, a servant of God and an apostle of Jesus Christ according to the faith of God's elect and the knowledge of the truth which is in according to godliness and hope of eternal life which God who cannot lie promised before times eternal but in his own seasons manifested his word in the message wherewith I was instructed according to the commandment of God our Savior. To Titus my true child after a common faith, grace and peace from God the Father and Christ Jesus our Savior. For this cause left I thee in creed that thou shouldest set in order the things that were wanting and appoint elders in every city as I gave thee charge. If any man is blameless the husband of one wife having children that believe who are not accused of riot or unruly for the bishop must be blameless as God's steward not self-willed not soon angry no brawler no striker not greedy a filthy looker but given to hospitality a lover of good sober minded just holy self-controlled holding to the faithful word which is according to the teaching that he may be able both to exhort in the sound doctrine and to convince the gainsayers for there are many unruly men vain talkers and deceivers especially they of the circumcision whose mouths must be stopped men who overthrow whole houses teaching things which they ought not for filthy looker's sake one of themselves a prophet of their own said Cretans are always liars evil beast idol glutton's this testimony is true for which cause were prove them sharply that they may be sound in the faith not giving heat to Jewish fables and commandments of men who turn away from the truth do the pure all things are pure but to them that are defiled and unbelieving nothing is pure but both their mind and their conscience are defiled they profess that they know God but by their works they deny him being abominable and disobedient and into every good work repropet end of chapter one chapter two of the epistle of Paul the apostle to Titus American standard version this is a LibriVox recording all LibriVox recordings are in the public domain for more information and to find out how you can volunteer please visit LibriVox.org recording by Sam Stinson by his faith dot com chapter two but speak thou the things which be fit the sound doctrine that aged men be temperate grave sober minded sound and faith in love and patience that aged women likewise be reverent and demeanor not slanderers nor enslaved to much wine teachers of that which is good that they may train the young women to love their husbands to love their children to be sober minded chased workers at home kind being in subjection to their own husbands that the word of God be not blasphemed the younger man likewise exhort to be sober minded in all things showing thyself and in sample of good works in thy doctrine showing uncorruptness gravity sound speech that cannot be condemned that he that is of the contrary part may be ashamed having no evil thing to say of us exhorts servants to be in subjection to their own masters and to be well pleasing to them in all things not gain saying not perloining but showing all good fidelity that they may adorn the doctrine of God our savior in all things for the grace of God have appeared bringing salvation to all men instructing us to the intent that denying ungodliness and worldly lusts we should live soberly and righteously and godly in this present world looking for the blessed hope and appearing of the glory of the great God in our savior Jesus Christ who gave himself for us that he might redeem us from all iniquity and purify unto himself a people for his own possession zealous of good works these things speak and exhort and reprove with all authority let no man despise thee end of chapter 2 chapter 3 of the epistle of Paul the apostle to Titus American standard version this is a LibriVox recording all LibriVox recordings are in the public domain for more information and to find out how you can volunteer please visit LibriVox.org recording by Sam Stinson by his faith dot com chapter 3 put them in mind to be in subjection to rulers to authorities to be obedient to be ready unto every good work to speak evil of no man not to be contentious to be gentle showing all meekness toward all men for we also once were foolish disobedient deceived serving diverse lusts and pleasures living in malice and envy hateful hating one another but when the kindness of God our savior and his love toward man appeared not by works done in righteousness which we did ourselves but according to his mercies he saved us through the washing of regeneration and renewing of the Holy Spirit which he poured out upon us richly through Jesus Christ our savior that being justified by his grace we might be made heirs according to the hope of eternal life faithful as the saying and concerning these things I desire that thou affirm confidently to the end that they who have believed God may be careful to maintain good works these things are good and profitable unto men but shun foolish questionings and genealogies and stripes and findings about the law for they are unprofitable in vain a factious man after a first and second admonition refused knowing that such a one is perverted and sin is being self-condemned when I shall send Artemis unto thee or tychicus give diligence to come unto me to Nicopolis for there I have determined to winter set forward Xenus the lawyer and a Paulus on their journey diligently that nothing be wanting unto them and let our people also learn to maintain good works for necessary uses that they be not unfruitful all that are with me salute thee salute them that love us in faith grace be with you all end of chapter 3 and also the end of the epistle of Paul the apostle to Titus


Good morning Joey. Hello, how are you mate? I've got you now. I am very well indeed Joey.  I'll talk about your colorful past very shortly. But tell me where you stand on this veganism issue. OK, so veganism is a lifestyle which seeks to exclude any animal use. We believe that it's unnecessary to use animals for their body, for their flesh, for their breast milk, for their eggs. Anything that comes from an animal these days is just unnecessary. And we avoid it as far as practically possible. So if you had your way, there would be no cows, no chickens, no hands, no pigs, no sheep in the Irish countryside. Well, inherently, Ireland is a nation of, Ireland and UK are a nation of animal lovers. And we love and care for some animals, dogs and cats and dolphins. But we condemn others to a slaughterhouse for an unnecessary reason. And there's no difference inherently in the way these animals want to live, in the way they feel pain, in the way they suffer. And we just think it's an injustice to these animals. You've made incredible progress. And people who are into turning people vegan and turning your back on the farming industry have made progress. A lot of this down to social media, you're very active on the social media scene. You film what's going on. You go to the slaughterhouses. You follow the farmers to market. They storm into the market. You're pretty vocal in your protest. Yeah, well, the thing is we bring to the light what happens in the dark. And I think if the majority of the public just didn't see the green pastures with the animals grazing and all these high welfare animals, if they actually seen what happens in these slaughterhouses, then they would have a different view on eating the flesh of animals. I've been inside a slaughterhouse myself and it smells like fear, like feces and like blood in these places.  And why did you become so active in relation to this?  You've had your challenges in life. You've been involved in drugs. You've had addictions. You've been pushing the boundaries off the law. What was the road to Damascus moment for you? OK, so I had an epiphany and it happened while I had a period of sobriety and I've seen my life with new eyes. And I'd spent a long period of time in my life taking from people and hurting people around me. And I decided that it was time that I gave back. And I was I always was interested in helping others, helping human beings. But then I realized that there was someone suffering more that didn't have a voice and they were the animals. And I believe that the animals are the most vulnerable and the most innocent beings on earth and they don't have a voice. So I decided to speak up for them.  Farmers across the the UK is doing something that's very sinister and cruel yet and all. We all know farmers. We're related to farmers. We live with farmers. We we see the importance of farming. And we also are very aware of the desire for all those dairy products and meat products. It's it's it's our lifestyle. What why do you feel that you have the right to change that? OK, now, for starters, I want to emphasize this.  OK, I understand that farmers are just supplying a demand for these products and they've been brought up in a violent society that believes animals are here to use. So I don't have a problem with farmers. I have a problem with the practice of using animals for their bodies. Now, now, I believe people think it's just a choice. It's just an arbitrary choice. But the animal has no choice in this dietary lifestyle. Does it? So the animal has no choice. The farmers are making money off the backs of animals. And I want farmers. I don't want farmers to be out of a job. I want them to change the things they farm to the farm plant foods.  And that does not involve a direct victim. What do you say to the people who target the farmers on social media who literally use the word murderer about farmers? I do peaceful, nonviolent advocacy. And I actually train other vegans on how to advocate. And that is not part of the advocacy that I recommend. I recommend polite dialogue. OK, respectful discussion. Now, we have to always have perspective in this situation. Farmers are literally force breeding animals, sexually violating them against their will, sending them on slaughterhouse trucks to be killed against their will. Now, would a bad nasty name that a vegan called you is that really worse than literally killing animals for a living? I don't know. But I still speak to farmers with respect because I don't hate farmers and I understand the conditioning.  OK, so they touch the animals' private parts. They're sexual. They stick their fist inside a cow's anus, hold the cervix.  OK, now, this is all done against the cow's will. They're held down on a rack, very uncomfortable. If this isn't sexual violation, what is? I just don't understand why people wouldn't think that that's sexually violating an animal. Yeah, so I'm not exaggerating. These are actual standard practices across the board for the dairy industry. All animals are sexually violated. They're all impregnated, impregnated forcibly against their will. And they're all slaughtered.  At the end of the line, they're all killed. Joey, do stay with me because I want to find out where you're going to be speaking. You're going to be appearing here in Belfast. And I also want to speak to Sam Chasney. Sam is a beef farmer who's going to have the platform to put the point on behalf of the farming community, the very strong farming community here in Northern Ireland, just after this. Good morning to Sam Chasney, a beef farmer. Good morning, Sam. Good morning, Frank. Good morning, Joey. Hello. How are you, mate? Joey's on the other line. Sam, you've taken a quirk buttering this morning. Farmers in general from Joey's analysis. What do you say? Well, you know, really, this is just another new way of culture legend that we're seeing coming out of the woodwork. I take a Joey's from Australia and he's not really familiar with the animal practices and welfare that we have here in the British Isles in Ireland. You know, farmers in general in Northern Ireland, I can really talk with farmers here. We look after a stock second to none in the world. The practices we have are highly regulated by vets who really at the top of the chain, the veterinary profession is who we have to go by. You talked about slaughterhouses. All the animals go into a slaughterhouse or veterinary inspect it on the way in during the process and actually coming later on the year. I'll be videotaped for any any abuse or maltreatment of those animals. Now, we produce beef here and I thought that any of my animals on my farm were being maltreated or mistreated anywhere. I would be the first in the line. Joey wouldn't be in the first in the line. I would be as many farmers in Northern Ireland would be. We are very, very conscious of our livestock, our animals, their welfare. We treat them with dignity. You know, we are very, very much farmers and environmentalists as well. On this farm here, we have all sorts of wildlife with foxes, with squirrels, with kites, with buzzards. That just doesn't happen with maltreatment of animals. Now, Joey said, yes, we all should be eating vegetables. So where do those vegetables and those other proteins come from? Soya bean comes from South America. Brazilians are cutting down the size of whales every day of rainforest to grow soya. And then it's putting the plane and flowing across the world. The carbon that is produced from those flights across the world are destroying our atmosphere. They're destroying our climate. Yeah, so 91 percent of Amazon deforestation is to grow soybeans to feed your livestock. Defense salmon furnace of the farming industry. I'm going to let Joey reply to that. OK, so I don't deny the fact that you look after your cows. I would never I would never suggest that. The point is, is when you send them on to that truck, even in the most highest welfare conditions, they get a bolt gun in their head.  And that's where it ends. That's where the welfare ends. OK, because that is not looking after an animal. That is using them for their body. And I have 91 percent of the process. I have this. I have witnessed this process and our local and our local are outdoors. And it's instantaneous. It is so quick. These animals do not know where they are irrelevant, irrelevant. They don't want to die, my friend. You know that your cows do not want to die. What what sort of animal do you farm cows? Sorry, do you farm cows or sheep? We have cows and we have sheep. OK, so do you know your animals do not want to die? Our animals don't know. They don't know they have no recognition of what they have. No impending impression of what's going to happen. That's what I say. This process is so smooth and slick. I understand you come from Australia. I understand some of the practices that happens of livestock haul to Indonesia on ships. I understand. Now, I've seen UK slaughter, my friend. I've seen UK slaughter and it's no better. Just on that, the point that Joey's making is even if the animal doesn't know when it leaves the farm and even if it doesn't know when it's getting off the lorry at the marked, it will know when it goes through the door.  Yeah, I mean, I just don't think this is a justification for it. Like, even if a human being didn't know they were about to be murdered, that would not change the fact that it's an injustice to take a human being's life. Now, if your dog, your pet dog, didn't know they were going to be murdered, it would still be an injustice for me to bolt gun them really smoothly, slice their throat, throw it open really cleanly and chop them up into pieces and eat them. They are no different in the way they want to live. Really, Joey, you're trying to change people into the way they eat and the way they think. You know, through evolution, we've all got sets of teeth and those teeth include K9 teeth-raiding meat where we're hunters and guards. Yeah, just hold on, Joey, let Sam finish. I have no problem with vegans. I have no problem. What I suggest is that everybody eats a healthy, very diet. Vegetables are very important in your diet as red meat because it contains bit of B12 and omega fatty acids from Northern Ireland. You can't get that really easily in supplements.   Joey, that's a strong point because, you know, most medics will tell you a healthy, balanced diet includes white meat or red meat, or it includes eggs, it includes cheese. OK, well, the science is on our side here because saturated fat and cholesterol. Cholesterol is only found in animal foods and it builds up in your arteries over time and it's 17 million people die a year of heart disease. Now, part of a healthy diet does not include violence. It does not include the body of an animal who didn't want to die. Animals get all of their nutrients from plants to begin with. We're filtering our nutrients through a dead animal's body that was killed in a slaughterhouse. Vegans are healthier. They have less deficiencies on average than nonvegans. And the peer-reviewed journal, the peer-reviewed studies done by scientists who aren't even vegan, support this as a fat. So it's unnecessary. We don't need to eat animals to survive. We don't need to need it for our health. We're killing them for an unjustifiable reason. Just stay with me, Joey, because I do want to, I do want to, as one final bit, find out where you are because I think people are interested in listening to you or maybe challenging you when you speak, when you speak in public. Sam, how concerned are farmers here? Because this is growing, if you excuse the term, growing legs in terms of social media. A lot of young people are rowing in behind what the like of Joey is saying. And some of them are losing the run of themselves as well. Joey's trying to rein them back in and has criticised them for being, shall we say, aggressive with their terminology and their language on social media. But how concerned are you as a farmer that this may take off now at a global level and people will turn their backs on the dairy industry and the farming industry? We're not really that concerned. But what we must do as farmers is to ensure that what we do is open to critical inspection in which we are. We are very reliant on the veterinary profession and all that.  You do spray crops, the worms are dead, so they're all living animals too. So, you know, the vegan isn't completely, as he says, murder free. No, we're not really that concerned. We're going to have a dairy, a dairy February to put the dairy industry immediately, possibly on a lamb September. And, you know, I have no problem with the vegan. If he wants to take what he eats, that's fair. But don't just ram it down everybody's throat. Let people make a conscious decision. We don't tell people who to vote for. We don't tell people what sort of car to drive. It's a conscious decision if they want to be a vegan, be a vegan. But that's fine. I have no problems. OK, Sam, thank you. So, Joey, people surely should have choice. Yeah, but their choice involves a victim, which everyone seems to forget. The animal doesn't have a choice, OK? Now, vegans are reducing their harm as far as they can, OK? Animals, on average, to get one kilo of flesh, you need 16 kilos of plant matter. So animals are eating way more plants to get that one kilo of flesh than vegans are just eating directly those plants. So plant agriculture would be less. So there'd be less crop deaths and all of that by going vegan. Now, in your choice, there's a direct victim involved, just like any other form of injustice. If it was my choice to beat my wife, there's a victim involved in that choice. Just like in eating animal products, there's a victim involved, a direct victim that has no say in this. So the final question to you, because people either want to challenge you or support you, where are you speaking in Northern Ireland? OK, now, I guess I will be speaking at the holiday in Belfast Centre and I guess that will be my main non-vegan speech for this tour. But the rest of the events will be on how to advocate in a polite, respectful manner, which is what I recommend. I don't recommend people call farmers names.  OK, I just hate the practice of exploiting and killing animals. OK, OK, Joey, thank you, Sam, thank you very much as well. It is some debate, isn't it? Especially when you look at it through the eyes of people living in this part of the world, where there are farms all around. And we have families where some members are vegan and some members are actually involved in the farming industry. How much of a dispute, debate, row is it going to become in the years ahead? We'll be, no doubt, covering it in the future as well. Thanks to Sam and thanks to Joey.


For more videos on people's struggles, please subscribe to our YouTube channel. Hello and welcome back to Around the World in 8 Minutes, where we bring you stories of working class struggle from across the globe. Since April 28th, hundreds of thousands of Colombians have been participating in mass mobilizations as part of a national strike. The strike has seen widespread participation of diverse social sectors from students, feminist and LGBTQ groups, peasant indigenous and Afro organizations, to street vendors and trade unionists. One of the key motivations for the strike was a tax reform bill that would increase taxes for the working class on goods of basic consumption. But demands are much broader than that and include the demand to respect the Havana peace agreements and end to the violence against social movements and more investment in guaranteeing basic rights like housing, education and health care. The strike is making history not only for the violent crackdown faced in cities and towns across the country by state forces, but also because of the size and popular support. Today on our show we want to discuss another historic strike in Colombia's recent history. The national civic strike of 1977, where hundreds and thousands of workers rose up for many of the same reasons we see people on the streets today. The rejection of tax increase on goods and public services and end to authoritarian measures of the conservative government and demands for better working conditions. At the end of the 1960s and beginning of the 1970s, Colombia entered the first phase of neoliberalism. The last National Front Coalition government of the liberal and conservative oligarchies in Colombia had ended in 1974 and Alfonso López Miquelisín had taken office as president. His slogan was convert Colombia into the Japan of South America, prioritizing the development of an export-based economy to benefit local and foreign monopolies. In 1974, in order to address the fiscal deficit, López Miquelisín decreed an economic emergency which hit the working class hard. Inflation skyrocketed, subsidies were eliminated and prices on public services increased. The government of López Miquelisín was popularly called the expensive rule. Social protests and labor strikes began to multiply. In May 1977, during a trade union protest march, the trade union center of Colombian workers led by the workers sector of the Communist Party called for civic strike. The growing unrest and economic hardship meant that the proposal received widespread support from political and social sectors that historically did not align. The four major trade union federations at that time joined forces and called for a general strike with a list of eight key demands which went beyond the demands of the trade union sector and was able to massify the strike and the support behind it. The demands were a wage increase of 50%, price freezing of items of basic necessity and on fares for public services, suspension of the state of emergency and respective liberties, financing and demilitarization of the universities, abolition of the administrative reform, turning over land to peasants, the eight hour workday and basic income for transportation workers and the suspension of decrees that called for the reorganization of the Social Security Institute. Strike preparations were underway in the streets and plazas of major cities for weeks. At the same time, the government of President Alfonso López Miquelesen attempted to stop it from happening. The government started to arrest people that were organizing mobilizations and at the beginning of September, public concentrations were prohibited. The government ignored the list of demands presented by the trade unions and popular sectors and declared that the strike was a subversive action. These repressive actions, far from discouraging the people, heightened tensions and anger at the government. On the night of September 13th, fireworks were set off across the streets of Bogota and people prepared for the blockades of the major roads of the city. On September 14th, workers, trade unionists, teachers, students, housewives, informal workers, members of the community action boards and more took the streets, above all in the capital Bogota, organizing road blockades and effectively paralyzing transportation in the city. For historians and activists, one of the most impressive elements of this strike was that what began as a trade union mobilization became much, much more. On the streets of Colombia, people saw popular unity, the mobilization of unorganized sectors and the emergence of the urban subject that lives in the city's periphery. The strike had become a social outburst, channelizing popular discontent with the government. Such levels of mobilization had not been seen since the 1948 Bogotaso after the assassination of Jorge Elisar Caetano. During the day of September 14th, road blockades were seen across the city marked with burning tires and vehicles and very early on, the police began to carry out violent repression. The anger at the regime and the desperation with the economic situation saw many taking items from large stores which gave more justification to repressive forces to violently attack the protests. Thousands were detained on September 14th alone and brought to the Campín Stadium and Plaza de Toros. Blockades remained throughout the night and police repression intensified at night as well. Estimates vary on the number of injured, but many alleged that the number was around 500 while the number of dead from violent police repression on just that day was 33. The national civic strike has remained in the legacy and historical memory of Colombia's social and political movements. The social uprising and outbursts managed to achieve a never-before-seen level of popular unity on the streets. Beyond achieving certain demands, it was a turning point for movements in urban centers which only grew in size and importance in the following decades. In the national strike this week and in the protests over the past couple of years, we see many continuations of this legacy. The protagonism of the popular urban subject over the traditional worker and the importance of building organization and carrying out political education in the periphery of the urban centers has become vital. We will continue to follow the latest developments with this strike which has already made history. That's all we have time for today and keep watching People's Dispatch.