Hello, thank you for participating in our data governance education series. My name is Kelly O'Neill and I'm the founder and CEO of First New Francisco Partners. We are an information management consulting company. Today we're going to talk about some very fundamental concepts around data governance, such as the data governance framework, and a simple process to get started governing data. Let me also go through what the future modules in this education series will be. Module number two is introducing the idea of an operating model, which is the fundamental structure for creating a data governance organization. Module three then drills down deeper into the roles and responsibilities of the participants of the data governance program. And then module four goes even deeper into the role of one of the critical players, the data steward. And module five will go through the process of how to create a data governance policy and tie it into the guiding principles of the program. Next, we'll discuss general best practices for a successful, sustainable data governance program. And the last module, module seven wraps up the series by discussing data governance and its relationship to other data management activities like metadata management and master data management. And we hope you join us for the whole series. So the purpose today is the starting point for data governance and going through some of the basics. Hopefully by the end of the program you'll understand the critical success factors for establishing a data governance discipline within your organization and that you'll understand the key reasons to implement data governance, why it's critical, why it's important. And at the same time, we'll talk about some things to avoid and some things not to do. So because data governance has become a more understood and sophisticated discipline in the industry, we do have several learnings from previous experience that we can share with you and other folks in order to help you not learn things the hard way, like we have done over many, many years. So the process that we'll go through in this section is that we will first start with some very fundamental concepts around data governance. We'll talk about why it's important to definition of governance and then move into some data governance frameworks to help establish the context of data governance. We'll look at the reasons that organizations establish data governance. So what are the business drivers? And then as I mentioned, we'll go through what are some common risks and pitfalls. And then of course, what are some critical success factors for data governance? We'll wrap up this module by talking about how to get started. So back to the basics, getting started with your data governance program. Okay, fundamentals of data governance. Why is data governance important? Well, as I was establishing this presentation and writing down the speaker notes, my five-year-old daughter was sitting next to me and reading through my slides. And funnily enough, she says, data. Data, data, data, data. Mommy, data, data. And I said, you know what, honey? You are absolutely right. It is data, data, data. And I think that that is really very telling. So out of the mouths of babes, right? So really, the world is becoming much more data-intensive. And our world has changed and is continuing to change. So companies are trying to understand their customer and their interactions with their customer at any time, across any channel. Data quality issues that are created across these multiple channels tend to perpetuate even further within an organization. So a misspelling of a customer name, excuse me, a customer name becomes persistent across all systems, potentially in a data governance, without a data governance guidelines and policies. Technology is changing. So many organizations still have legacy mainframe systems that they're trying to integrate with new technologies and even new approaches to managing systems and technologies like the cloud. So as companies move towards a cloud environment, this reduces the level of control around your data and also around the people and processes that are responsible for managing the data. Of course, big data is the latest trend in our industry and this is all a reaction to the fact that data volumes, velocity and variety are increasing. And that data is being created and consumed by mobile applications and in a mobile environment. Project management offices are becoming standard ways to implement new systems, products and processes. And on top of all of this, there's external pressures in the form of new regulations such as Basel III and Dodd-Frank in the financial services industry, the Physicians Payments and Sunshine Act, and the Unique Device Identification in the health and life sciences industry. So these regulations are compounding the internal pressures that organizations are facing in regards to their data. And in the same way that companies are wanting to understand their customer at any time across any channel, customers are demanding to have their information available at any time across any channel. And these technology and market changes are happening faster than most organizations can change their infrastructure to respond. So data governance comes into play because it ensures that the right people are brought together to make the decisions and to determine the standards, the usage and the integration of data across projects, specific areas and lines of business. So this means it's getting the right people to the table at the right time to make the decisions around the data. At the same time, data governance has a role to play in smoothing out traditional project-based implementation processes that in fact create additional silos within the organization. So fundamentally, data governance is important because it is that practice that ensures that we manage data as the strategic value-producing asset that it is meant to be. So how do we define data governance? Well, we think about data governance as an organizing framework. It is definitely not a one-size-fits-all. And that framework guides the process to establish the strategy goals and guidelines that ensure that data is accurate, available, timely, auditable, secure, and consistent across your organization. And so because data governance links traditionally technical capabilities like data modeling with traditional business capabilities like strategy and communication, data governance really is the glue that brings together business resources and IT resources around the conversation of managing data as an asset. And because it pulls together multiple people from multiple organizations who create and use data in different ways, this is both one reason why it's complicated but also one reason why it's incredibly important to have some level of organized standard, strategy, and approach. So now we're going to go into a bit more depth regarding data governance, leveraging some of the First San Francisco frameworks that we use within our practice. So this is our data governance framework. And this framework is a comprehensive series of components needed to implement an effective data governance program. So you can think about this as a bucket list of all of the things that you should be considering when establishing a data governance program for your organization or for your enterprise. So let's just go through this briefly. So essentially, this framework, you always want to start with a strategy. So to a certain extent it's left to right, but not 100%. We recommend starting with a strategy. And that strategy is the articulation of your vision and mission, goals and objectives as it aligns to your corporate objectives. This is where you create the why and where you align it to the business objectives and goals of your organization. And you create an agreed upon set of guiding principles that will help to establish your data governance program and discipline and create meaning within the practice. Now, after you develop your strategy, then from there it's not necessarily left to right. Meaning that, as soon as you create a strategy, you also need to think about how do you communicate that strategy out to the rest of the organization and what potential change may come up as a result of the articulation of that strategy and the communication process of that strategy to the organization. So in this way, it is really and truly a series of components that you want to consider when determining how to implement data governance within your organization, not just a left to right process. Okay, so having said that, after you create the strategy and establish your goals, you need to identify who is going to be accountable for the execution of the data governance program and establishing data governance as a discipline within your organization. So that's why we have organizations as the next module. As the next module, both within this framework and as the next module within the education series. That organization structure then creates the accountability to execute on policies, processes, and standards as well as to measure and monitor the progress of the program to implement technology to support the strategy that has been identified. So many people think about data governance just as the bubble called policy, processes, and standards. So I think it's very important to understand that yes, policies, processes, and standards are governance, but if you just focus on the creation of policies, processes, and standards, it's very difficult to make your data governance discipline sticky within your organization. It's difficult to move that organization through the change necessary that is needed to have data governance be a productive practice within your organization. So that's why we've created this framework to take into consideration all of the different ways to make data governance sustainable. To ensure that you have proactively addressed the people side of the organization through a proactive change management, training, and communication plan, and that you consider how you're going to measure the success of your program, not just from a progress perspective, but measuring the impact of the data governance program on the organization. And technology we see as a great enabler to data governance. Technology isn't data governance in and of itself, but it is a great enabler to make a data governance program effective. So this is the way that we think about data governance and a framework in which to consider how data governance should be implemented within your organization. This framework will create the context for the rest of the education series around how to build out a governance program within your organization. So governance actually is associated with another practice called enterprise data management. Enterprise data management is really those activities that are executed within an organization guided by data governance to manage the data within your enterprise. So the blue bricks that you see within this enterprise data management framework, we think about as core capabilities needed to implement governance within those contexts. So to implement the guidelines and the policies and the standards that are created by the data governance program as it pertains to the different categories of data. So data governance essentially provides a wrapper around other activities and capabilities needed to manage data across the enterprise.  Reference data management as well. Metadata management which includes the process of data definitions and business glossaries. So many times these are considered to be technologies, but I'd like to challenge that perspective and to have you think about the blue bricks, not as technologies, but as capabilities to manage data within your enterprise guided by the business context that's provided by data governance. And this is the link between data management and data governance which will be explored in more detail in the last module of this series. Now if we take this to the next level, really the big picture is enterprise information management. And an enterprise information management program ensures that the data as well as aggregated and derived data, also known as information, is managed consistently across the enterprise and is managed in a way to ensure that it is a corporate asset. So an EIM program or an enterprise information management program ensures that the way that information in the form of data, reporting and analytics, documentation, and other sorts of content is created and shared across an organization and externally to business partners and affiliates. So the EIM program ensures that information is consistent, effective, and efficiently managed. So that information is a value-producing asset within your organization. And of course a good EIM program leverages architecture and technology as you see as essentially the foundation of this framework to enable more effective and efficient processes within the enterprise information management program. Having said that, what is the role of technology? Well, I've seen many organizations actually start an information management program by buying different technologies to manage their information. So whether they buy a master data management hub, a data governance tool, reporting software, or whether they start to implement a big data analytics environment, that's where a lot of companies start because as we've done in Silicon Valley, we have created this technology and software industry that solves lots and lots of problems. Well, what's missing is actually other more important tools that you see identified on the right-hand side of this screen. And these are tools like business processes and capabilities and stakeholder support that ensure that the software implementation is successful and that that software is truly used and consumed in a correct way in the environment. So essentially this is a very synergistic process because of course that software also makes information management and data governance more efficient by automating some of the quality processes, by automating some of the measurement and monitoring processes, and by automating the way that you can measure the quality of your data and the way the data is used across your organization, then you can use those measurements to better communicate the value of governance to your organization, which then helps to maintain the momentum behind your data governance program. So technology and data governance are very synergistic and it's optimal to leverage both to make sure that you have the organizational buy-in and understanding of why data governance is important to the organization as well as the question for me, to the individuals, as well as the technology to support that concept. So because the goal of this education series is to establish successful data governance programs, we're going to talk about success factors a couple of times. So this is our first slide where we talk about success factors within a data governance program. And over the years, we have learned that the most important success factor in any data governance program is actually understanding why you're doing data governance in the first place. So as I mentioned on the previous slide, some of these other must-have tools like the business sponsors, the executive sponsors and support, the solid alignment between business and IT, all of these can be articulated through a clear understanding of the business drivers, business goals, and the business case for data governance. And if the organization understands why data governance is important to the organizational success, then it makes it easier to motivate people to adopt the policies, standards, and processes that are outlined in the data governance program. And that's why having a clearly understood and defined business case for data governance is critical. It establishes the fly for the company, which is the starting point and leads to establishing the what's in it for me for the rest of the organization. And that what's in it for me will help with the inevitable change that occurs when you're implementing a data governance program. Hence, another critical success factor is proactively addressing that change and creating a change management plan to address potential change issues and resistance that may come up within the organization as a result of the data governance program and the request to manage data differently than people have in the past. And of course, that change management capability will help to ensure that the people that are identified as participants in the organization understand their ownership and accountability and can be effective participants within the organization. And that organization crosses all levels from senior executives down to the people that create data and use data in their daily jobs. Now, to discuss this last bullet point, although data governance is considered to be a program and the establishment of data governance is creating a new discipline within an organization, it's ultimately implemented as a series of projects. So we have found that one of the critical success factors for sustainable governance is to be able to effectively implement projects through trained, educated, and knowledgeable resources within the organization. So effectively managing those series of projects helps make the overall program much more effective. So if data governance is so important, why is it so hard? Well, unfortunately, there's lots of internal obstacles to data governance that exacerbate some of the external market and industry pressures that are put on any company and any organization. First and foremost, data governance is hamstrung by the view of it being overhead or bureaucracy. And the resistance that comes with the perception that data governance is going to slow down the way that business is executed within the enterprise. That feeling of bureaucracy is exacerbated by a competing pressures based on time and resources when folks have a lot that they need to be doing within the organization and they feel that their priorities are constantly shifting away from data governance. Sometimes this is also exacerbated by data ownership or the lack of data ownership. So this is the concept of the data is mine and you can't use it or a flip side being the lack of ownership where nobody takes accountability for the data. So there's a negative impact by having people be too accountable and trying to prevent other people from using their data. But at the same time, if nobody is accountable for the data, then nobody is accountable for the quality of the data. A lot of times data governance is the first program that is attempted to be implemented that requires cross business unit coordination. So those organizations that don't have experience pulling together multiple business units to work in a cohesive and collaborative environment have a big challenge with implementing this. So I'm not going to go through all of these obstacles in detail, but what you can see happening here is that there are many, many personnel and people-driven issues that come up from a governance perspective. So we'll address those people issues as we continue in this module, but also as we talk about the organizational constructs in the subsequent modules. But fundamentally, this is about balancing the requirement for control around the data to make sure that it is accurate, secure, and supported with the desire to increase efficiency and reduce the effort that's associated with managing the data. And ultimately, successful data governance is balancing the requirement for control with the desire to reduce the effort. And thereby serving the goals of the business, which is to increase the productivity and reduce the effort around the data with the desire to have control around the data. Okay, so now let's turn to specific business drivers. So we did talk about some of these in the previous slides where we were talking about why is data governance important. But let's talk about some of these other categories of business drivers, lead organizations to establish a data governance program. So legal compliance and regulatory drivers have helped this industry significantly by highlighting the role of data in understanding risk and mitigating risk within an enterprise. So within those highly regulated industries like financial services and health and life sciences, we have the government to thank for pushing forward data governance as a body of knowledge and as a practice and discipline within the industry. Most of those regulations are focused on an organization's understanding of how the data is created and used within their enterprise and the ability to demonstrate and prove accountability for that data and an understanding of transparency of the data as it moves across the organization. So because of those regulatory drivers, many organizations have started on data governance programs. Now what we have found is that if that's the only reason that organizations create a data governance program, it in fact becomes a bit limiting because they will do the minimum to adhere to those regulatory drivers without looking at truly how do we manage data as a corporate asset. So those organizations that leverage the external driver of regulatory compliance with internal drivers such as executing across their corporate strategy, those organizations are most successful. So looking at how does data contribute to the ability of that organization to execute against their mission, vision, objectives, and goals is really a critical success factor for governance. So understanding that the requirement or understanding that data is a key requirement to execute on those corporate strategies is very important. Now there's other sorts of IT drivers such as just a fundamental need to increase data quality, the experience of having multiple delayed or failed implementations because there's not been the proper recognition of the data that's included in those systems implementations. Those can also drive organizations to implement data governance as well. Those sorts of industry or those sorts of information technology drivers lead many organizations to start their governance program within the IT organization themselves. And then of course, there's external industry drivers that are also pushing forward the need for data governance such as the desire for consistent and standardized information that can be shared across a supply chain is pushing consistent data governance practices in different industries. The desire to optimize customer information and customer interaction, as we mentioned before, is both an internal and external industry driver as well. So lots of reasons to, from a business perspective, to be pushing forward data governance. But ultimately, the goal is to align the business or align the benefits of data governance with the business goals and objectives of the organization. So what you will do as you go through the implementation of your data governance program is you will take a look at the typical benefits of data governance and determine why is this important to my organization and how would I measure the impact of those benefits to the organization. And this is how you would determine truly how data governance is assisting the organization to move forward and better execute their corporate objectives. So if we think just fundamentally around one of these benefits, for example, data transparency and quality, the idea is that we want to determine how does data transparency and quality improve our business. So if we better understand how data is created across multiple channels within our organization, we can better understand how those customers interact with us across multiple channels and we can react from a business perspective to optimize those customer interactions across those multiple channels. So the idea here is that you want to tie that benefit of data governance and in this case data transparency back to ultimately the business goal of, in this case, improving customer experience and optimizing your customer interactions. And in this way, by aligning to the true business drivers that we discussed in the previous slide, then you can start to understand the true impact the governance will have on your organization. Okay. So now I'm going to go through a few risks, pitfalls, and success factors. So this is where we're going to go through some lessons learned and hope to provide some guidance so that you're not necessarily learning everything the hard way as we have done over the years that we've been in business. So by learning from experience and from where other people have been challenged, you can avoid those challenges as well. So if we think about the risk of not governing data, we can think about it in the way that a company itself understands and estimates their risk. So the idea is to go through the typical risk categories that are identified and measured in any organization and understand the data component of these different risk categories and how the lack of controlled governed and high quality data would increase that risk in that category. So what I'm going to do is I'm just going to touch on each of these categories of risk and talk about how better quality data either reduces the risk in that category or helps you to better understand and measure your risk within that category. Okay. And not all categories are equally impacted by the quality of data. Some are impacted more than others and it also depends on your industry. But in general, it's important to understand the risk of not governing your data in the same terminology and same language that the company discusses risk in general. So strategic risk is understanding what is the risk of our company's ability to execute on our strategy. So how will competitors react to new product launches? How will this acquisition enable us to grow and secure market share, et cetera. And clearly there's a role for data analysis in decision making and how to address competition, how to understand merger and acquisition in any sort of corporate event that would be critical to the expansion of a market. Now another way to think about this is that there is a huge component of a merger and acquisition or bringing in another organization. It is data oriented. So therefore data has a big role in making sure that any merger or acquisition is in fact effective and actually meets the goals that you identified when you're thinking about acquiring that business in the first place. So from a strategic risk perspective there's two ways that data has an impact. One is in understanding what that risk is and also in ensuring that when there is an event that occurs from a strategic perspective that that event is managed in such a way that it does deliver the value that's expected. So financial risk is whether the company has enough cash to meet its obligations to employees, shareholders, partners, et cetera. Within the financial services industry financial risk is also understanding market risk and understanding how the markets impact the ability to execute as a financial services organization. But a great example here is that when the recession started in 2008 when a lot of the meltdown started to occur there was a big scramble for CFOs to understand their cash flow collections risk and overall financial risk as it pertains to some of the big suppliers and some of the big manufacturers that were starting to become insolvent and go bankrupt. So I spoke to multiple CFOs that were rapidly scrambling trying to determine how much is due to them from companies like General Motors and what would happen if General Motors didn't pay their bills or fulfill their commitments. And so understanding every place that General Motors is either buying from you or you're selling to General Motors is a way that data can inherently help you to understand your financial risk, your cash flow risk and your collections risk. In the financial services industry the same thing was occurring where financial institutions were scrambling to understand their exposure to Lehman Brothers. Well, Lehman Brothers isn't always represented as Lehman Brothers in all categories of transactions based on the number of affiliates, partners, joint ventures and other organizations that might be partially owned or wholly owned by Lehman Brothers. It's not necessarily represented just as Lehman Brothers as that counterparty. So it's very difficult to pull together all of the data to truly calculate the exposure to that entity as it went out of business. So this is how data can help to understand financial risk and also to react to it. Now we talked about how governance can help to execute against regulatory requirements but I'd like to also talk about another category in which improved data and well-governed data can assist to reduce regulatory risk and that is the cost it takes for an organization to adhere to different regulatory requirements and the cost it takes every single time a new regulation comes out. Well, the better infrastructure that you have around your data, the better you can respond to those new regulations as they come out and your cost to adhere to those regulations can be reduced significantly. From an operational perspective there's many ways that data contributes to increasing operational risk or reducing operational risk. So some of these things are understanding how information is created and shared and therefore is there a risk of losing information, whether that's through information that is held on an individual's laptop, information that is held in a non-secure building. But one thing that we've seen come up that isn't an obvious one to most organizations is that data actually can have an impact on employee turnover and we saw within one of our clients that they were hiring very talented and expensive MBA students into their organization but because their data was not well-governed and was not of high quality these expensive MBA students were actually spending more time doing data remediation than they were doing data analysis and as a result the turnover in certain data oriented jobs within this company was quite high and improving the data actually led to a reduction in employee turnover because those newly minted MBAs were actually able to do the analysis that they were hired to do versus just the remediation to clean up the data. So anyway, a few thoughts around the risk of not governing your data. So let's go through a few pitfalls and these come up quite a bit because folks have, as we have progressed and matured data governance as an industry we've identified some things to avoid. So the first is governing data within IT. So it's not a pitfall in and of itself because of course data needs to be governed within IT but data cannot only be governed within IT. Data needs to be governed across the entire life cycle of that data and usually data is not created in IT. It may be managed in IT but it's not created, it's not acquired by IT and it's not necessarily analyzed by IT except for maybe an equality perspective. So it's important that data is governed across the organization, not just within IT. And that kind of leads to the next one which is a pitfall of governing data in silos. This happens many times in very large organizations where the coordination is very challenging across multiple lines of business and so we will address some of that in the next module which talks about the operating model but the idea is that you want to be able to govern data consistently across your organization even if the implementation of that governance is unique to the operations of that business unit or that region. And the idea here is that you're thinking globally about your data because it's a global asset of your enterprise and you're acting locally as it pertains to your job, your business unit or your region. I'm going to jump to one of my favorite pitfalls and this is using meaningless metrics. So one of the biggest challenges around governance is metrics and measurement. And so organizations will scramble to identify something to measure so that they can be at least measuring something. So what can happen is you end up measuring things that aren't really meaningful to the business impact that you're looking for within data governance. So you're spending some time measuring your progress but you're not necessarily measuring your impact and that progress might be important to you as a data governance owner but it doesn't necessarily measure the impact to the organization. So when you're creating metrics it's important to measure impact as well as progress. The next one I'm just going to touch on is ensuring that the company culture is taken into consideration when you're implementing data governance. We found that it's very difficult to push the boulder uphill or to try and change culture via data governance. So take into consideration the norms of the organization, whether it is you consider it a positive norm or a negative norm but take that culture into consideration when you're creating your program. And then lastly, a few ideas around ensuring success. So over the years, we have found that the following factors are usually evident in a successful program. And again, I'm not going to go through all of these bullets but I'd like to highlight a few that are really critical. So the first one, creating a strategy and then following it. So this is one that I think is incredibly important, is that there is a documentation of what you are trying to accomplish with governance. And that documentation, even if it is written on the back of a napkin or whether it's a hundred-page tome of information, it really doesn't matter how big that strategy is. But it's a documented articulated statement of how data governance will benefit the organization and how you can use that strategy to rally the participation of different parts of the organization. And that's a really critical starting point because that strategy will help with all of the subsequent bullet points that you see. It will help align business and IT. It will help to define what that measurable success criteria is so that you are measuring impact, not just progress. It will help to articulate how you itemize those iterative or that iterative deployment process. It will help recruit your executive sponsors and it will help to articulate why data is important to different stakeholders across the organization. The other thing is it will give you that foundation for communication of data governance across the organization and why data governance is important to the organization. So that last bullet point of communication is absolutely critical. So to wrap this up, we're going to go back to the basics. So let's talk a little bit about design principles. And these design principles will help ensure that you don't fall into those pitfalls that we discussed and that you will also take into consideration those lessons learned or those success factors. So it's important to be clear on what you're trying to accomplish. So as we talked about the business drivers, the business goals, be clear on what you're trying to accomplish with governance and what that impact would be. And going back to thinking globally and asking locally, there should be an enterprise viewpoint around governance when you're designing your program. Even if you're implementing governance on a project or on a strategic project just to start with, understanding what the ultimate enterprise impact will be is really important. It's important also to be flexible. Businesses change. Requirements change. People change. So it's important to have a model that is changeable and flexible as the organization changes because change is inevitable. What is it? Desk tasks isn't changed. They're all inevitable. And then just to highlight, again, you see the exact same thing on the bottom, communicate, communicate, communicate. It is really important that you set up within your data governance design the process of communication. Who communicates? Who is communicated to? How frequently does that communication happen? What's the contents of that communication? So ensure that communication is incorporated into your design, not just into a series of activities and that it is staffed for, it is resourced for because it is very important to the organization. So how do we get started? So the first thing is to assess and to understand what you have. What is your current state? Where is data being governed? So even if you don't have a data governance program in those terms, every organization is governing data in some way. So it's important to understand what that is because you don't want to reinvent the wheel and you don't want to redo something that is already working. So that was one of the design principles that I didn't highlight, but the idea is that you want to leverage work that has already been done in the past. So assess your current state, inventory current data governance practices, inventory your data management technology. What do you have? Who is involved with it? Who are the stakeholders? How do you align the goals of data governance and create that business case? So all of that initial assessment in the current state is a very foundational activity to ensure that you're building upon that foundation. And this is a good idea to start creating some baseline metrics at this point as you're assessing your current state. Now the next step is, okay, if we have assessed our current state, we've created a business case, we've started to articulate what that future state will look like. And if we can articulate what that future state will look like, then we can create a map and a plan and a strategy to execute against that future state. So this is where it's important to create that roadmap that will guide you to that future state and that it will guide you to execute that strategy. That roadmap will help to articulate how you are addressing all of the different components of the data governance framework that we introduced in the very beginning of this module and presentation. And that roadmap will be your guide to implement data governance across your organization. So roadmaps can change, but at least you have a point of articulation of what is going to happen, who is going to do it, so that you can start to execute and implement governance according to your plan and not in an ad hoc, unorganized, uncoordinated way. So this is the end of module one and we appreciate you going through this module with us. We encourage you to take the assessment questions and then join us again for module two, where we will drill down into creating a data governance operating model, which is the core of establishing a data governance organization. Thank you very much and enjoy the rest of your day.


So there you are, deep in the enemy jungle, 4-0-3, and you know a monster can be lurking in any bush. But you're not scared, because you've got your cunning, and your marksmanship, and the love of your life watching your back. Yes, indeed, the two of you are unstoppable, and you know that the Ocean Dragon Treasure is yours to play. Now, quick. What game are you playing? If you said, well, I'm playing the perennially popular competitive computer video game League of Legends, you would be wrong.  You know that if you're in, you're in for the long haul, and who's got the emotional fortitude for that kind of thing right now? Anyway, no, you are playing Zaya and or Rakan in Dungeons and Dragons, because in fifth edition, there's rules for that. Zaya and Rakan are a pair of wandering idealists, lovers and fighters both, on a mission to save their people. As members of the dwindling Vistaya, it can be hard for either of them to find a friendly face when they need it most, and that's why they go with the more reliable method of always bringing a spare one with them. It's this team aspect that makes them so unique, so making characters that dovetail and synergize with each other is going to be just as important as getting each of them right on their own. In its own way, that goes for the role-playing aspect of these characters, too. Creating a PC that hooks into the game world with and through another PC means that no matter how absurd and unrelated of a situation you find yourself in, you'll always have a jumping-off point for how to act and react, and that can definitely help shortcut some of the awkward early-session process of creating a personality from scratch. Just make sure that you and your partner aren't crowding the rest of the party out of social interactions and character moments while you do it. Alright, back to rules. Let's start with Ziya. First, for stats, Ziya should focus on decks and wids. Next up, choosing her race. Both Ziya and Rekhan are Vestayan, which means that their ancestors, however many millennia ago, were super powerful humans who merged their very beings with the world of spirits. I don't know about you, but that pretty much screams fey to me. So we could definitely go with elf or any other fey race, but there is one thing that is more powerful than magic in the world, and that is feets. Variant human will give us the one we need here, and hey, after all, the Vestayan are descended from very, very, very aided humans, so the Lord checks out. We'll take an old vibrant magic initiate, and that will give us the first level druid spell, Entangle. Ziya fights using her wits and at a distance, usually with feathers, but we'll substitute it in arrows and then focus on tricks and wiles, like setting traps and using the environment to our advantage. As for class, since we want to use a bow, we should of course go with fighter, but we're actually going to have three levels of ranger first. This will give us not only the archery fighting style to keep our arrows nice and precise, but also spells. We can use snare, along with entangle from our feet before, to root and trap our foes just like Ziya's rooting feathers do digitally. Hunter's mark will increase our DPR, and for our last spell, how about jump maybe? Just a thought. Now, we'll want to take Hunter as our archetype so we can have the ability Horde Breaker, which allows us to shoot two different enemies a turn, so long as they're within five feet of each other. So we can attack at range and lay traps, but we're still missing some pretty crucial elements of Ziya's kit, and that's where fighter comes in. We can't specialize in archery twice, so we'll take armor for the extra AC, but what we really came here for is the archetype Arcane Archer. This archetype allows us to start collecting a number of Hawkeye-like trick arrows at level three. We get to pick two from a list, and we can use them twice per long or short rest. In one of her characteristic attacks, Ziya runs a feather through all enemies in a straight line, so we'll take Piercing Arrow. That allows us to hit all enemies in a 30-foot line, so that's pretty perfect. Let's also take Grasping Arrow to add another form of trap, all of which we can use to buy us some time when we need it. Now that we have the DPR machine going, how are we gonna protect it? Let's turn to our wise-cracking bodyguard and life companion, Rakan, who favors Khan, Wiz, and Charisma. In digital game, Rakan heals allies and charms enemies while fighting in close range. More importantly, however, his powers are stronger when he's standing close to Ziya. To emulate that, we'll need to take a dive into Unearthed Arcana for its new cleric archetype, the Unity Domain. The marquee feature we get for this archetype is called Emboldening Bond, which allows us to form a bond between any two willing creatures, including ourselves, that last for an absolutely insane full hour. 600 rounds of combat. When two creatures who are emboldeningly bound stand within 30 feet of each other, they each get to add an extra d4 to attack rolls and safes. It's like a super bless.   This is where we're really gonna shine.  But let's also take a look at our cleric spells and see what we can snag to make this character feel even more like the cheesy charmer Rakan. We're up to 3rd level spells and there's plenty of charmer and utility here. We've got hold person for the hard crowd control. We can take bless so that along with our bond, we're adding 2d4 to every attack roll. We can use healing word and mass healing word, both of which outclass the tiny heal from Rakan's Q ability online. And for anything that those don't fix, we can hope that the protection from shield of faith lasts long enough to find a solution. For a finishing touch, let's look at what we can do for Rakan's ultimate, which is apparently running around really fast and charming everyone. But there's no real good way to replicate that around level 6. That said, we can draw on our racial heritage to take the fey teleportation feat exclusive to elves. Did I mention that we're an elf? By the way, we're an elf. That will not only give us more charisma, which we definitely do need a little sum of for a dashing guy like this, but also the spell misty step to ensure that we can always leap back to Ziya when we need to stick together. That's pretty much all we need to emulate Rakan. The domain feats do everything we want to do, like letting us take hits for Ziya with our channel divinity to split damage among the party. And there we have it, a pair of absolutely legendary PCs from Runeterra. Until next time, it's dangerous to go alone, so take some rules. And this is the end part of the video, where I like to address some of the things people were saying on the last video, which y'all had a lot of really great discussion on. A lot of it was about whether or not Gestalt was or in fact was not broken. And I think there's a lot of good perspectives on there. It definitely is broken if you're not expecting it. And it is overpowered, but that's kind of the point I think. Like somebody said that they run Gestalt campaigns and they want to be not just like heroic, but super heroic. Like these are like the biggest heroes in the land. And that's a really great feeling for that. It's like also when you do like a higher than average point by similar kind of thing. It's when you want to feel really, really cool and good at what you're doing. Another use that people mentioned a couple of times is if you only have two players and you want to play a campaign, this works. You basically give each player two characters. That's a really fantastic use of Gestalting. Some of the combinations y'all listed barred with anything, fighter with anything. Connecticut has got thrown in a lot which is really exciting because Connecticut has just a ton of super cool ways to just like interact with the world. The only problem is Connecticut is horrifyingly complex even when you know it's the only class. So good luck with it. But it does make things a lot more fun to just kind of like walk around them. Investigator came in a couple of times. Always remember the Inquisitor. Inquisitor has a bunch of narrative agency tools. All really great stuff. I got comments on the origin of the word Gestalt which I was going to go over in the video but I thought nah that's not a rule. But yeah it's a German word. I think I know it from psychology. Like graphic design uses it a lot. Like when you have like a dashed circle. It's not really a circle right?  It's a Gestalt circle. And apparently it means a lot of other things in German. So and I also apparently say it wrong every time. Just like Arcana. But that's who I am and I'm going to stay that way. As always if you have rules you would like to hear more about or strange interactions in any system that we've ever touched leave it in the comments. We will get back to it and maybe make a video on it. Also if you like video games we stream on Twitch three times a week. That is Sunday, Tuesday and Thursday. Our Twitch streaming schedule is up and about. I think it's on our Twitter and you can definitely find it. If you look for it I'm sure it's on Twitter. We are streaming some cool stuff.  It's really fun so just drop in. Say hi. Tell them that I sent you to me. I'll like that.


Hey guys welcome back to my YouTube channel this is Daniel Rosal here bringing you today's video from my home office in Jerusalem. Very very pleased to wake up today to see I've crossed over the 800 subscriber mark here on YouTube 200 to go until 1000. Never expected to even get this far to be honest although I've been putting out these videos for a little while. Thank you for anyone who has subscribed to the channel to date and stuck with it I know the subject matter is super varied I mentioned before that I tend to that I intend in the future to break down into more niche channels or more thematic channels but right now I'm just having great fun learning a lot about video production meeting interesting new people interviewing interesting new people and bringing my camera out with me to interesting places. So speaking about interesting things and interesting people I got to mention on Twitter today from a very good friend of mine a guy called Peter Duffy from back in Ireland in the motherland and Duffy is a very very astute follower of technology he puts out a terrific monthly newsletter called How Curious and it's kind of an interesting synopsis usually of tech Duffy has seen a podcast he's been listening to he's an avid podcast listener and he's also a big non-fiction reader so he's very much a guy sort of aligned with my interest but he's a he knows that I'm really interested in artificial intelligence and this whole world of deep fakes because I may or may not once have published a book under a fake name and that was really my kind of eye-opening experience for me into the worlds of deep if you know fake faces fake videos and how quickly artificial intelligence is advancing I've also written a couple of articles I'll put a link maybe to one of the ones I've written on medium my predictions for that this market for AI generated fakes and deep fakes of all kind is going it's evolving very very quickly right now as you're going to see in a minute the tech is not wonderful because we have two things required for deep fakes ready one of them is credible synthesized voices or TTS text to speech that's been a tech sector that's been evolving in recent years it's getting very good but it's not quite there yet it always sounds a bit robotic and then the more recent development or the more recent tech we're seeing is websites like the one I'm going to show you that Duffy told me about it's called movio.la and again you can see the mouth the mouth movements look a little bit artificial but it's pretty good and it's kind of freaky so I thought in this video I would show you guys how this webs give you a little inside look now there's another website that I've been following this is movio.la and they've got a few templates but you can also create something completely from scratch another website that I've just been on my radar for a long a long time now is called this person does not exist there's actually a website called this x does not exist and the link to various projects is something using an algorithm I believe it's called GAN from NVIDIA and you can read about how the algorithm works here or you can just get fake faces now I'm going to hit the refresh image button and we're going to so what I think is really fascinating about this this whole world of deep fakes it's not any of these one tools by themselves it's the fact that when you put these ingredients together we're going to get a fake face that looks like a real person then we're going to take that fake person and make it into a deep fake video and we're going to create a video of a person that never existed right so it's when you start combining stuff that it gets pretty wild I'm going to just wait until I can get a little bit better they say the best type of face for this project for a movie or dot l a is a face that isn't smiling almost like a passport photo so I'm going to just keep hitting refresh until I get a pretty neutral adult face and then I'm going to make a video from it with a backdrop of let's say the western wall in Jerusalem because it's where I live you know what this guy is pretty decent I'm going to take him and then let's see what kind of a video we can make from this okay so I've gone ahead now and I'm downloaded my fake face from the internet I'm going to call this guy Dave now something that would be very cool if they added this feature was I'm just going to use this as is but if you have someone with a background you can just do this kind of manual cropping I'm doing now in GIMP and then put them on a transparent background and that will allow you to get an even more realistic deep fake video for now I'm just going to play with Dave's Dave's fake itself and see how this works okay so I've gone ahead now and done a pretty crude job at cutting out my fake Dave from the AI generated background so I'm going to go ahead and save this as a transparency you guys can see how well it handles transparency at least it's going to give the avatar a background to stand against instead of the background that comes with the generator and let's go ahead and plug that in so I'm loading up a Muvio here and you get options to create landscape or portrait based videos and I've gone for landscapes so you can also upload your own backdrops I'm going to go ahead now and put in a custom backdrop so I just took a random scenic backdrop I did google images and I went for one that was licensed appropriately under the creative commons so that's going to be my backdrop and you can also add different elements here and textual elements into the video for instance if I want to add overlays for whatsapp with certain frames of the video or background music I can also do that but let's just keep it simple for this example that's the background I'm going to be using now I'm going to go ahead and add in my fake avatar okay so I'm uploading Dave into my avatar library now as you can see Dave is just uploaded there as well as the ones that I can upload of myself or of my friends there are different avatars now they do give you a bit of guidance in terms of how you should do this and I'm going to call that up in a second but for now let's just take Dave now as you can see in terms of the transparency let me just just jump back to gim so you can see what I did you can see I did a bit of a scrappy job here this is actually kind of a bit of his hair against the background and other I guess clop crops of his hair but it still got this kind of white background showing there which to me kind of detracts from how credible it looks and it's obviously not a head head and shoulders one it one either but anyway that's kind of decent enough for the purpose of demonstration and what you can go ahead and do here is create a script and then you can pick between your fake AI generated voices right so I'm going to write a little script here I'm going to say hi this is Dave I'm not a real person I never oops I never was a real person instead I'm an I'm an artificial intelligence generated face that has been super imposed on a real background the purpose of this video is to see whether my face and background looks credible enough for your average viewer to believe that I am in fact real and something I like about the script writer on this is that you can choose to manually add in five second pauses and you can also change the speed there is a 60 second speed limit on how you know on how long it can run for and you can choose between your different voices so clearly this Dave is a man so I'm going to go for a fairly neutral voice it's not the most amazing AI voice I've ever heard but for the purpose of this test it should be decent and I really like this a deep fake creator I guess that's not really what it's called this AI video based creator because it's really an intuitive user interface as well as choosing your different elements you can choose to put on subtitles so I can choose to have my subtitles here I'm going to move my fake tongue head a little bit out of the way and now I'm going to just go ahead and click on submit and this is then going to go into the rendering queue now in order to get the watermark out you do need to pay for the service for this demo I'm just going to show you what it looks like with some watermark inside of it and as you can see it's now rendering so this is a kind of graphical rendering process that happens in the cloud presumably it's quite compute intensive as you can see we're only at five percent after you know 10 or 20 seconds so it's going to take a few minutes to develop your your deep fake avatar but we're going to see the output in a second one last thing I wanted to say really about what's scary about this technology to me so as my friend Peter Duffy remarked the credibility of the deep fakes that are being created now with this they're not amazing I don't think anyone's really going to be tricked but we can expect this whole market to advance very quickly now there's not really such a concern about you know deep fakes your friends being able to deep fake you maybe there is in the sense of pranks I think what's very scary about this technology is a potential for hackers or you know social engineers to create deep fakes of world leaders or presidents or celebrities and create fake accounts and put those two elements together so again I'm not I'm not encouraging by any means anyone to use this tech for malicious purposes the white hat approach would be well if you want a business and you and if you have a business and you want to make a simple what's called talking head video or you just have a person talking to camera kind of like what I'm doing instead of hiring a real actor and giving them a script you could use one of these avatars so Dave is rendering here and while that's going on I'm just going to actually create a second video and something I like about this is that you can render simultaneously so let's take a video of this guy he's pretty you know corporate looking so this might be I guess good for one of those corporate videos and I'm going to go ahead and drop in a background from Pexels of an office setting and we'll see if we can create a perhaps more credible looking fake talking head video than we did in our in our last one okay so just in order to try challenge movio la's technology was something that wasn't in their default stock library I went on to google images in the end and I searched for Tel Aviv so this is going to be a little background at Tel Aviv now again something I really like about this system is that it's really intuitive so if you've used any kind of image editor whether it's GIMP or photoshop or something like that you're probably very familiar with working with layers so what I'm going to do now is bring my fake speaking person or let's call him Dave too up to the front now as you can see I've chosen it's probably not the best background because he's in a black suit and it's all it's quite a dark background so the contrast isn't amazing I'm going to pop him down in the bottom right corner so he doesn't look totally out of place this almost looks like a kind of one of those virtual green screen screenshots except of course that our avatar isn't real so I'm going to give him another script to say I'm going to say hi this is Dave too and this is the second proof of concept for what are known as deep fake videos that Daniel has created for his YouTube channel and again the pauses the kind of limitations of the avatar speaking are going to be that you know sometimes if you use foreign words like Tel Aviv is a word in Hebrew right so let's see how well it handles Aviv I'm here today in Tel Aviv and it's not as hot as it was during the day thankfully you should totally subscribe to Daniel's YouTube channel which has just passed 800 subscribers he loves sharing cool new technology with his friends and those interested now something that's also pretty cool about the voice you can use to go along with your avatar is that as you can see here on the left panel there are options for different languages so I click into Hebrew for instance we have Avril now I know the audio is coming through my speakers not through the microphone so I hope that was audible but it's text to speech Hebrew and I have to say it's decent I wouldn't say it's either better or worse than the English versions right there's one option in Hebrew versus many in English it does sound a bit robotic but it doesn't definitely sounds quite understandable so I'm going to just go for a pretty neutral male voice we're going to go with Matthew which is one of the US voices I've written I have a hundred and fifty eight eighty four characters there's a lot of room to work with here and again you get a little timeline for those who are used to video editing I can add little features you can add elements and you can add text at certain points but just to keep it simple let's go for a talking talking head video Dave's going to give us a little speech in front of virtual Tel Aviv and I'm going to add that now into my rendering queue so the good news is that while my second video is rendering my first one's already ready so I can download here with a watermark for free something quite cool is it also gives you a URL to share so I can click on this share link share this on my Facebook or you can download the mp4 and of course the good thing about downloading the video is that you can then edit it in a video editing program what I did using Kaden live which is a video editor for Linux is I reduced the speed to 80% with pitch compensation and I think it came across a little better I would say that these tend to be a bit fast so my first avatar video is ready my second one is in queue I'm going to go ahead now and pause the video and then let you guys see how the output looked like I'd be very interested in hearing your thoughts on this avatar or deep fake technology coming from movio.la if you've seen better technology for this kind of thing that you like please let me know in the comments if you have thoughts about what the advent and rapid advancement and sophistication of this technology is going to mean for both white hat marketing uses and black hat uses for disinformation misinformation and all other kinds of mischief that can be achieved when you can take fake people or real people and make fake videos out of them and share them with the world as if it was something really done by that person if you have thoughts on what all this is going to mean for the future of the internet for the future of society and the sharing of information please let me know in the comments too because this is something I've really been thinking about and I must admit I'm a little worried about it because this technology is definitely rapidly coming to a point of good maturity and I expect in the next couple of years these synthesized voices will be a lot better these the fake speaking technology will be a lot better so what's kind of proof of concept and leading edge today is going to become relatively mature tech I imagine a lot sooner than any of us imagine thank you guys very much for watching this video I'll leave you with my videos of the deep fakes so stick around until the end if you want to get more videos from me please subscribe to this youtube channel thank you very much for watching hi this is Dave I'm not a real person I never was a real person instead I'm an artificial intelligence generated face that has been superimposed on a real background the purpose of this video is to see whether my face and background looks credible enough for your average viewer to believe that I am in fact hi this is Dave too and this is the second proof of concept for what are known as deep fake videos that Daniel has created for his youtube channel I'm here today in Tel Aviv and it's not as hot as it was during the day thankfully you should totally subscribe to Daniel's youtube channel which has just passed 800 subscribers he loves sharing cool new technology with his friends and those interested


Thank you very much. Good morning to you all. Mr. President, President Paul Kagame of Rwanda, Mr. Carlos Limelu, Chairman of Carlos Lim Foundation. His Excellency, Mr. Jose Antonio Maede-Guribena, Secretary of Foreign Affairs, Mexico, my dear colleague Irina Bokova, Director General for UNESCO, and Co-Vice Chairman. Distinguished commissioners, ladies and gentlemen, let me first offer you a very warm welcome to Mexico, and it is a real pleasure and a great honor to have so many commissioners and their representatives here with us today in this fine country. I would like to thank our Co-Chair Carlos Lim, in particular, for his kind invitation and for hosting this seventh meeting of the broadband commission. Particularly, I would like to express our gratitude for having shared with us the very fine initiative, Aldea Digital, that was organizing this week. I mean, the aspiration we got from that, Aldea Digital means the digital village. I felt in a digital city, and I believe that this will go to Mondo Digital very soon as the commission continue to do his work. And this is a great contribution to the world, and I would like to really thank Carlos Lim for putting this together. I would, before I go any further, I would like also to thank all the commissioners for the very, very strong commitment that we have shown over the past two and a half years, close to three years now. On July 12th, we'll have three years of work. And this is our seventh meeting, and you've been always all committed. Especially today, especially want to have a special tribute to our friend Dennis O'Brien. As an Irishman, being here on the St. Patrick Day is really a sign of commitment. So I would like to congratulate all the Irish participants here on a very good St. Patrick Day. As usual, we have a full agenda, and I'm very much to make sure that we have time for fruitful interactive discussions. So I will be brief as much as possible. Ladies and gentlemen, I'm very pleased with the progress that we have made since we last met in New York last September, and we will hear more about this today. Globally, Broadband continues to be at the top of the global political agenda, and nowhere was this more clear than at the World Conference on International Telecommunications the week of 2012, which took place in Dubai in December last year. There was universal consensus at the conference that Broadband was the future, and I am pleased to note that the new International Telecommunication Regulations, the ITRs, which came out of the wicket, contain important new provisions, notably in Article 6, which will encourage investment in international telecommunication networks, and which will promote competitive wholesale pricing for traffic carried. This is one of the most important articles in the revised ITRs, and I'm confident that it will play a very important role in furthering Broadband rollout around the world and bringing the internet within reach of the 4.5 billion people who are still offline. We are among the privileged ones, the 2.5 billion people who are connected today, so I'm sure nobody in this room forgets about the remaining two-thirds of the human population that are not connected. The revised ITRs also contain several new resolutions which do not require any ratification, acceptance or approval process, and are not inherently binding for member states. They are nonetheless important texts that will themselves help to promote improved access to ICTs to all the world's people. In terms of the commission, resolution number three is perhaps the most interesting of the five resolutions as it addresses the fostering of an enabling environment for the greater growth of the internet. The resolution specifically calls for greater broadband investment and expresses support for the multi-stakeholder model and makes special mention of the broadband commission. To me, that's really very important. Between now and our next meeting in September, ITU will be holding the Fifth World Telecommunication Information and Communication Technology Policy Forum, WTPF 13 in Geneva in May. WTPF 13 has been convened by ITU membership to provide a global forum to examine international internet-related public policy matters. And let me stress here that WTPF is a forum, not a treaty-making conference. It is a unique opportunity to air the issues as they are seen among fellow experts and the forum will enable all stakeholders to contribute their unique perspective to the discussions and help the global community chart a common course forward. The preparatory process for WTPF 13 has been open and inclusive. It was led by an international expert group that was open to all stakeholders, irrespective of whether or not they are members of ITU. The expert group recently concluded its third and final meeting and approved six draft opinions by Consensus for further discussion at the Policy Forum in May. These opinions cover wide range of internet-related global policy issues of significant relevance in today's world, and I'm confident that they will serve as a good basis for fruitful high-level discussions at WTPF 13. Just before WTPF 13, on May 13th, we will be hosting a high-level strategy dialogue to discuss the importance of investment in infrastructure and the changing nature of ICT regression. The focus will be on broadband, and I'm sure that many of the issues we discuss here in Mexico will form a key part of the input of that dialogue. And the reason why I'm mentioning those two important events is that I would like to invite you all to join us. Before I close, I would like to give thanks on behalf of the whole commission to the following organizations who have made contributions for 2013. They are OREDU, formerly QTEL, QTEL rebranded in Barcelona two weeks ago as OREDU. Microsoft, Azerbaijan, Huawei, and Cisco all contributed, and I would like to thank them again. Special thanks must go to Intel, of course, and it's regular for its regular annual contribution of the work of the commission. We are tremendously grateful for your support and your continuing faith in the importance of this commission and its ongoing work. Honestly, let me also congratulate Huawei and Microsoft, both present here in the commission for their partnership in developing a low-cost smartphone for Africa. That's a tremendous achievement. Africa remains a continent with the lowest broadband penetration in the world today and represents enormous opportunities for those willing to seize them. And let me applaud Huawei, Microsoft, and others for playing their part in giving Africa online, in getting Africa online. I can assure that the leadership in Africa is ready. As President Kagame told you, we have convened the first Connects the World series in Africa in October 2007 in Kigali in Rwanda at the invitation of President Kagame. And he's convening this Transform Africa Summit to just make sure that leaders come back again five years later to revisit what they're committed to and see how we can fine-tune our strategies and move forward. Of course, industry is invited. And we are very grateful to President Kagame for taking that leadership and showing the lead in not only transforming his own country, making it digital, but also making sure that the whole continent will benefit from that. And I am personally grateful we all should be to both him and chairman, co-chairman Carlos Slim, they have attended every single meeting, no matter where the meeting had taken place. And that's despite their very, very busy agenda we all imagined, but we are very grateful to show their commitment. And I can tell you, Mr. Chairman, Chairman Kagame and Slim, the people here in this room are committed. And we are relaying back the information to the rest of the world. And we know the world is listening to us and we can make a difference. So I would like to thank you again. So let me conclude by encouraging everyone to keep up the momentum and keep shaping the broadband future for all. Thank you very much. Pleasure, Mike.