there you go um hello everyone um Welcome to our webinar uh this is uh a third webinar in our series of uh educational events hosted by damai Ukraine ke and today we are happy to have Scott Taylor uh the famous data Whisperer with us um so uh I will let's go introduce himself um later so um uh I'm quite excited uh to have such a u strong and experienced speaker speaker today uh because in D Ukraine one of our core values is to promote data management uh and make people aware of importance of data management and uh enable people to also uh share this attitude and uh Advocate data management uh across Enterprise ac across all the industries and uh I hope today uh you you'll take something with you and you'll be able to learn some uh important powerful techniques um for that um so um my name is Alexander shukov I'm the president of D Ukraine ke and I'm happy to uh to greet everyone and I guess uh we'll slowly kick uh the ball roll and I will uh transfer the mic to Scot Taylor and let him do the show all right are we set my on yeah great hello hello hello everybody let me uh share my screen get all that set it's going and then I gotta there we go so you can see both me and the slides is that all working okay should I be bigger should I be small I can be small all right we good yeah all right good morning everybody or at least it's it's morning here good afternoon to all of you delighted to be here Scott Taylor the data Whisperer and uh I am uh thrilled to be presenting to my 38th dama chapter you can see the logos of all the other ones I've been going to I did a virtual world tour a couple years ago with the dama chapters and then visited plenty of them in person obviously uh phoning in here from Connecticut in the United States about uh 50 miles from New York where it's hot and humid but then the day is barely started yet but thrilled to be talking to all of you about uh this important topic with uh what we call telling your data story We Stand by Ukraine absolutely just to get a little bit serious there for a moment I wish all of you you peace and happiness and hopefully things will will work out uh but I can't even imagine what you're going through so we'll try and kind of focus on this topic here for for the moment uh and wanted to share with you what I call uh leveraging the three vs of data storytelling for data management data storytelling is really uh critical element of data management these days and I'll give you my perspective on it which is a as usual a little different than what most people think but hopefully it'll be help or the subtitle of this particular presentation is data is the new why the way we talk about data is holding the industry back and what you can do about it somebody's got to say it somebody has to say the way we talk about data sometimes is not as impactful or as clear or as effective as we would like it to be and all of us out there trying to struggle to get stakeholder engagement get funding get your your enter and your corporation and your company to support what you are doing in data can be an absolute Challenge and part of the reason I believe we're not getting the support we need is because of the way we talk about it and I've been using this little mon this little uh phrase here for a while and I updated it this year with of course the geni Edition because everything we do in data now has to have gen in it right all you have to do is slap gen on something and all of a sudden it's brand new I'm sure some of you are using generative AI to drive tangible business value some of you are probably rolling your eyes and because you've been using classic regular old artificial intelligence for who knows how long and now all of a sudden everybody's interested in it and maybe perhaps a few of you are telling the business you're using AI but it's really machine learning you know they'll never know but in any case the whole AI hype cycle as no matter what value it's bringing it is also adding a whole new layer of complexity in terms of being able to talk clearly about the power and value of data management and I'm here to help with that so my mission is to give you new ways to talk about what you already know I'm sure plenty of you are data leaders data experts data management have tremendous data management experience you know how to get the things done but sometimes we've got to talk about it in a different more business accessible way so the stakeholders will give you that support you're looking for a little bit of background about me my company is metam meta Consulting we're about what it's about Meta Meta no we're not changing our name to Facebook Facebook don't ask that question I get that question all the time and spoil Alert in case you're wondering uh Scott Taylor the data Whisperer I don't do a whole lot of whispering I'm out there to help tell sell and yell about the power and value of proper data management I talk about how people talk about data that's my my expertise I've been a Storyteller in the data space since storytelling was two words and I've helped organizations convey the value of what they're trying to offer to their Enterprise in terms of data management I provide what I call data evangelism is a service a way to get people fired up about the work that you do and I focus on the why rather than the how I'm sure you know how to get it done but I've never met a CEO or a business leader who cares how it's going to be done until they understand why it's important to the organization my experience comes actually from the supplier side so I've worked with some iconic worldclass data Brands like neelen dun in Brad street wpp canar I've traveled the world and talked to every type of Enterprise at every level of data maturity in every sector all across the Earth there I'll limit my scope a little bit in terms of experience but I began to see very common traits challenges patterns similarities between companies when it came to data management and while the challenges aren't always the same I'd suggest they are more the same than they are different at this foundational data management layer you might call it different things and I'll go through that but those basic challenges that that hamper any Enterprise's progress are really remarkably similar I'm a full-time content creator now for the last five years I've been spending my days in LinkedIn and YouTube provide uh creating all kinds of content I've got a puppet series called the data puppets you'll have to check that out if we have time I'll show you one of the videos at the end it stars the CDO the chief dog officer and uh he's accompanied by the ITB and they go off and try and fix their Enterprise data challenges and run into all kinds of problems that I'm sure would be very familiar to you as well only it's a bit of a light-hearted entertaining view of the data space just Google the term data puppets I'm all that comes up it's a wonderful 100% organic search SEO marketer dream when you Google data puppets only my videos come up there I guess Google has never seen the terms data and puppets together other than me I also hang with a group of influencers called the data ventur we go out we'll be in uh London in the fall we've been in New York uh in the spring we go to all kinds of events together and support each other on LinkedIn I have a bunch of videos on YouTube if you want to check them out I call it the torture data Department Taylor's version I'm sure some of you get that reference but there's a whole bunch of videos about the Basic Value and benefits that things like Master data reference data data management data stewardship bring to an organization so just look for the data Whisperer Channel on YouTube and I've fortunate to have been recognized by a whole number of third parties in terms of validating the work that I do I'm in the data IQ 100 analytica huge who top blogger in dataversity CDO leading consultant all kinds of wonderful accolades that I've gotten and this is what I do I do events I do videos I work with Enterprises and do internal webinars and town halls and sales meetings or I do uh I work with event producers and do Keynotes I love being on stage I I think I have a fear of not public speaking so I spend my time wherever I can to get these kinds of opportunities and I also work with tech brands that uh sponsor the work that I do I wrote a whole book about this topic you may want to take a look at it it's called telling your data story data story telling for data management tell right on the cover it is 99% Buzz wordfree I did not want to overpromise and it was recently translated into French where it's 99% s ma alamode which of course means no words with ice cream and we all try and be disruptive in the data space I come by that honestly as well I've been disruptive since the fourth grade this is my fourth grade picture school picture see if you can pick me out yes that's me I still love the polka dots and in my fourth grade report card my teacher wrote Scott is disruptive and distracting to others I took that as a compliment being distracting to others that's a way to attract attention and that's all I've done my entire career is attract attention so I took the positive version of that comment from the fourth grade and have built a whole career around it but when you talk to your business partners when you talk about data do your business partners ask in the words of the Great Canadian philosopher some of you are probably wondering Canadian philosopher who Could That Be Afra LaVine you got to remember her why' you have to go and make things so complicated that's what we do in the data space we make it awfully complicated we use terms and buzzword and Technology oriented vocabulary that our business people just simply do not understand and data can be very confusing I'm sure you're familiar with the lak house but a lot of business people think the lake house is where their data goes on vacation or the data Fabric and the data mesh what about the data spanks let's tighten that integration you may have heard of sequel sure all of you have have have used SQL or maybe you use no SQL anybody out there know what the n o in no SQL stands for anyone to take a guess not only no o stands for not only it's the world's shortest acronym not only I mean only in the data space there no equal yes they're looking for a standard for identification in the internet of things only the abbreviation for that is idiot that's not going to work or have you heard of integrated platform as a service with governance as a service it's called I pass gas that is an elevator pitch I am sure you do not want to experience believe me that that was recently released from stealth but deadly mode not a demo you want a lot of people think just data is an IT problem classic way to explain it the IT person might just throw up this this glorious data model and say to their CEO see this is how we're going to do it again why is it important I don't care how you're going to do it until you tell me why but I got a warning for you it can be scary you do not want to leave your data alone with it never know what's going to happen but the truth about data management my first personal philosophy here when you look at storytelling as well you want to be succinct you want to be direct I go through an exercise where I try and boil down whatever I'm saying to the fewest number of words and in my case you can take my entire data philosophy and boil it down to three words I couldn't get it any shorter truth before meaning you must determine the truth in your data before you derive meaning obviously I'm in the truth team hence the meaning of my truth hat but you've got to find that meaning first that foundational meaning before you go off and do all kinds of fancy stuff in analytics truth before meaning it is not chicken or egg here it is egg and omelet if you do not have the truth you will not create the meaning that your organization is anticipating from the data that they're collecting and managing on that data Journey if you will let's dive a little deeper into Truth Versus meaning when we say determining the truth those are those foundational activities data management data governance data stewardship data quality Master data reference data metadata RDM MDM Pim Rim Dam all those foundational activities that you know and I know are out there to Steward and curate and distribute and govern that foundational content that flows through every type of enterprise system and that needs to be focused on that needs to be funded that needs to be in place before you can go too far in deriving meaning through business intelligence analytics data science data literacy visualization AI ml all the cool hot super sexy fancy stuff that gets a disproportionate amount of the focus and funding considering how it depends on the truth part so I like to think about determining the truth as where data starts and deriving meaning is where data ends up if you don't start the right way you're not going to end up where you want to go no matter what you do and there's two types of data storytelling out there so some of you may be familiar with some of these books under the deriving meaning Banner there's nine of them from some good friends of mine around data storytelling I wish that had been called analytics storytelling because that's what it really is way to take a piece of analysis A kpi A Metric some inside and put it into a business context to drive value that is super important we're not saying that's not important but there's also a story to tell about the data about why managing data is of such critical nature for your organization so two types of data storytelling out there one about the data data management one with data business intelligence you need both it's not Sophie's Choice here you got to have both but I think a lot of you given your data management expertise will focus on that data management storytelling as well we go all the way back here I've been taking a look at kind of how far back back this data management story will probably go now today we're in geni and that burst on the scene about a year and a half ago again I'm sure plenty of you were working on regular AI for who knows how long but suddenly everybody's everybody knows about gen Ai and it didn't take too long for people to start to talk about well you know geni is only as good as the training data and we need AI governance huh sound familiar and before that during Co everybody burst into e commerce was a huge Initiative for so many manufacturers out there who were now blocked from their retail engagement with customers and so they had to suddenly throw themselves into the e-commerce space and well they started saying we need a foundation we can't do it unless we have proper product data all of a sudden our e-commerce engines don't work and there were a record number of MDM Master data management inquiries from Gartner and Forester and a lot of the big analysts out there because suddenly all these companies needed to know about building that Foundation the chapter before that was data science when that came on the scene and then all of a sudden people were talking about how much time they spent oh data scientists spent 80% of their time munging and wrangling data and the other 20% complaining about how they munge and rang Wrangle data but those of us in data management knew needed the data to be good going in there and Andrew in I'm not sure if you're familiar with him he's a great data science leader ler he came out with this breakthrough observation just being slightly cynical here where he announced you know if you want to improve your data science output be more data Centric and less model Centric spend less time fine-tuning your model and more time curating the data that goes into it duh of course we've always known that and Big Data came out big data needed little data and those three vs of Big Data volume velocity variety that last V will kill you believe me that last V was the hardest part the variety of data and before that Enterprise systems came out that's when I started to get into the space in Pre 2K in the 90s people were implementing Erp and CRM and they realized oh we have to harmonize all our Legacy data and we have all these domain Masters we're starting to create and if you go way back all the way to general ledger you still need a chart of accounts so this whole here is just to prove from gen ledger to gen AI it is the same story no matter what the coolest thing is out lately you still need data management because the truth about data management is the success of every digitally transformative customer facing initiative every as a service offering every fora into e-commerce every enterprise software implementation every geni initiative is inextricably linked and connected to the successful output of your data management efforts that is the most long- winded complicated way I could say G goo garbage in garbage out we all learn that on the first day of data it is as sure as gravity what goes up must come down what goes in must come out what you but I like to call this the golden rule of data do unto your data as you would have it do unto you what you put into data management is what you get out of business intelligence or analytics or whatever we're calling it these days you put bad data into an Erp you get a lousy Erp you put bad data into CRM you're going to miss your customer opportunities you put bad data into fintech you might get a visit from The Regulators bad data in bi is BS bad data in AI is as artificial stupidity because no matter how you slice it or how you Dice it the golden rule of data prevails do under your data as you would have it do under you or another way to say it my most quoted quote good decisions made on bad data are just bad decisions you don't know about yet now every company has a data story to tell every Enterprise every Organization no matter what you're doing you have a data story to tell about why managing data is of strategic importance and you know that I know that but do your business stakeholders know that does your sea level management know that do the people who have the money to help get the work done that you need to do realize that we got to start that data story a lot of people people like to start their data stories suddenly with every company's a data company that's why we should do it boss because every company's a data company no every company is a software company no every company is an as of 18 months ago oh every company is an AI company frankly I don't like this approach I don't think it's real that logic doesn't stand up for me because if e if the kind of company you are is based on the tools that you use then every company is a paperclip company and nobody's bragging about that are you may want to start your data management story with some analysis from some of the analysts out there here's one that's hilarious from Gartner they did this poll and looked at okay the percentage of companies measuring the value of Master data 90% said they don't measure it and 10% said other I hope yes yes is in other I love MDM that's where I came from that's my background in the master data space so I love MDM so much I had to pull off the road and take a selfie in front of Michaelson door manufacturing but explaining MDM explaining Master data as an example and again that's core to any data management activity I like to think about a simpler way so if I had a minute with your CEO we would talk about how we need a common language across our Organization for the most important things that we track our customers our prospects our products our services we want to create a standard establish a standard across our Enterprise standards work I know there's that old cliche the beauty of Standards there's so many to choose from but people understand standards you don't even need to be in the data business to understand what a standard is and at a certain level it's just about rows and columns if you think about a classic data visualization technique the table it's really easy to add columns it's really hard to align those rows columns are easy rows are hard you ever try and bang two spreadsheets together columns are the meaning rows are the truth and at a recent trip to the acrop I realized it is all about rows and columns data management I know it can be a pain it can be an absolute pain I have talked to so many data leaders out there and they don't use all those cute little business euphemisms like we have a challenge or we have a hurdle they talk about physical pain the pain of trying to deal and manage with all this data I'm going to show you what pain really looks like there's a warning here this is graph TRC content might be disturbing to any data stewards in the room but we're going to have to show it if your children are there don't don't don't don't let them look at it I call it naked data because there's no way to hide from it are you ready are you ready to see what it looks like there it is this is it classic stuff these are from embarrassingly large Global Enterprises who don't know what they're doing with Coca-Cola can't spell Nestle the same way twice trying to track 711 I don't if you notice it yet but look at that 7 equals 11 not in base 10 that last column came from a manufacturer who put people into stores to check on these 7-Eleven convenience stores and we took a look at that call file as they call it which is the the root file that the that the uh merchandisers use to track all these store locations and because they were all doing it themselves they had when we took a look at it over 200 1 70 different versions of the 7-Eleven Banner name that is a mess that is the garbage in that is a lot of creativity in the field none of it is selling product they're trying to come up with a new way to spell 7-Eleven every day this is this is what we deal with this is the truth that people have to see to realize we can't get there unless we fix it and just because you put it in in uh software doesn't mean it gets fixed by itself because you put this in Excel and you get July 11th or you put it in Excel and you get November 7th right it depends on what geography you're even in I've been using the slide for almost 30 years and the good news is it's still effective and the bad news is it's still effective this is still the same problem again from geni to general ledger we're still dealing with the same stuff this is a funny and just as another example of systems not always picking up the data correctly I don't know if you noticed this little shoe advertisement here on a e-commerce site take a look at these sizes I wear an October 5th crazy but structured data Works harder than unstructured data it's a it's a concept we have to convey to folks to realize if we can structure some of the core elements of what we track as a business so many other things are going to be easier there we go oops sorry I had the save SL in there so I talk about the four C's of data structure and I'll take you through them now code company category and Country and so you think about an important record an important entity in your business every record has a code has a unique identifier might have a ship to number might have an sap number might have some sort of unique customer number that you've got on that particular entity and it identifies it uniquely in that system and every other system that's connected to it and it essentially confirms that this entity exists that it's authenticated and when you want to know things like how many of something you have you count that unique code if it's some sort of relationship it has a company it has a hierarchy it has some sort of parent child structure it could be Shi to buil to plan to sell to all the different levels you might interact with with whatever type of entity we're discussing so you need to have that company hierarchy and that helps you with really basic use cases like we're sending a salesperson to the bottom left oval did they realize it's related to the bottom right oval those those two things are connected sales people marketing people legal Finance they all have to depend on those hierarchical structures then you need to know what kind of thing that entity is there's all kinds of different ways to describe that too and you use that for targeting for segmentation for market share what kind of thing is this and then finally because they all start with C unique country or some form of geography where is it and geography can have all kinds of structure in it as well there could be a zip code or a postal code or a city state ZIP Province sales Market medium Market measurement Market all the different types of geographies so these four C's code company category country they could be called different things depending on the use case in the application they could be an entity hierarchy taxonomy and geography it might be a location and a account a channel a market it could be a product a brand a segment and a region it could be an an owner and a sector and a location a thing a parent a type a place but it when you have these four C's you know where something is you know what it is you know who it is and you know that it's Unique when you have all that all sorts of data problems go away just thinking taking a Zen moment here here thinking about all those data problems going away it is that Foundation it's very simple to discuss in this way when you try and describe it to those stakeholders who are wondering why they even need to do data governance so let's put this in play here if you take a look at kind of an abstract example this yellow blob is a geography of some sort in that geography are different things they belong to they're different kinds of things they belong to different parents and those parents have things in different geographies as well and you need to know where they are so this strange abstract cartoon here I think explains a lot of basic reporting that enterprises have to do how many things do I have and what markets are they in I'm working with the green square where are there where are their green circles or we're dealing with red who do they compete with entity hierarchy taxonomy geography code company category country these four C's of data structure solve a lot of data alignment aggregation integration definition problems all across the company and between you and your partners as well the classic data challenge that a lot of companies go through they have different departments sales marketing Finance operation they've got different regions they might be Global they might be local they might be across different countries they have different go to markets how do you get the stuff you make to the clients and customers that consume it do you go directly through Ecommerce do you do you have a physical product that has to go into a truck and then go to a warehouse and then go to a store the more complicated your go to market the more chances there are for data being disperate between parties and then of course there's a lot more external data external suppliers like the ones I used to work for are providing more and more insight about different things but this creates a situation where multiple systems and workflows create disparate data with differing St with differing definitions that lack internal standards this is the challenge and it's very common no matter what time of company you're in you're probably deal dealing with something like this I could put this in front of a CDO at a top Fortune 1000 company this afternoon and say is this your problem they would go how did you guess how did you know because it is literally everywhere the solution is data management data management helps align that data helps structure that data helps govern that data helps brings that source of Truth to provide all that meaning across the organization so I always TRW draw data management on the bottom bottom I don't put it on the top or the center or the middle or the side because it is that foundation for all those silos it is the vertical for all it's the horizontal for all those verticals it's the row that goes across all those columns when we think about finding your data story finding that data story in your organization that data management Story the real place to start is the essence of of your business why does your business exist why does your company exist why does who you work for even have an offering that they provide to other customers that's what you want to focus on it's not the data reason it's the business reason that's going to drive more value out of the data work you do and every company that I've ever met that I've ever engaged with every company wants to provide value to their relationships through their brand BRS at scale another example of me boiling things down to the fewest possible words I looked for a statement that would Encompass and really be relatable to every type of Enterprise out there which is provide value to your relationships through your brands at scale and when we say provide value only three ways I've seen value derived out of data grow improve and protect how do you help grow the business like increase sales how do you help improve the business like operational efficiency how do you help protect the business like mitigate risk there are a lot of different use cases for data but I'll challenge anybody to find one that does not fit in these three buckets grow improve protect again a really simple way to describe a really complicated process and when we say scale you need Hardware that's all about technology you need Hardware you need software you need data if you have data you need data management when we talk about relationships we all have relationships every company has relationships if you don't have relationships you don't have a business but what you call them could be different so you want to focus on that vocabulary of your business are they a customer are they a partner are they a prospect are they a citizen are they a patient whatever you call them might be something different but they are all relationship and we all have Brands too of some sort not everybody's Coca-Cola and 7-Eleven and Nestle but we all have brands or products or services or offerings might be a location there might be peace parts and materials that go into those brand offerings but we've all got Brands and we've all have relationships and so when your leaders talk about improving their relationships and expanding the their brands that's when you can get into the room and say okay how's our data on that stuff does your relationship data look like my 7-Eleven slide then you're not going to get there you're not going to get there at scale so a framework I've put together are called is called the 3vs of data storytelling for data management obviously a knowing wink to the 3vs of big data but instead of volume velocity variety mine are vocabulary voice and vision the first one vocabulary the words you use are important you want to establish an accessible common business related vocabulary speak the language of your business if you want to talk to the business folks skip all that Legacy lexicon skip the technological double speak and even words like data quality don't really resonate with the business side again quality I know it's important but it's probably one of the most emotional and subjective ways to describe data everybody's got an opinion about data quality that's why you want to focus on words like structure and foundation and standards and the vocabulary tip if you have established a business glossery use it use those kinds of words you can map it to whatever technically you want internally between you and the rest of your data and Analytics an IT team but the business side shouldn't learn a new language just to talk to you about what they need hear their language hear the way they talk and map that to your data what what your data can do the second V is voice how do you talk about this stuff you want to harmonize to a common voice now Harmony doesn't mean everybody sings the same notes but it does mean they sound great together so putting together almost an internal marketing program about your data management Journey try and get people excited about it in some way understanding that link between what you do in data management between the the the outputs that you have in data management and the outcomes you're looking for from the business and here's a little voice tip too seek out other storytellers in your organization every everybody knows how to tell a story you all know how to tell story if you've got children you're telling them stories every night probably two or three of them you're talking to your family about stories you're sharing stories with your co-workers and the rest of your organization about whatever it happens to be it's the same technique there's nothing new about that when it comes to data storytelling for data management so look for those other data storytellers or look for those other storytellers in your organization in sales and in marketing and in Communications marketing people know how to tell a story sales people if they they can't tell a story they don't make quota so that's part of their training it's the soft skill part of being a data leader that we don't always focus on that's so important here and anybody who wants to be a leader in their organization must be able to communicate if somebody doesn't understand you consider it your fault not theirs so look for those other storytellers and they can help you get better at this and the last V is vision why it's important everything we do in data must enable the Strategic intentions of our Enterprise where is your company going and why is data going to help you get there that's gets their attention listen to what your leaders say enable those strategic intentions your leaders are going to talk about company initiatives that have to do with brands that have to do with relationships again you can map those to the to the data challenges you have but when they talk about that they're not going to talk about data quality I'll tell you that much there's not a CEO out there who's going to write in their company letter every year or their strategy statement we need better data quality it's just not going to happen but they are going to talk about relationships they are going to talk about Brands and so everything that's way up at the top has this Foundation connected to it at the bottom and listen to what your leaders say if you're having trouble understanding what your business vision is look at your annual report or a strategy statement or customer or company meetings in the US we have all these investor day presentations so we can hear what the leaders say and then map the data work to that now here's a quick example here it's actually a uh slide composite from an investor Day presentation that uh a fortune 1000 company gave there's not really a build so I'll kind of take you through it the first one Vision how do we find the vision of this company it's right there just you could see that that border around it their Vision was to Aspire to be the premier partner of choice for their customers suppliers and employees relationships right there their Vision the single sentence that described where their company wanted to go and the objective was about relationships the voice was in all sorts of stuff throughout their strategic framework customer engagement enter PR Effectiveness they were talking about brand management they wanted to differentiate the customer experience they wanted localized productivity and efficiency even though it was a global company that grew by merger and acquisition so you know and I know behind the scenes there there's all kinds of data mess going on and then the vocabulary came in these company fast facts doing business in 90 countries so a huge Global country that's trying to harmonize and structure all that data across their different entities 800 Supply hes 100,000 customers the top box actually came from an example when I was den and Brad street we worked with this company and we took a look at at their customer master and we found they had 185 duplicates of this particular company Panasonic mobile Communications how could they possibly be the premier partner of choice for Panasonic when they have 185 duplicates there's no strategic reason to have that much of a mess that was their 7-Eleven slide so very quickly and this was a real example where we worked with an IT team to try and prove help them prove why they need to do invest in the data management side this type of anecdotal example Open the Eyes of management to realize we're not going to achieve our vision completely until we get our data house in order until we strengthen that Foundation till we reduce that 185 duplicates down to something that's real and manageable so leveraging the three VES of data storytelling vocabulary the words you use voice the way you talk and vision why it's important Aaron sarin if you're familiar with him one of the great screenwriters Oscar winning screenwriter of the of A Few Good Men and social network he said the most powerful delivery system ever invented for an idea is a story and I have one last story here I'm hoping this works so Alex break in if the uh sound doesn't work here I'm going to play a little video if it doesn't we can send you the link to it but it's a uh cautionary tale about the lack of data governance it's a data bedtime story I read to my grandson there he is it's called The Little Red Data hint let's see if this works it's Cod uh I think there's no sound is what I think there's no sound there's no sound yeah I don't know if I clicked the right button there okay um well we'll uh well I I'll send some links out sorry about that technical piece here so sometimes it sometimes it doesn't um but it's a it's it's an adorable little story and my four-year-old grandson in there and he talks all about data silos so I'm sure I'm sure you'll enjoy it here uh whoop so anyway uh just kind of living happily ever after every Enterprise has a data story to tell it's about providing value to your relationships through your brands at scale two types of data stories out there one about data data management determining the truth and the other one with data business intelligence deriving meaning you want to balance the how and why I focused more today on the why the how is important once they say yes you've got to get it done but again Business Leaders non-technical people want to understand why it's important leverage those three vs of data storytelling establish an accessible vocabulary harmonize to a common voice and illuminate the business vision and an effective narrative captures the hearts and minds of your business they can energize your team stories can work faster than processes and truth truth before meaning remember that as well and if you know uh if you know this movie without data management you can't handle the truth and all respect to Ain sorin who actually wrote this line and Jack Nicholson with data management you can handle the truth the final page in my book not giving away the surprise ending Hardware comes and goes software comes and goes but data remains no matter what the next thing is coming on the hype cycle again from gen Ledger all the way to gen Ai and whatever's coming next if it takes technology it's going to need data and if you have data you're going to need data management well I want to thank everybody here hopefully that ran long enough sorry about the uh the videos I should have tested that first but uh telling your data story if you take a look at that QR code that'll bring you to a whole variety of My Links please if you can follow me on LinkedIn take a look at my video page on YouTube and you'll find the Little Red Data hen as well as some uh some of my puppet videos too much Tech talk and then a Premiere with uh a whole bunch of these crazy puppet characters and hopefully it brings a smile to your day and helps you sell in your data management story my back wow that that that that was a great great story uh from you so yeah I was quite excited I would literally hold my breath the whole presentation was like really well really well done um so thanks for your uh for your uh uh like inspiration basically I was so inspired uh that even though I knew all all that stuff because I kind of do this 9 to5 pretty much uh but still like some some of the concept especially this part about truth and the meaning this this is amazing so thanks a lot and I think now we have some uh Q&A time sure can you still see me I don't know if I can am I still on yeah yeah I can oh okay all right yeah I'm still working with teams here so okay sure happen answer some questions no I appreciate it Alex I'm glad if it's effective there yeah for me too it was just really trying to boil it down how do you explain it I hit this truth before meaning thing and it just seems to resonate with folks and you know sometimes people take the word truth out of context they try and you know this isn't about politics this isn't about you know personal this about business in business you can find the truth in your organization of Standard customer definitions markets hierarchies taxonomies all those basic piece parts that make up so much of what we do in data yeah and and this anecdote about this uh strategic partnership uh which has like hundreds duplicate records like uh just a couple days ago I had a client who was kind of trying to understand if New Leads uh they were generating uh were for the existing customers they didn't have this matching algorithm because they for example for NY Times or New York Times They had two different records they don't even know if if it's an existing client or it's a new client and the whole process can can go like other way like if if you're talking to your existing client but you say hey like uh this our first deal or not you don't even know uh and they have this whole problem of Master data management but but also they don't really understand the importance of introducing this whole concept of Master data management and they they're all about like geni can we use gen to solve this problem real maybe yeah exactly so but you know if the data is good again it's the same it's the same problem it's just so it just keeps reoccurring a new generation of it and that's so classic what you're talking about there the idea of okay New York Times NY Times nyt there's just a million ways to spell it and it starts there if you don't start with the right stuff that is truly that garbage in true true so maybe maybe I I'll start with some questions just to to get this thing rolling um sure so uh maybe what what would be your advice uh when talking to customers who are just buzz woring about geni uh for example like uh I have a bunch of requests from customers can we like Implement geni and I keep selling them okay if you want J think about data gance uh but what what they give me as a response like we need something quick like in month like like proof of concept for geni uh and I'm like okay like do do you know like where your data is like do you have the right quality for of your data and they're like we don't know but we need like a simple PC like 50k worth um so what what would be your advice like uh in in that situation I I I I think you have to just sort of strip it down and just find the analogy that works for them to understand you can't make that omelette if you don't have the eggs you can't make a good meal unless you have proper ingredients food I found is probably the best most universal type of analogy for data because everybody everybody understands food they all understand cooking they all understand what it means that a great cook and you know perfect equipment are not going to get you a great meal if you don't have proper ingredients and it starts to sound a little cliche maybe but it is the absolute truth it's the only way to do it and so that proof of concept obviously you've got to carve out some sub segment Sub sub segment sorry of their data and clean that and structure that in a way that they could see what it looks like but the the when you explain to them how the proof of concept worked perhaps it's super important to show those first phases of where you had to structure and standardize that data to make it work maybe even show them what happens when you don't have that proper data I mean everybody knows about these llms hallucinating because the data that went into them is incorrect but it's a challenge there's there's no single answer there's no easy answer and as you could see by even this presentation this is just the nature of the beast in the data space that people get distracted and diluted almost by the newest fanciest thing and forget the the basics it's like you know I would love to you know be fit and and uh healthy but if I don't eat right and I don't exercise it's not going to happen and nobody's nobody's come up with a shortcut for that either right I saw some comments there I don't know if there's comments or or or or questions in that but uh oh let me look in the chat it's a call to discussion I guess yeah eventually they will trust someone to guarantee that their gen does not require go I'd like to know who that is I'd like to know who who they end up trusting I mean that is that that you know it's it's a fallacy there I don't know how I don't know how that works it just just simply doesn't you know bad bad ingredients make a terrible meal no matter what uh and they'll get fooled by them but unfortunately that's not going to be a good situation all right any other any other thoughts there any other questions you know I'll find some links that I can put into uh in into the chat if people are interested in some of my videos sorry that didn't work because it's super fun my grandson's become a star in LinkedIn um let's see here so be before um like maybe someone asks another question um maybe you can tell us about your book what what it is about uh and what people can actually get out uh when when they read it uh sure so the book was you know I I I highlighted a number of the things in that that I did in the book in in this session here and it's just about how to pull that story together and it came from all my years of of working with data management professionals and just realizing okay there's there's value in trying to have people you know put some kind of structure put some kind of framework together to put that story in front of folks and and it came from my experience you know working at den and Brad stre working at neelen I ended up bridging that gap between the IT people and the business people in those days it was even you know again I go back to the 1990s starting in data and there was no Chief data officer it was all CIO and what would happen is I would go in and I would talk with the you know representing neelsen or representing Den Brad street talk with the it and the data team they go this sounds great now can you help us explain this to the CFO because you explain it really well and I realized that was my Niche that was my talent uh lot of times the account people would say well you know that client loved you they want you on the account and I go no they don't want me on the account I don't know how to do this stuff they said well you really seem to understand their their their problem I I understand it I can talk about it but I can't fix it we got to you know hand that over to the right folks I never look under the hood I don't touch anything but I can sit down with Business Leaders and explain it to them in a way that they go from you know I have no idea what you're talking about to how do we live without this so you know as part of a team we all you know want to play part of a team and I I think I play my position really well but I stick to my position which is this the storytelling part of it uh and so I go through kind of how I came about a lot of these observations there's a section in there which is just kind of the classic data story that everybody has to go through I kind of highlighted some of it about all those different silos and the data management on the bottom and then go Fairly deep into these this 3v structure vocabulary and voice and vision and then give a number of examples of how you can kind of take apart just like I did with that that uh one quick example there how you can kind kind of take apart somebody's business approach and where they don't even talk about the need for data management and show look here are the little data management hooks in there here's the master here's why they don't have Master data here's why they need data governance here's why they need data stewardship it's you know it's in there it's behind the scenes and help people recognize look you've got to have the confidence that it's there that's that's what it starts with that you can walk into from me as a supplier side could walk into any organization and know there's going to be some data challenges there that we can unearth they may not recognize them they not call them the same thing but once you start to see it you can kind of recognize it almost everywhere all right um so by the way uh I forgot to mention uh if you want to ask a question uh please uh either type it in chat or you can raise your hand and we'll enable microphone uh uh for you so that you can uh ask questions live so yeah I already see a hand from Pablo Pablo uh I'm unmuting you so uh please go ahead with a question uh hi everyone hi Scott so it was like my pleasure yeah to listen to it I'm just crying because like so many issues I face with so yeah what's uh my question is I put it also in the chat but uh what good solution you have for engaging sea levels into data management because we have some sort of it but it's like uh scattered along the uh a lot of Divisions and uh a g division has its own pace of uh products Etc so they have their own life cycle so they think that uh they uh like a lot of the businesses has a lot of products and they are very like different so you cannot build like like centralized stuff you have to take into account the diversity so what would be your suggestion thank you again I would look at what what those sea level folks are already saying what is the vision of the company how are they talking about where the company wants to go what are some of those objectives and start to peel those apart and find the data management story within those so that example I gave about the vision of the company was to be the premier partner of choice that was in their annual report that was the number one statement they made they're locking themselves into the fact that they better have really good data about those relationships and when they don't it's going to keep them from achieving the goals that they want so find the goals that your company is setting it takes a little work to dig behind them but I don't know you know I don't know an organization that isn't trying to scale trying to grow trying to be more efficient trying to be more effective trying to find new opportunities trying to reduce risk in and exposure all those things need what data management can provide the challenge you have is is is connecting those dots but they they will what I found is if you can start with here are here are the company objectives right here's what you stated you want to do and it's published they've said it might be on a video might be an annual report okay let me show you behind the scenes here's what we could do if we had the right data to help help you get there whatever those examples are and sometimes it is as simple as showing them whatever version of that 7-Eleven slide is for you I've been in meetings with where just the bubble just bursts and people start looking at whatever that version of the slide we showed them and uh just go okay we we got to fix this I literally had a what we used to do at uh at neelen we had a technique where we would have maybe six or seven examples of really bad data and we would put them in order where it would just get worse and worse so the story just gets more and more horrific and there was a CO of a company we were presenting to and we didn't get much further than like the fourth example he just puts his head in his hands he like all right stop I I can't take this you're right we've got to fix this uh you know as as a salesperson as a presenter what you want to know in that situation is you don't say oh I've got three more examples to show you you go okay great now we' we've got alignment here let's move to the next step but it does take some some homework to to make sure you can connect where your Company's trying to go and the actual data situation you have that's keeping them from getting there yeah thanks really great yeah I also got one question but before before I ask it uh just a small announcements uh so um like we have recently started B new members to our organization um and we plan to kind of have uh exclusive uh events uh like this one um been done regularly uh so I I will put a link uh in the chat so you can read about our membership plans uh and benef especially benefits you would get and one of the benefits actually is not only uh access to uh precious information knowledge and uh webinars like this this one but also like uh career opportunities um you you'll get a lot of lot sorts of professional development support uh access to knowledge internal knowledge base and uh you'll be like ahead of others in terms of being um inside this community of data professionals and we also will help you to prepare for cdmp exam if you're also interested in achieving this certification and actually my uh my question is also related to uh DM framework so Scott like in your experience like um we have this really famous demo wheel uh with all this buz Wars uh in it so like how successful you could say using uh this framework will actually help you promote uh and Implement data management uh for your clients including this data quality so what what can you tell uh about the framework you know I I think I don't have a deep opinion of it I've got some friends of mine if you follow Malcolm Hawker he's with a software company in now prophecy he and I used to work at dun and Brad street he's got some very strong opinions about the D DEA and the demok and the and the wheel because he's a lot more experienced in actually doing this data work but so I I don't really have a you know it's it's a classic it certainly covers everything it probably is a little too deep to take a business group through so I would not use it to you know as soon as you say well there's nine slices of the DEA wheel and let's go through them one by one and just people just start to roll their eyes and and and glaze over that they want to go through all this but sort of capturing the essence of it and and reinforcing the fact that whether it's dma whether it's uh um I think uh there's a couple other organizations out there who have similar types of approaches you know pick something and and at least it gives the confidence that okay there's a standardized framework that we're going to we're not trying to create this on our own which I think is the is the point that's important to make we're not starting with our own homegrown way to do data management these are well Run Road tested practices that work across Global Enterprises and I doubt anybody on the business side's going to have any push back on you know well we shouldn't use D we should use uh you know the uh I'm struggling with the other competing group you know tdwi or something like that um but I think your your instinct is right that it's it's too deep on its own to go through on the business side but having a framework is important just helps guide you through where you want to go exactly yeah and and that's why you start with why and and then you you continue with the how and and the is actually the how probably more very much yeah yeah very it's you know it's this much worth a how [Laughter] exactly yeah thanks Scott um super yeah any other questions guys any else well thank thank you everybody for your time appreciate your time uh and attention during this hopefully it gave you a few nuggets or a few you know new twists of phrase that can help you in your data Journey please share with me how you're doing and uh if there's any way I can help let me know follow me on LinkedIn that's the easiest way if you want to reach out to me in any way linkedin's the best place to go take a look at my uh videos on on YouTube when you have a moment that'll probably give you a smile and uh wish everyone the best of luck all right thanks thanks everyone foring yeah have a great day to ahead of you bye byebye Cheers Cheers everyone for