 Hello and welcome. My name is Shannon Kemp and I'm the Chief Digital Manager for Data Diversity. We want to thank you for joining the latest in the monthly webinar series, Data Architecture Strategies with Donna Burbank. Today Donna will discuss emerging trends in data architecture. What's the next big thing? Sponsored today by Digital Realty. Just a couple of points to get us started. Due to a large number of people that attend these sessions, you will be muted during the webinar. For questions, we will be collecting them by the Q&A panel, or if you'd like to tweet, we encourage you to share questions via Twitter using hashtag DA strategies. And if you'd like to chat with us or with each other, we certainly encourage you to do so. And just to note, the chat defaults ascended just the panelists, but you may absolutely change that to network with everyone. To open the chat and the Q&A panels, you will find those icons in the bottom middle of your screen to enable those features. And as always, we will send a follow-up email within two business days containing links to the slides and recording of this session and additional information requested throughout the webinar. Now, let me turn it over to Dan for a brief word from our sponsor, Digital Realty. Dan, hello and welcome. Hi, thank you, Shannon. Hi, everybody. Let's go in for everybody. Looks good. All right, hopefully everybody sees that okay. Yeah, so thank you, everyone for having me briefly today. My name is Danny Lin. I am Senior Director of Platform at Digital Realty. And I'm very excited. I'm really looking forward to Donna's presentation as I'm sure you all are as well. And I saw a couple of things that I just want to kind of mention and talk about. Obviously, I'm from Digital Realty and those of you who do know who we are are possibly wondering to yourselves why the data center company is here to talk about data. And I sort of jokingly but at the same time rather seriously say that the clue is in the name, right, and data centers or as I prefer to refer to them, centers of data are at the center of the data revolution. And so, you know, I do want to talk about something that we're doing that I think really fits in well at Digital Realty. We sit at a unique vantage point. You know, we're home to a large number of cloud provider deployments, large enterprise deployments, and so forth. And that gives us a unique vantage point. And, you know, in terms of seeing what people are doing, obviously we know and as you'll see in the survey if you've already read it, right so many companies are on their way or at least wanting to get on their way. And to go through a digital transformation, their company right, almost 65% of folks in the survey said that that's their top priority, and we see the same thing. And, you know, as a result of that right, a lot of digital transformation really is powered by data and can be as easily encumbered by data. So one of the things we've been doing is, you know, we've been looking at the kind of infrastructure patterns that are occurring, you know, within our four walls. And we see this, you know, massive growth of data. And, you know, we're thinking what are people doing with this data, you know, where's it going, how can we start to predict or think about what's happening. And so, a gentleman by the name of Dave McCrory, about 10 years ago coined the phrase data gravity and talking about, you know, the mass of data and what that means. It's not enough to call Dave a colleague now he's working with us at Digital Realty studying this phenomenon, and we've actually published the results to additions already now of this study, we refer to as the data gravity index. And what we're really, you know, looking at and wanting to kind of, you know, contribute to the industry is, you know, we see this challenge. We see data gravity as a challenge, and we see it as one of the biggest impediments to a successful digital transformation. So, you know, we're really wanting to get the word out and have people understand that hey this could be a challenge right. What does it mean. The other thing we want to do is is inform some of the decisions we make right because we're able to look at this data gravity phenomenon and actually start to make some predictions. So where's it growing. You'll see right as of right now the prediction show, nearly 140% combined compound annual growth in this data gravity, which is insane if you think about it. How's that happening. Oh, it's us right it's this continuous continuous data creation life cycle. It's we create data, and then, you know, we do something with it, then we store it, and then, you know, doesn't go there to do nothing, you know, then then folks like myself start to look at it right we do analytics on it. We enrich that data that gets put back in, and this perpetuates the cycle of the growth of data. So, you know why, why us again talking about it as I said I think we have a unique vantage point. And in the middle, kind of between the, you know, the people, the locations, the things that are accessing, you know, these applications and generating this data, you know, both that sort of out at the edge and in the clouds. And, you know, since both of those environments can live with us, you know, we see this. And so, you know, when we talk about it right we sort of see the same thing. You know, you'll see again in the survey, the fact that when you look at, you know, challenges, and the challenges around data management. Who's handling that in organizations is the reality is I looked at that and I said wow there's a lot of varying titles. You know, in interacting and potentially either claiming to or someone else in the organization thinks they're responsible for this data management. So, you know, we're trying and we do and one of the challenges is, you know, we know that that not necessarily all these folks in the organization are talking to each other and it's, it's kind of one of the challenges, we see, you know, if the folks who are attempting to make this data useful and valuable, aren't having a meaningful dialogue with the folks who support the infrastructure that can bring that data to life and actually help derive insights. So, to break down the process. So, to try to work through that and help people we've come up with a concept that we call pervasive data center architecture, which is really, it's a set of kind of, you know, it's it's both prescriptive architectural patterns, but it's also methodology that we encourage people to consider using to solve those data gravity challenges right to have awareness of who are the people involved in the process where are the things where are your data, and being intentional rather than accidental about where replace them, right because I think anyone who's been in it. For any period of time knows that you know so much of what we have is is truly accidental, and it's not that we've been careless it's just, you know, these things have grown organically and we started out doing something really never imagining how far it would take off. In order to harness that make that data powerful make that data, you know whether it's monetized or help it generate insights or interact with it real time, you know all these things that we aspire to be able to do as part of the digital transformation strategy, we have to be more methodical and more intentional about data. So we need to think about where our data needs to live so that we can get the most use out of it. And that's why we have that you know this concept of the methodology and and I would encourage you all to take a look at both the data gravity index, which we make available it's you can go to data gravity index.com or you can find it from the digital realty website. Take a look at that and look at how that might affect you, the industry that you work in some of the places in the world you might be, you know doing business or aspiring to do business, and also take a look at pervasive data center architecture, where we actually talk about being thoughtful about data, rather than accidental, and making sure that we're putting our data the infrastructure that supports our data positioning it so it can serve us best generate those insights, potentially come up with new business models based on data. So, as I said feel free to go out and take a look at the data gravity index, you know, think about what it means to you, reach out to us, if you have questions or ideas, and of course, throughout the course of the rest of the session. Feel free to put any questions you might have in the in the chatter in the Q amp a and look forward to interacting with you and really looking forward to your session Donna. Dan, thank you so much, and for kicking us off but thanks to digital realty for sponsoring and helping to make these webinars happen. And if you have questions for Dan or about digital realty may submit your questions in the Q amp a panel, and then we'll be joining us for the Q amp a portion of the webinar at the end. Now let me introduce the speaker of the monthly series Donna Burbank Donna is a recognized industry expert in information management with over 20 years experience helping organizations enrich their business opportunities through data and information. She is currently the managing director of global data strategy limited where she assists organizations around the globe and driving value from their data. And with that, let me give the Florida Donna to get her presentation started. Hello, and welcome. Hello. Thank you so much. It's always a pleasure to join these webinars and always nice to see some familiar faces or names at least on the attendee list. If you have not attended these webinars in the past, this is a series this is a week we generally kick off the January with some sort of look forward looking trends. And this year is no different. You'll see a lineup throughout the year we hope you can join these going forward. And I'm sure Shannon will repeat at the end as well. These are all recorded. So miss these are ones from last year you can always go to the diversity website and kept those. So, what are we going to talk about today. So, Dan had mentioned a survey and some of you may have seen that if not it's available on the the diversity website. And we did a survey on these this idea of trends and data management we really kind of want to walk through that, both from a technological point of view which is a big part of architecture, but also, and Dan mentioned this as well as a kind of from that people process and governance point of view and the survey kind of covers all of that. So, you know, what is what is new and what isn't I think what isn't is that we're, we have data driven business and that's really driving a lot of what's happening today I think, you know, you'll see over 70% of the survey respondents said that I think that's great. I don't think that's surprising anymore. I think those of us who are in the business though should be heartened by that I remember I was tell the story, you know, I've been doing a lot of the you know, conferences for years and it used to always be the topic of oh we don't get attention from the business no one cares about us we're in the back server room. And I often say well be careful what you ask for right because now the spotlight is definitely upon data. So if you're looking to hide, you're probably in the wrong career, because that also comes with responsibility. I found interesting, but perhaps not surprising in some sense is you know, a big driver of data as a strategic asset is reporting in analytics. I think that's been true for probably since data has been, you know, around if you look at cave dwellings right they're counting things that they are counting the animals they, they killed an eight and things like that so however you define data that's sort of what we've been using data for a long time. But I don't think that there's new ways of reporting this new analytics. But what interesting that that was sort of flat year over year. That's a strong number. We see that kind of you know staying fairly similar across the surveys we've been doing these I think. And probably the past five years and it's kind of interesting to see the strict the trends. So while that's great, and not surprising that reporting analytics will probably continue to lead the way. It's not necessarily the growth pattern that we see with some other areas where we did see a big increase in this idea of digital transformation. And so 64% not quite as high as the pure analytics. But you'll see that there's a lot of growth over 10% growth year over year from the year before, maybe not surprising either. But definitely interesting to kind of drill down into if you're if you're interested in kind of the other things that kind of bubbled up to the top again the two big ones are insights for reporting and analytics, and then this idea of digital transformation that we'll talk a little bit about some of the other ones. Again, maybe we get a little jaded of. Yeah, of course we're saving costs and increasing efficiency and reducing risk. I mean those are always popular ones as well but that also, you know, speaks to the power of data to do those things. I was talking to a customer this morning I had this great quote, you know data governance is what makes us faster and stronger than that job. And I don't, that just was nodding heads in the room when she said that but you know that might not have been the case, you know, a while back and maybe even in your organization, that's not the case yet. Now that people see that connection with strong data management strong data governance and efficiency and things like that because often is sometimes gets the other wrap that it takes too long and that sort of thing. Some of the others again, not surprising that have been leaders for a long time, you know, complying with regulations, especially if you're financial or healthcare, not necessarily always what you want to drive with not the sexiest part of it, but definitely a strong driver up there with, you know, customer satisfaction growth, product quality. I liked this year that you know it this made the top 10. Just list the top 10 there were a lot more, but approving outcomes for health and education that that's more of you know maybe more your nonprofit not everything is revenue and growth right and we've got several clients where their main data drive there is outcomes outcomes for health outcomes for mental health and outcomes for education for children and I think that's that's really great. Hopefully that this interesting to but what sort of, I think is maybe interesting to drill down a little bit is this idea of digital transformation is that just a buzzword is that, you know, is that a trend is that old news. I often like to go to the Gartner glossary think they've got a good definition for a lot of the terms and buzzwords out there. There is a fair in some ways you know it's what does that mean it could be anything from it modernization, you know for some folks that's moving to the cloud. Some of this entirely new business models, where companies are either, you know, digital first, or, or something like an Uber right whether you really transform the taxi drop business to more of a digital model. This is on dot com there's a good digital transformation right we don't go to bookstores we, we go online. And I think with covert that's even, you know, last year's version of this, we talked a lot about that how covert was driving digital transformation were companies that weren't digital before certainly are now might push back a little bit on the Gartner ran list to do this one of widely used in public sector organizations for modest initiatives like putting services online. You know, that's kind of a big deal, I think if you've ever tried to do that, moving online for your services actually, I think is almost the definition of digital transformation. So, again, a lot of different definitions and like I think December we actually last month and if you want to catch it on the diversity we did a whole section a whole session on digital transformation. But what I found was kind of fun to go through was, what does that mean in a different organization we had a healthcare provider, one of our customers that for them digital transformation was online telehealth. You know, maybe that's not super innovative for, but to me it was to them it was to their patients it was. And so that means a lot of different things to different people what I kind of think about and I wax poetic whatever in my head. We can often dismiss these trends as buzzwords, but it also often becomes more just business as usual I always sort of laugh when people say, you know, the dot com and the dot com Boston and maybe some companies went under but the whole idea of dot com is the way we work. The biggest companies in the planet is a dot com. So, yes, these things are buzzwords because they start to buzz and eventually, maybe they, we get jaded and just become so used to them that we forget that they're transformational. And there's a lot of pieces that go to it, you know little color to digital realty what what Dan was saying is, you know, maybe that's the forgotten side of it that isn't the no offense. You can't stand the sexiest side, but you can't do all this digital transformation without without the backs of you know the stuff on the back end, without the infrastructure and that's the stuff I think we just take for granted, but as a big part of this digital transformation. So what I also find a sort of interesting is, you know, what, what were the priorities in 2021, as I mentioned, which I find interesting is we do the survey every year. Again, some things always rise to the top, you know, bi and data warehousing always do some things kind of come and go. So when when folks talking to the 2021 survey absolutely number one was data warehouse and business intelligence. I see those as related but different. Unfortunately, I see maybe too many companies doing the bi side but not the warehouse or the, you know, there's different flavors of warehouses but the hard work behind it. You can do bi on a spreadsheet. So that might be the best enterprise approach. But when you look towards the future priorities in 2022 and beyond, what's bubbling to the top is data governance and data strategy, and when I just use our practice as kind of a litmus test for that. Are we doing data warehousing and reporting of course, what's our one of some of our biggest drivers from our customers governance strategy, probably some of those other ones they're master data management is another big one. Because to do that third one on the list in 2022 and 23 self service reporting analytics. I think what a lot of people are realizing is you can't do that without correct data and I think I want to say ironically but maybe it's expected that you know the more people want to get into things like met their buzzwords but they're true things like AI machine learning advanced analytics, and the more citizen data, data scientists and citizen, you know, self service bi start looking at the data, they very quickly realize that the data might not be great or might not be trusted and so how do we really get that data governance in place to make the data trusted so might not when we come to a webinar to say what's the big hottest trend and data, data architecture is data governance, maybe that sounds like a let down and it's not as sexies would like when there's so many things like you know data mesh and, you know, fancy platforms we can be using but when it comes down to it you can't do anything else without that so I think people are going back to foundations data strategy I almost think I mean data governance is across everything data strategy. I think that ties into people seeing data as a strategic asset people wanting to be digital and having digital transformation you can't do that without data. But I'm heartened by that because we do a lot of that as the name of our company but it's getting you know, getting business aligned with data and making those two sing together, which I think is a great positive trend. And none of these others are surprised and probably aren't to you that things like quality architecture metadata. Again, maybe not the sexiest stuff that people see in the front end but you can't live without it so. Moving ahead on that I also found interesting the question is who's driving data management and be clear most of these are multiple choice answers so it's not the only people, for example when you see the CEO. I don't think the CEO is personally putting together the roadmap for business intelligence, but it does mean that they're champion of it so that's really I think the high number of C level roles on this chart is very heartening that the fact that data is a strategic asset is proof to that. I don't think we're too surprised by seeing a CIO or a CDO that's kind of in their role, but a CEO is really great and those business stakeholders are great. What I find super interesting and we always say this to our customers as well. Data governance lead is so critical to the organization and I'm very not surprised and also very pleased that data governance lead is the top of that because when we have someone ask us, you know what is a good data governance lead look like. Yes, you have to understand technology you don't have to be a tech person I would actually not recommend that you come from tech that is generally a business person who can really be a champion in the organization and really get all of those roles together and really be that driver of change, because that is what governance is about it's as much of a change management effort as a technical effort it's both. I don't want to belittle either. But that data governance lead is that unique type of person that can speak both that they, they know what a warehouse is and why that's different than a data like, but they can also go talk to the chief marketing officer and explain why, you know, her campaigns got me better because of data. Right. What I find, you know, a corollary here is the chief data officer not every organization has a chief data officer I think that's a higher level of evolution, I wouldn't start if you're just starting your journey wouldn't start with the chief data officer. And you probably often start with the data governance lead and for those in the call who are a data governance leader aspiring I think there's often a career path from data governance lead to CDL. Because again, you kind of have to prove the value of data before this chief data officer role really even make sense or have enough of a foundation for that to exist. Again, a good data governance lead is that champion for change is able to get it and business in the same room and heard the cats and get all the different motivations and really get that that singing so I think this in my experience is very representative to what I see in organizations, and I think also very heartening that you'll see there's a mix of business and tech and kind of how they work together. So, although it isn't always harmony and love and kumbaya when it when it is kind of business and tech is both are hard. Tech is hard and people are even more hard. And this might be a hard and maybe the best visualization here but bear with me for a moment. So, what I found interesting and this may not be the most pure analytics I'm adding my own version of truth here but again bear with me. What I found interesting is when we look at self service bi. That's about 32% of organizations with 36. This is people planning to in the future to do it 36% already have it in place so just to get to get this is again future looking people in the future are looking to do self service bi. That's actually a decrease in the past few years since 2019. So when we look in the other side folks looking at data governance, a little higher percentage with even more having it in place and that's an increase in 2019 these are huge numbers it's a slight trend. But another point from the survey is a lot of organizations really have trouble collaborating between business IT, and when they say what's your impediment to success. What was the impediment so what what could help with that know one of it one of the things is data governance did a literacy we'll talk about in a bit is another big one, but my reading of this is I think a lot of people do want to do self service bi. And as I mentioned before as soon as you get into that. You see that the data needs help it's either not a data quality or we don't know who the owner is or we don't have the lineage. And we realize let's let's pause a sec on the self service and up the game on data governance. And a lot of the people doing that self service might be data owners in data governance right, but I think people are realizing that we want we are data driven we want to do these great things, but before we can do that. I think that's one of those foundations in place. I'm seeing a trend to me is not surprising but everyone, you know, sees the shadow it, or the part of you know marketing wants better campaign data and dashboards and it's just taking so long. In that old fashioned data warehouse gosh I don't know why they take months just to clean the data and get it out in a report I can do that. It was me trying to kind of do, you know, I always use the analogy I was trying to do some work on my house, and I was going to do it all, you know, homegrown and get the hammer and do it myself and it took me months and it was half as good and when I hired the person with the right tool and the right skills it took a couple days. And so I but I realized how hard it didn't look that hard how hard is it to put up a wall, you know, I've seen walls my whole life how hard can that be. And sometimes there's a, I've seen in our practice just recently as several folks that were the shadow it that are now coming and saying how do I build governance and data warehouse folks maybe we're kind of saying I told you so because some of this stuff just is hard. You know everything's hard and they're absolutely support self service bi there's a place for it. And the tools that are available today really put the power in the hands of the user, and to get that right, you need to have the right data so to me that's my reading of little bit of pause on the growth of self service bi to we get our data right, and we understand kind of who's doing what a sister to that as I mentioned, is this idea of data literacy. So self service bi can be super powerful it can also be dangerous do we understand the data we're joining do we understand how to join data that makes sense. You know there's some data foundations with that. Also, and I, I feel this more than anyone we're a data, my company is data and it's hard to find great data people who get the business as well. So there's a skill shortage in pure it roles, and I think data business, business people. I think I did a webinar before on that that blurring of the line between it and the business is blurring. I think business people either have been very data driven but the tools didn't support it, or are becoming data driven, you know go to a finance person or an actuary and accounting. I mean, they're all about insurance and, and try to say they're not data driven I mean they're all about data right they just a different flavor of data or a scientist who's doing you know, study analysis. It's just a different type of data so the more the tools I think in the technology blend than this alignment of whose business and who tied as it kind of morphs a little bit that said, in both it and in the business there is a skill shorted in the in the survey that we pointed to in the beginning. These were some statistics and a lot of kind of the right in comment, we said what is your biggest challenge the literal words data literacy came up a lot. What does data literacy mean, maybe that's another buzzword we kind of need to figure that out and I know a lot of the companies I'm working with. What does that mean does does a business person need to know third normal form or really or do they need to know just enough and advice for as a how much of that. So sorry to interrupt you but we're still seeing slide eight. Really. Yeah. Oh, right. Let me start sharing again. Thanks for putting it out. Okay, well. Thank you. We try this again. Yep, we're good. All right, let me go a little backwards because you missed all the cool stuff. Oops sorry now everything is now. Sorry. Sorry y'all I didn't catch that earlier. Eight. That was quite a while back. I don't know why we were just joking before that technology will always. They curse us. I do think it's Shannon's fault because she was saying that technology was actually working this year. Okay, so this was when I was so wow that was a long time back let me just do the quick so you can at least see the slides I was talking about that that data warehouse and is kind of the morphing towards data coverage data strategy. Now, I am changing my slide to say nine to people. Yes nine we're good. Okay, so this was the whole five minutes I spent talking about roles and you're probably wondering how that matched with the previous slide so thank you for jumping in. I'm going to pause for just a moment if you want to digest that but this is where I was talking about, you know that data governance lead is really the top but there's other C level roles as well. And then this is where I was looking at the, which probably made no sense as I was talking, kind of the numbers of and self service is a bit smaller and decreasing and data governance is increasing. And then I will move to slide 11 and you can now see the challenges faced. I am going to just to check so we don't have the same problem. We good channel channel or someone, or have I dropped all together and now my issues. Yeah, we're good. I don't be traumatized the rest of the week. So this is where I was talking about yes there's a skill shortage and yes there's a gap in how do we align it with the business and data literacy really has been kind of posed as a solution. Thank you whoever jumped in on the chat and I said that because I cannot see the chat moment. Okay, so this was a lot about the people in the process and the goals and the digital transformation and for some folks in the call who's expected an architecture conversation. I would say well this is part of architecture, and this is a big part of what makes architecture sing when we look at trends is getting that data governance right and really doing that alignment with the business. I always find one of my favorite. Again, we do this every year is kind of seeing the trends in the tech and the platforms and just confirming that we're on slide 12. I'm going to keep doing this for a little bit just to make sure. Good. I will stop doing that now and just be elephant happens again. Well, so we, we asked two questions. What are you using now. And what are you planning on using in the future. And I super found this interesting so, despite discussion of its imminent demise the good old on premise relational continues to lead the top by a lot. I mean not just sort of making out a win here it's just absolutely the overall winner. What continues to keep me up at night and upset me and make me cry is that spreadsheets is number two in terms of I mean, I guess I understand that we did ask, is it a platform or a data source, either one isn't isn't great. I mean, I don't want to say negative things about spreadsheets I use them all the time they have their purpose as an enterprise data management solution, I would not suggest that for anyone. So, but people are fairly honest on that at least and I, you know, when I lived in the vendor world and people would say kind of what's your number one competitor would say spreadsheets. And the other vendor tools it was the good old fashioned spreadsheet. I guess some of the others probably aren't a surprise you know package applications is that a big platform. Yes and no, I mean sometimes I, I feel I need to push back that an ERP system is not master data management, even though MDM might be embedded, your suppliers your customers, etc. You know JSON XML as a, you know, data exchange format with JSON being a little bit more common is not a surprise to me, you know the number of legacy systems, good old fashioned cobalt I think you can make a whole lot of money if you're the one of those few cobalt programmers out there. And we can love to hate the mainframe, but you can also say well, you know that was the old waterfall development and but it's still working. It's still there right so I'm a little bit interested in this small amount of the data, big data platforms. You know Hadoop isn't the only one we just had that as an example, but there's a lot of hyper on big data is a lot of great use cases for big data as well. So that one surprised me that it was quite as low, as well as some of the non relational both cloud and on prem seemed a bit lower given, you know, given given what I'm seeing honestly and given that those are some great use cases for it. So that would mean to be fair that is what people are using today that's not what people are testing or, or thinking about in the future so that that's the next question. Please screen, if you did not see the slide change. And again though, the good old fashioned relational database wins the top but the difference is that that cloud first paradigm is kind of coming through and and I see that as well. The ease of implementation the scalability, a lot of the good things about cloud are winning people over, but not everyone. It isn't a cloud only maybe cloud first, a lot of, a lot of good reasons, you know, cost skills, some people see as a risk in the cloud that people do want to stay on on premises so it isn't the only solution being in the cloud and many have kind of a hybrid cloud You'll see a bit higher for some of these non relational cloud based databases, which I think is great and I think it's a both and I do not expect the relational model to go away and it's super powerful for a lot of the operational data we use. But I think there's other tools in the toolkit and I'll talk about that later I'm also seeing a bit of morphing just like people morph and in this, this, you know distinction between all business and all it is kind of morphing. I think the idea of your, your only a relational database and your only a column or store database, but you only do big data, you know to drop a another buzzword, you know this idea of a data lake house where it isn't, you know, either or you and some of the technologies are getting much more advanced so I think there's a lot of tools in the toolkit and it obviously if you're only using a relational databases, you, I would suggest looking elsewhere for other use cases. You know, graph and for for doing trend analysis and maybe key value pairs for trying to get some some really fast analytics. But again, I think there's an overlying between a lot of the hardware. I find it interesting that spreadsheets went way down when you actually said what are you planning to use I was I was impressed with the honesty for a lot of people that they realize is not going away. I think the reality is higher but no one really wanted to admit that you don't see so much of the legacy in the, in the future. And some of the others seemed seemed to write this idea of streaming and real time I am seeing a lot more of, but that that that could be a webinar right what when does real time makes sense and there still is a case for batch. You know, if I'm doing my financial close I probably want to wait for things to close. But if I'm trying to get, you know, real time order status maybe I do want that little more real time. So hope you found that interesting I do, and we'll continue to do that each each year and kind of see how the trend continues. And who knows I mean I find it interesting these buzzwords that become business as usual. Is there anything here internet enabled or right because that's just obvious in my cloud become the norm where we don't have a category for cloud relational and on prem or will this still continue to be too valid options, depending on the use case where some lives on prem and some on cloud so I guess that's a stay tuned for next survey. So I'm just going to keep going on and tell me if it didn't each year I, you know, not to put too much weight on who I am but I put my own little predictions. And I call myself against them. Did I do okay or was I vastly wrong. And then we'll go into what my, my personal predictions might be for 2022 and beyond. So last year. I'm just looking back and it might seem like is 2021 and 2020 and 2022 any different work still in our living room in our pajamas with coven. But it did feel a lot different than I think the focus of last year and last year survey was a lot about coven reaction to that and needing to go digital and and really a lot of the survey responses didn't look it wasn't as much future looking a lot of it was just going to look at the different foundations. We need to do the basics, we need to get our data quality right and governance, but it wasn't too much forwards thinking on it seemed a more digital transformation as a reaction and not as a future plant. This year survey seemed a lot different that yes there's still a focus on foundations but not so much of that but so we got that one that one right. And that's true, as well as a lot of people and my customers use this time that maybe either things slow down or folks were forced to go more digital is to really build that data foundation and a lot several of our customers who had we're having trouble kind of getting this digital transformation, we're kind of augmented by able to, I don't say, use the pandemic that sounds horrible. That's a terrible thing but kind of use that situation. A lot of folks I was saying we're doing a lot of covert reporting. And we had one kind of nonprofit customer that does social services, and they said, you know, it was really hard to get some of our staff to understand why they needed dashboards but suddenly they were looking at a covert dashboard every single day, and whether they were going to go in or not, and whether the, you know, the patients could come in or not, and it really hit home what data driven meant. So again, it was a terrible situation but people were able to kind of get some good from it. The one where maybe half right or partially right. I put a little bigger push on this idea of business insights with not only bi, but advanced analytics of predictive analytics data science. Not as much as we expected so maybe even an X. I'm seeing a lot of folks wanting to get there, but are kind of stymied by by data quality issues or data governance issues or, you know, not getting data in a way that can be consumed for data science. So I would say every single one of our customers has some sort of data analytic advanced predictive analytics data science on their roadmap, but very few really are doing that right. Not nobody has plenty of people at a higher level maturity are, but I think folks are being held back a little bit data governance being strong. Yep, that's going to continue to grow as well as things that are related master data metadata and investment data management well maybe you can, you can see with your own company but I'm seeing it grow I think a lot of the data management vendors and things are doing that as well that people are trying to get this right. We really need data. So, looking ahead, what's the next big thing for this year and beyond this year. This is just my personal opinion not anything from the survey or anything from data diversity sponsored so get that caveat out there. So I think self service reporting in bi, I think morphs a little bit into business driven data governance and what does that mean is that you know this this this distinction between business and it becomes less of a distinction, and it's more about how do we build into data sets, and that's both business people and it's tech people, and it's all of the groups bring their right skill sets together and getting that right. And then yes of course, you know, maybe bi becomes an afterthought just like your dot com is the way of going out of trend anymore is of course how could you not have a dot com if you're a company right. So I think self service, you know, and that idea of self service bi, it just becomes a both course how else would you do it I actually had a customer who's in a very lower age maturity and then nothing gets in the great news that they're just starting. But when they were talking about self service bi. I was talking all about building your own reports and your analytics and he literally meant, can I bring up my own dashboard without having to ask somebody to generate a report from me. And that was so surprising because to me that's, I forgot those days. We just expect to open up power bi or you know looker or something and to start slicing and dicing, but that wasn't the case, not that long ago. We didn't need that now we don't even expect to have to go to it to get a report. But so again, I think even building these trusted data sets will become more of a team sport. Maybe this is my snarkiness number two data literacy will rise to buzzword status I think it's already there. I'm almost getting tired of hearing it but what does that mean, right so do we need to understand data is data important. And I think I've seen some companies do this well of what is the, you know, the average user in the company knows how to know how to read a report and that might seem simple. The recent news knows how numbers can be twisted. So, you know, if I'm CEO making decisions on data do I know what that graph means and what it implies and how the analysis was done to how people build their own reports. Maybe that's a citizen data analyst, or someone that actually wants to build their own data hub or Martin and you know again, there's a lot of layers of data literacy and I think getting that right. That actually means, should we get more people interested in data and knowing more about the fundamentals. Yep. But what does that mean, I think we'll have to kind of spell out. I think digital transformation pretty soon won't be a term or shouldn't be that's just kind of business as usual and maybe that's what Carter was getting at when people are only putting their services online well, you know, I'm really say I don't even think about if I did get my driver's license to do it online you want to buy something online. So, that's not the only definition of the digital transformation I realized but I think that's just going to be the way of doing business. Cloudverse approach for databases I think will grow really curious if that how how much that becomes the only way, or just becomes one of the ways. And this last one number five, I do a lot of work with the vendors used to be one now just play with them. It's a lot easier that way you just get to see this cool stuff and I have to actually build it. But a lot of the database vendors and the platform vendors really are doing some cool stuff that again, it just gets cool and we forget about it, you know, again giving a call out to the platform people we just expect things to be performant and the volume of data that we I can even do on my laptop that you couldn't do before. And the database platforms themselves. And maybe that's another webinar and of itself isn't just a relational database right there they're getting some of the ideas of column there I can't say that we're just going to try column oriented databases in within the same or that again not fan of the term data lake house, but yeah that idea that you have some things in data lake storage and some things are more relational storage is kind of the same data ecosystem, you know some might be streaming and and some might be more batch and there's different options. I think both from the pure database vendor level, they're betting it in the technology and from implementation level. You know it isn't just either or that you go to the data lake or you go to the data warehouse and it is kind of a best agree which I think is great and I think pretty soon, that'll just be so obvious we don't even talk about it. Basically, you all folks used to just separate, you know, structured data from unstructured why did you do that. And of course we know why we used to do that or maybe still do that. But I think again the technologies improvement so much that it'll be more but kind of a best breed thing that we don't even think of anymore. So, I do want to open it up for questions because I'm sure there'll be some heated discussions there always is more interesting discussion. Another of the takeaways this idea of business insights and analytics and digital transformation continues to be drivers. More and more business roles are a part of that or it roles are a part of business or everyone to say it. They're morphing data literacy their skills will be important whatever you want to call it. And there's a lot of tools in the toolkit it isn't just relational databases but don't, don't knock them either they're still. The analogy I like to use is these things are old fashioned they're foundational like Tesla is a super, super advanced car but it still has wheels, you know, and we invented the wheel thousands of years ago. You don't knock, you don't knock it you just use it as a foundation to build upon it, just like the Tesla did. So, before I open up for questions just a reminder that this is a monthly series so if you like this and want more. We'll be doing another one of February on on data strategy and how you can kind of build a strategy for your organization blatant plug that we do this for a living so if you need help, we're happy to share. Oops, and then I will open it up to thoughts questions ideas and Q&A. So Shannon over to you. Thank you so much and sorry I didn't catch that earlier so on the slides but glad we got it working again. So, and just answered the most commonly asked questions just a reminder I will be sending a follow up email by end of day Monday with links to the slides and links to the recording for this webinar. So, diving in here and Dan we invite you to come back in during the conversation. I often see gaps between marketing and it where marketing is collecting data through Adobe Google etc but it it is focusing on data warehouses data lakes did. It's not collecting data from CRM other systems but the quote unquote marketing data is not necessarily connected to you see that as well. I see that as well I see it all the time and I see it I wouldn't even just say marketing. It's finance it's engineering. And there's a couple reasons for that and then that that's probably a good call out some good and bad reasons I think some of the good reasons a lot of I mean everybody is getting that things are data driven. The core tools are putting a lot of embedded analytics in their tools themselves I actually we had a healthy discussion with a client this morning in finance and she said I don't understand why you need a warehouse that the are finance reporting tools are so good it gives us everything we need. And she was right. And they also need a warehouse because not everything that just she needs right so her costs need to be fed into engineering so they can estimate better right and so I think that's a limitation, I guess a risk of there are really good analytic tools out in that marketing ecosystem. And maybe that's enough for the marketer can either they benefit from some of the insights that might be in a warehouse or another group, and vice versa. And so I think, I think that's a great case of a both and but the silos need to be broken down and you don't want to just keep everything. It's a good platformer or maybe that's a, you know that is a good virtualization option or something but there has to be some kind of integration generally to kind of get that full benefit but open to what Dan has to say if you did any thoughts on that as well. Yeah, I think it's a little bit of what I, you know, kind of alluded to right at the beginning is, is, you know, when we don't have this dialogue, right that I think needs to occur. I think the provider right it in this case and the consumer the marketing department and that example, but between the various consumers as well. You know, because we're, how many of us, you know, are taking data that, you know, I get a report, okay from someone in finance that the report is perfect for them it built for them. I want to derive my own insights from that and integrate that into some marketing data that I have. So, you know, how do we make sure that there's opportunities to build that, you know, and being sensitive to the fact that typically it right is kind of gets the sad part of the data, which is right, juggling, keeping the lights on, and, and, you know, trying to be a good partner to the business and driving change and digital transformation, probably while being asked to do it, keeping budgets flat. So, you know, the first step is to get the dialogue going and just generate the awareness. You know, and hopefully we'll get there like I said as a marketing person. I'm super sensitive to that I oftentimes say man I wish I could go outside of corporate boundaries and do something because I, I know I could get what I need faster, easier and possibly even cheaper. I love it so don't take us back to slide number eight. Oh, that's the one I was stuck on now I'm traumatized. Maybe I need to give all the slides up longer because we all had a lot of time to analyze that. There's a lot of things to do. Would you explain the discrepancy in percentages. The discrepancy percentages. I am any good that that the future priorities are lower. Overall, the one only goes up to 45%. Is that what they mean. That's very possibly yeah, or couldn't mean Oh, this was a more than we had choose more than one. That's probably the answer that you're right that 60% of 60% of 6% doesn't add up to 100. Yeah, I guess it's about the percentages at the bottom so yeah. I guess there's two several answers to that I think that the biggest one was that there was multiple choice. So it does they don't add up to 100 and I should I put that on some of the others probably should have put it on this one. I think that the overall responses were lower in 20 days the highest one is only 45%. I think the distribution was a little bit wider on some of these. Otherwise I can't speak to that I'm not sure why fewer people. I think it's both the same for governance it probably stayed the same but relatively it's bigger. Yeah. But I think that the main was that probably why the numbers don't matter. Absolutely yeah that'll teach me to leave a slide up people look at it too long and look at the details I'm going back to the question slide. Of course they had the chart range changes based on the highest percentage of the answer. So how long does it take for an organization to adapt and succeed in data governance, we are good to have a data governance. We are going to have a data governance group, a new one. Great question. Should I give the consulting answer it depends. But it's a journey and I want to put that out there. More and more, we're kind of mixing in the companies we work with kind of full on organizational change management effort with your data governance, you know, I always equip industry the tech tech is hard to change but it can be a lot faster to change than hearts and minds and people. And I think if you look at any of the organizations, national change management frameworks like pro size just one of many. They start any change effort with the people understand why they understand, you know, that they're a part of it and all of that motivation before you get to the how. I think what I've seen some data governance efforts do wrongly is focus right on the how you know here's how you fix your data quality but didn't kind of step back you know because we in a day that are so involved in that we jump right to that and kind of forget that people have a day job and what's in it for me and and how this might be a different way of working and it may seem like it's slowing things down even though in the long run with speed things up. So, so it'll be a journey, but I don't want to dishearten people what we also often do when we do data governance is pick some sort of quick win. There's generally some pain point that such a pain point that everyone can feel it that you can get some results in a short time period, three months, you know, six months. And I would say that whatever if you especially if you're starting a new governance or pick something that's easy to fix it could be I mean one of it was, it was run on profit and they cleaned up address data. And for them that was a really easy fix they use some external tools and cleaned it up, and they were very quickly able to seek as they were having a campaign come up. People who they had fixed the addresses for they got like another $100,000 that they wouldn't have gotten and that was just such an easy. And that was when we fixed data quality we did it together, we saw the result and can't always be quite that fast or that like obvious, but the idea was, they picked something that would make sense to people. For another one it was actually was a marketing where they had marketing and sales together. And I realized why the campaign data wasn't right, and they picked it for them it was email addresses again a really tiny small thing, and they fixed that and they were able to really see how the marketing campaigns improved. And data governance can seem really theoretical. So if you have a committee get them together doing a thing I often don't even tell them they're on the committee until after you've done the thing. And then you say wasn't that good. And they say yeah I want to keep doing that and so that's governance and the role you just played was a data steward or, and then they can kind of sure I'll continue doing that but going to a random person who's busy and says now you're now dubbed as a data steward and you know these things can just sometimes seem really weird. So the more you just get people doing stuff that shows value I would say, how long does it take to finally answer your question for a long time. Make it three months make it six months otherwise you're not going to get that long term growth because people will get bored or frustrated, but open to what Dan has to say on that one. I mean I think that's the really great advice. I think it's just, it's, it's understanding right and making reasonable goals and then arranging them into milestones is when we see people having success. Yeah, I think because it's all about momentum right. Yeah, exactly. So, do you see a general trend towards decentralized data management and how our organization is approaching this. Actually not I'm actually seeing the trend the other way. I think it seems like decentralize it will maybe depends what we mean by decentralization federated, you know getting more people involved in data man and maybe that's that that blurring of, of it and business. I think there, there has to be some centralized approach or plan, and then decentralize can work a little better if you know you don't mean what we don't want to have a silos. And I think sometimes when this decentralized, it can quickly become silo so whether it's a centralized governance group that that, you know, has has representation in the various groups, and I've seen some folks kind of go the other way. And this also depending right is that famous it depends certain things like your core master data, my product list, my customer list. Some of those things should be centralized. And then maybe things like analytics or some of the use cases or, you know, maybe it's the classic warehouse versus smart approach some of those can be more decentralized but I'm actually not seeing that so much, or I've seen folks kind of try that and then get a little frustrated because it wasn't done in a correctly orchestrated way so maybe my answer is central orchestration, and then data maybe decent a little less centralized but there has to be at least a planned approach to keeping, keeping the cats herded together a little bit. I love it. You want to add that. Well, no I mean I think it's it's it comes into the to the point of view right where you're sending I mean I think one of the things that's kind of interesting is the data itself continues to be. It still seems vexingly distributed. But yeah, I would agree that folks that are successfully leveraging their data are doing that because you know they've centralized the important pieces largely the management of it, the governance of it. You know, the data itself, some of the processes, actually dealing with the data don't necessarily have to be right but but there's got to be, you know, I don't know to use an analogy right only once at a hands on the steering wheel, or things get really or things get really wild. Yeah, and I think just admitting that and getting that in the right is one of the cruxes of governance. We're not going to mess with your business processes. We're not going to mess with maybe 70% of the stuff you use to do your day job. But part number, can we agree on that? Because that's going to make us all more efficient because we all share part number. I think getting that right balance can also kind of get people less nervous about governance. We're not here to change your world. We're here to help your world. And there's certain things that are shared and certain things that aren't, and just setting those boundaries early, I think is really helpful. I think one of the other things I'd just add, and this is a little bit of it because of human nature, right, is the dialogue needs to include, and people get frustrated with this, I think, but it needs to include the why. Why is someone asking me to have a certain thing a certain way? You're going to get more by and fast because people are like, oh, OK, I get it, right? Your process has this kind of dependency, and OK, I can work with that, right? And again, and it can go both ways. A lot of times, right, when you come in, you're just like, it's this, no, right? You get a lot of nodding, but then no activity. Yeah, and that ties in to the earlier point about that organizational change management, which that's a really good job of starting with the why. Why and what's in it for me and how I'm involved before you tell them the what, because otherwise, you're right, people, no one wants to be told what to do. They want to feel like they're a part of something. And that was my point of also starting early with governance, get everyone involved in it. So it's their thing, not something you're telling them to do, it's just, again, we're all human. We have our own motivations and just acknowledge that. It goes a long way. All right, well, I'm afraid that is bringing us to the top of the hour. I hear that us all the time we have for this session. Thank you, Donna, so much as always. And Dan, thank you so much for joining us. And thanks to Digital Realty for sponsoring and helping to make these webinars happen. Just a reminder, again, I will send a follow-up email by end of day Monday for this webinar with links to the slides and recording. And I'll get you a link to download the paper as well. I'll just get you a copy of the paper for y'all so you can take a look at it. Hope you all have a great day. Thanks to our attendees for being so engaged. Love it as always. Enjoy. Thanks again, Donna, and thanks again, Dan. Thank you, always a pleasure. Thanks, all. Bye.