>> Announcer: Live from Boston Massachusetts. It's the cube. Covering IBM Chief Data Officer Summit, brought to you by IBM. >> Welcome back to the cube's coverage of the IBM Chief Data Officer Strategy Summit. I'm your host Rebecca Knight, along with my co-host Dave Vallante. We're joined by Sanjay Saxena, He is the senior vice president, enterprise data governance at Northern trust Corporation. Thanks so much for joining us Sanjay. >> Thank you. Thank you for having me. >> So, before the cameras were rolling, we were talking about how data governance is really now seen as a business imperative. Can you talk about what's driving that? >> Initially, when we started our data governance program it was very much a regulatory program, focused on regulations, such as GDPR, anti-money laundering etc. But now, as we have evolved, most of the program in my company is focused on business and business initiatives and a lot of that is actually driven by our customers, who want to clean data. We are custodians of the data. We do asset servicing, asset management, and what the customers have, are expecting, as stable stakes, is really clean data. So, more and more, I'm seeing it as a customer driven initiative. >> Clean data. can you ... >> So, many many businesses rely on data, financial services. It's all about data and technology, but when we talk about clean data, you're talking about providing data at a certain threshold. At a certain level of expectation. You are used to data quality when it comes to cars and gadgets and things like that. But, think about data and having a certain threshold that you and your customer can agree on as the right quality of data is really important. >> Well, and that's a lot of the, sort of, governance role, some of the back-office role, but then it evolved. >> Right. >> And begin to add value, particularly in the days where IBM was talking about data warehouse was king. You know master data management and single version of the truth. Data quality became a way in which folks in your role could really add business value. >> That's right. >> How has that evolved in terms of the challenge of that with all the data explosion? You know, how to do been big data it just increased the volumes of data by massive massive amounts and then lines of business started to initiate projects. What did that do for data quality, the data quality challenge? >> So the data quality challenge has grown on two dimensions. One, is the volume of data. You simply have more data to manage, more data to govern and provide an attestation or a certification, you say "Hey, it's clean data. It's good data." The other dimension is really around discoverability of that data. We have so much of data lying in data lakes and we have so many so much of meta-data about the data, that even governing that is becoming a challenge. So, I think both those dimensions are important and are making the jobs of a CDO more complex. >> And do you feel maybe not specific to you but just as an industry that, Let's take financial services, is the industry keeping pace? Because for years very few organizations, if any have tamed the data. Just a matter of keeping up. >> Has that changed or is it sort of still that treadmill? >> It's still evolving. It's still evolving in my from my perspective. Industries, again are starting to manage their models that they have to deliver to the regulators as essential, right? Now, more and more, they're looking at customer data. their saying "Look, my email IDs have to be correct. My customer addresses have to be correct." It's really important to have an effective customer relationship. Right? So, more and more, we are seeing front-office driving data quality and data quality initiatives. But have we attained a state of perfection? No. We are getting there, in terms of more optimization, more emphasis, more money and financials being put on data quality. But still it is evolving as a >> You talk a little bit about the importance of the customer relationship and this conference is really all about sharing best practices. What you've learned along the way, even from the stakes. Can you share a little bit with our viewers about what you think are sort of the pillars of a strong customer relationship, particularly with a financial services company? >> Right. So, in the industry that we are in, we do a lot of wealth management. We have institutional customers, but let's save the example of wealth management. These are wealthy, wealthy individuals, who have assets all around the world. Right? It's a high touch customer relationship kind of a game. So, we need to not only understand them, we need to understand their other relationships, their accountants, who their doctors are etc. So, in that kind of a business, not only it is about high touch and really understanding what the customer needs are. Right? And going more towards analytics and understanding what customers want, but really having correct data about them. Right? Where they live, who are their kids etc. So, it's really data and CRM, they actually come together in that kind of environment and data plays a pivotal role, when it comes to really effective CRM. >> Sanjay, last time we talked a little bit about GDPR. Can you give us an update on where you're at? I mean, like it or not, it's coming. How does it affect your organization and where are you and being ready for the, I mean GDPR has taken effect. people don't realize that, but the penalties go into effect next May. So, where are you guys at? >> So, we are progressing well on our GDPR program and we are, as we talked before this interview, we are treating GDPR as a foundation to our data governance program and that's how I would like other companies to treat GDP our program as well. Because not only what we are doing in GDPR, which is mapping out sensitive data across hundreds of applications and creating that baseline for the whole company. So that anytime a regulator comes in and wants to know where a particular person's information is, we should be able to tell them with in no uncertain terms. So we are using that to build a foundation for our data governance program. We are progressing well, in terms of all aspects of the program. The other interesting aspect, which is really important to highlight, which I didn't last time is that, there's a huge amount of synergy between GDPR and information security. Which is a much older discipline and data protection, so all companies have to protect the data anyway, right? Think about it. So, now a regulation comes along and we are, in a systematic fashion, trying to figure out where all where all our sensitive data is and whether it is controlled protected etc. It is helping our data protection program as well. So all these things, they come together very nicely from a GDPR perspective. >> I wonder, you, you remember Federal Rules of Civil Procedure. That was a big deal back in 2006, and the courts, you know maybe weren't as advanced and understanding technology as technology wasn't as advanced. What happened back then and I wonder if we could compare it to what you think will happen or is happening with GDPRs. It was impossible to solve the problem. So, people just said "Alright, we're going to fix email archiving and plug a hole." and then it became a case where, if a company could show that it had processes these procedures in place, they were covered, and that gave them defense and litigation. Do you expect the same will happen here or is the bar much much higher with GDPR. >> I believe the bar is much much higher. Because when you look at the different provisions of the regulation, right, customers consent is a big big deal, right? No longer can you use customer data for purposes other than what the customer has given you the consent for. Nor can you collect additional data, right? Historically, companies have gone out and collected not just your basic information, but may have collected other things that are relevant to them but not relevant to you or the relationship that you have with them. So it is, the laws are becoming or the regulations are becoming more restrictive, and really it's not just a matter of checking a box. It is really actually being able to prove that you have your data under control. >> Yeah so, my follow-up there is, can you use technology to prove that? Because you can't manually figure through this stuff. Are things like machine learning and so-called AI coming in to play to help with that problem. Yes, absolutely. So one aspect that we didn't talk about is that GDPR covers not just structured data but it covers unstructured data, which is huge and it's growing by tons. So, there are two tools available in the marketplace including IBM's tools which help you map the data or what we call as the lineage for the data. There are other tools that help you develop a meta-data repository to say "Hey, if it is date of birth, where does it reside in the repository, in all the depositories, in fact?" So, there are tools around meta-data management. There are tools around lineage. There are tools around unstructured data discovery, which is an add-on to the conventional tools and software that we have. So all those are things that you have in your repository that you can use to effectively implement GDPR. >> So my next follow-up on that is, does that lead to a situation where somebody in the governance role can actually, you know going back to the data quality conversation, can actually demonstrate incremental value to the business as a result of becoming expert at using that tooling? >> Absolutely, so as I mentioned earlier on in the conversation, right? You need govern data not just for your customers, for your regulators, but for your analytics. >> Right. >> Right. Now, analytics is yet another dimension effect. So you take all this information that now you're collecting for your GDPR, right? And it's the same information that somebody would need to effectively do a marketing campaign, or effectively do insights on the customer, right? Assuming you have the consent of course, right? We talked about that, right? So, you can mine the same information. Now, you have that information tagged. It's all nicely calibrated in repositories etc. Now, you can use that for your analytics, You can use that for your top line growth or even see what your internal processes are, that can make you more effective from an operations perspective. And how you can get that. >> So you're talking about these new foundations of your data governance strategy and yet we're also talking about this at a time where there's a real shortage of people who are data experts and analytics experts. What are what is Northern Trust doing right now to make sure that you are you have enough talent to fill the pipeline? >> So, we are doing multiple things. Like most companies, we are trying a lot of different things. It's hard to recruit in these areas, especially in the data science area, where analytics. And people not only need to have a certain broad understanding of your business, but they also need to have a deep understanding of all of the statistical techniques etc., right? So, that combination is very hard to find. So, what we do is typically, we get interns, from the universities who have the technology knowledge and we couple them up with business experts. And we work in those collaborated kind of teams, right? Think about agile teams that are working with business experts and technology experts together. So that's one way to solve for that problem. >> Great, well Sanjay, thank you so much for joining us here on the cube. >> Thank you. Thank you. >> Good to see you again. >> We will have more from the IBM CDO Summit just after this.