 from the campus of MIT in Cambridge, Massachusetts. It's theCUBE, covering the MIT Chief Data Officer and the Information Quality Symposium. Now, here are your hosts, Stu Miniman and Paul Gillan. Welcome back, this is theCUBE, SiliconANGLE's flagship video platform. We are here at the MIT Chief Data Officer and Information Quality Symposium. I'm Paul Gillan, my colleague, Stu Miniman is with me. And we have two guests here who come from sort of different ends of the spectrum. We're going to talk about different things, but all related to big data and it's application to business results. Joe Caserta is the president and CEO of Caserta Concepts, which is a big data warehousing specialty consulting firm. And Yulan Yo-Yo Yuan is a professor at the Department of Tourism Management at Jinwen University in Taipei, Taiwan. And she is leading the first big data conference in that university, perhaps the first big data conference on the island of Taiwan. Is that the case? It's the second one. The second one. So let's talk first about Joe, your topic for your presentation. You're the new CDO now what? Now, we just had a CDO on in the previous session from the Department of Transportation. We asked him to define his role. He has one definition of it. Are you defining any commonality or any similarity of definition to the CDO role? So I've been in the data space for 30 years now and I've seen the evolution of data over that time span. And the CDO is a fairly new role. But in the past couple of years, I've seen it have its own life evolution life cycle. It started off being purely data governance, but now we're seeing that it's also embracing trying to help monetize your data and also help do the analytics portion of your data. And then there is some aspect of a divide and conquer where you have a CDO organization that will have maybe a chief analytics officer, a chief data governance officer. And then that collection of people will be a new division within an organization from the executive leadership level down. Because data is becoming so much, so critical within an organization, it's no longer just a back room collection of data, it's actually becoming a way of doing business. One term I, word I didn't hear you use in that description was technology. Are we making a mistake in thinking of the CDO role as being a technology function? If you are thinking of it as a technology function, it might be a mistake, yeah. I think that what we're advising our clients to do is do more of a collaboration. So if you think agile, you think of a scrum team with specialists in order to solve a problem. And I think the data office, NIT and the business and maybe your project management all come together and bring their own level of expertise. So you do need a technology aspect to provide a solution, but the chief data governor, the chief data office will provide purely the data side of things. Where to get the data, how to govern the data, how to disseminate the data. All of those decisions really are being removed from the IT function. IT function is really just becoming more of an application development function and the data side of it is really becoming separate owned by the chief data office organization. Yo-Yo, I want to change the topic here, talk about what you're doing in Taipei. We hear so much about big data in the context of the United States. It really has been much of the conversations around what is happening on these shores, but what is the state of big data use in Taiwan right now? I'm looking at this question from more tourism industry perspective. Tourism industry traditionally is information intensive industry, but however we are licking off the IT personnel, I mean, we're experts. So for using the big data, comparing with the engineering and also computer science, we are trying really kind of, not just one step behind, it's 10 step behind. So why trying to catch up? So my after in Taiwan, my effort, my role in Taiwan is trying to bridge two sides of people, computer science, engineering, with tourism industry people together. So the conference I'm going to host is we'll have all for a special session on this topic, how these two sides of people work together to have a cross-discipline effort together, IT and the tourism. So we have two sides of people together to work on the big data. So speaking about big data in Taiwan, we have really good people from computer science background to working for the big data, especially right now there are several programs established in different universities. One of them is the co-authored, co-together, we host the conference is the Shuzhou University in Taiwan. They have a really great big data program in Taiwan, the Office of Mass Programs in Taiwan. And then we try to bridge the people from different backgrounds from tourism and also from the CS or ICE background to work together. That's what I'm doing. Yeah, so Joe, one of the things we've been looking at for the last few years is kind of the digital transformation that companies are going through. Can you talk to some of the challenges in what you're helping some pretty big companies in their transformation through the leverage of their data? Yeah, sure. So there's two aspects of it, I guess. One is the technology part and then the other one is the people part. The people part is actually the more challenging part. Making the paradigm shift from traditional methods within the technology space to more of a big data platform. It's been since about 2009, the evolution of data technologies have pretty evolved over the past seven years now. But what's really, for it to really be fully embraced by an enterprise to actually change the way they do business is they need coaching from almost like a management perspective, management consulting perspective, where we have to help our clients not only change their technical platform, but also figure out what does your new organization have to look like to support it, who actually is going to help convert just what was basically tech debt into data assets and then be able to generate new revenue based on your data. That is truly taking your business and kind of turning it on its head, where for the past couple of decades we would make decisions using our conventional wisdom and the brainpower of our executive leadership and then use our data to prove whether it's working or not. But what's happening now is we're actually using our data and the insight from the data to actually drive the decision making. And it's a very, very different way to think about running your business. So becoming a truly digital company takes platform, technology change, processes within your organization and then a reorganization of your people as well. I was just gonna say, any kind of, maybe you can't talk about the company specific but any kind of industry specific use case you could give us on that? Oh, there's several. So we have one media company that was probably one of the leaders in the cable business for the past couple of decades but now the new, the media business is really being overtaken by streaming media, the Netflix and the Hulu's and all of that. So in order to stay competitive, there needs to be a transition. There needs to make some kind of change. So going from broadcast to cable or from cable to streaming media, it really changes, again, those three things. It changes the platform. It changes the people and it changes the way you actually run your business. You wrote a best-selling book on ETL which is a topic of particular interest of mine because I've read that InvigData Project's ETL can consume 80% or more of the time of the people working on the project. Is there some sort of magic elixir that's going to make this problem go away or do you see progress being made toward shortening that owner's task? So one of the, yeah, I wrote that book back in 2004 and it has become an industry best seller and it's still today a de facto standard on how to take data from multiple systems and prepared for analytics in a holistic view. And when I wrote it back then, I specifically stayed away from technology. So it's purely best practices and concepts which are still 100% applicable. The difference now is that instead of doing a lot of cleaning, conforming, consolidating, putting it into a rigid data model before you can actually look at it to do analytics, what's changed is we're ingesting data directly from external sources now that we mostly don't have control over like, you know, clickstream and media and trying to medical records, internet of things, right? All the state is coming into a big data platform now. Could be Hadoop, doesn't have to be. And then we're doing analytics on the semi-structured data within these new platforms. Once we do that data exploration and data discovery and figure out if we can actually get some insight out of it, then we take the valuable parts of it and then we structure that. We put it into still a very structured, rigid data warehouse with traditional BI tools, some emerging BI tools, but the BI tools nonetheless for the masses. And the big difference and the big paradigm shift within these organizations is all about governance. You know, the Hadoop or the big data platform was not embraced by the enterprises as quickly as I thought it would have. Like I predicted in 2009, by like 2012, most of the companies would be running on a big data platform. And I think the difference is that most enterprises are used to having fully governed, fully structured data in order to distribute it to the masses. And so what I'm trying to help my clients understand is to really understand the use case for your data and to have more of what we call tunable governance. So if you have data that is really just for data scientists to munch the data to see if they can get insight, does it really need to go through the rigorous process of being fully governed as it would as if you're writing reports for Wall Street, right? And I argue that it doesn't. Right, so. Yeah, to loosen up. Right, loosen up exactly. So that's what we're doing. We're coaching our clients on how to come up with the best practices in today's modern data engineering world. Yo, yo, I'm curious for your conference, what are some of the kind of the key concerns, questions, you know, tracks that you'll be going to. So some of the things that Joe talked about that resonate with you? Before I go into that, I was appreciated for attending this conference in Portia. Actually, most of the topic we are going to talk about will be similar as this one. One thing that's very huge about this is the security and privacy issue. And we are more, if we definitely address it, the one is the cross-discipline collaboration because we perceive the big data and also data governance is not just one discipline issue. It has to bring bridge the different discipline of people together and to work together. So one, the other issue is collaboration. How do we communicate across discipline? That's the second big issue. For, we just keep hearing about the one section doesn't talk to the other people together. It says collaboration actually will be a big hurdle in between the, when people collaborate together. So privacy, security, and also collaborations will be the main to talk about it. Very similar issues as are being debated here. We're almost out of time so just to give you the last word here, is the Chief Data Officer role emerging in your region as it appears to be here? No, I will say no, especially for the tourism industry. Consider it's not a money-making position. So it's right now for the tourism industry is not a position there. But I will say that definitely in the future there will be, this position will be needed in place because as I mentioned, is information intensive industry. So eventually this position will be created for the Chief Data Officer to be here. With that, we're out of time. I want to thank you, Joe Caserta very much for joining us. My pleasure. Yo-Yo Yuan, thanks for joining us. Best of luck with your conference. Thank you. Thanks for having me. Symposium, yes. Symposium. We'll be right back from the MIT CDOIQ symposium in just a moment.