Claudia Imhoff Discusses the Important New Trends in Data and Analytics
by Ron Powell
Originally published March 12, 2019
Claudia Imhoff: Thanks so much Ron. I’m excited to be speaking with you.
Claudia, before we discuss your TDWI presentation, can you tell us about the BBBT and how it provides a unique way for practitioners, vendors and experts to discuss and evaluate the latest technologies for business intelligence, analytics and data management?
Claudia Imhoff: I’m very proud of the Boulder BI Brain Trust, and if anyone is interested, they can check it out at BBBT.us. We’re a consortium of about 250 members – independent analysts, consultants and practitioners representing about 26 countries throughout the world. We bring together vendors about twice a month and we get a good deep dive into their technologies. It’s a reciprocal agreement, though. Our members do get briefed on current and planned tools and technologies, but the vendors also get incredible feedback from us – such as ideas on where BI and analytics are going, advice on their marketing direction and messaging and input into their offerings. I’m going to turn the table just a little bit. You’ve been a member – it is free, by the way – for years so I’m going to ask you what you get out of the BBBT.
Well, Claudia, I’ve been a member since the beginning, and the best part of the BBBT is the deep dive into what the vendors are doing, what their directions are, how they’re moving in the market and then also being able to provide feedback to them. It’s not often you get the two-way street going back and forth with the vendor. I think it’s beneficial for all of us.
Claudia Imhoff: The vendors really appreciate the feedback.
Getting to your presentations at TDWI, could you discuss your relationship with TDWI, and what are you seeing as the most important new trends in data and analytics?
Claudia Imhoff: I’ve been with TDWI since the very beginning, 22 years ago. I’ve presented at almost every single conference in those 22 years. I’ve missed a few over the years, but not very many. I think TDWI, as they put it, is the premier conference to learn all the new things and to get a good basic foundational education. They give you a good grounding in analytics, BI and the related technologies. They have a boot camp. It’s an incredible resource to really learn everything you need to go off and be very successful in this industry.
You asked me about new trends. There is so much going on right now. One of the things that we just talked about at the February TDWI was the combination of artificial intelligence or augmented intelligence – whichever way you want to look at that – and machine learning with analytics and data visualizations. Vendors are bringing these very sophisticated, advanced analytics into visualizations and BI, really augmenting what you’re getting.
The other thing we talked about in February, and again this is something I’m very proud of, is that TDWI and the Boulder BI Brain Trust combined to create what we’re calling the TDWI Landscape. The Landscape is made up of eight components. I’m not going to go into great detail because we don’t have time, but at the very bottom, of course, are the data platforms where the data is ingested, persisted and so forth. Above that is data integration, always needed, which comprises all the technologies that capture and prepare the data for analytics. Above that are the analytics, and those are the technologies that help all the business users find their inputs, the patterns in their data, and so forth, using all kinds of techniques. Above that is discovery and visualization. Again, a very important part of that is being able to visualize the results of the analytics. On top of that stack are the solutions – the vendors are now creating common applications for both vertical and horizontal business functions. And there are some vertical stacks that we have to have that encompass the entire landscape. The first one is deployment. Of course, deployment now is public cloud, private cloud, hybrid cloud or on premises – whatever you want. The next one is security and privacy around the data and the utilization of the data – so critical today. Finally, is governance. Governance consists of the overarching processes that control or at least have the authority over the entire environment itself. We’ll talk about those a little bit later on when we talk about a new class that I’m developing for TDWI in Chicago.
Having this Landscape to follow and move forward is so practical for anyone who is now doing data and analytics.
Claudia Imhoff: The nice thing is that TDWI and the BBBT are putting the vendors in the Landscape. There’s a logo slide. It is going to get real crowded really fast. For example, you’ll want to know what companies are data platform companies. You’ll see all the logos of those companies, and you can start to do your research on them and figure out which one best fits your organization.
In your presentation, you also spoke about the data interpreter, calling it the hottest new role in analytics. Organizations already have data analysts, data scientists and business analysts. What exactly is a data interpreter and why do today’s organizations need them?
Claudia Imhoff: Let me tell you the story about how I came to the conclusion that we need data interpreters. I was working at a company, and the CEO called me into his office. I was working with the team to create the analytics environment, and he popped his head into the room and asked if he could speak to me. I went into his office, and he opened a drawer and pulled out a skinny three-ring notebook and turned to the first page. There was an incredibly complex, colorful, vibrant chord chart. And he turned to me and said, “My chief data officer just left this notebook, and he kept pointing to the graph.” He said to me, “You can see from this graph why we’re losing our market share, where our customers are going and why our revenues are not growing the way they should be.” The CEO looked at me and said, “I don’t get it. It looks like my retinal scan.” That’s when the light bulb went off in my head, and I realized that chief data officer was not interpreting the data into something that a business person could understand. This is a clear example of the need for data interpretation.
Let me just talk a little bit about the skills of a data interpreter. First of all, of course, they must have a deep knowledge of business processes. They have to understand the business processes and terminologies because they have to be able to speak to business people in terms that they understand. But, they also have to possess a good understanding of the data analytical processes at well. They’re looking at very complex visualizations and algorithms and so forth. They don’t have to be a data scientist, but they at least need to have a grasp of the statistical underpinnings – what’s a regression, what’s a cause-and-effect analysis, correlation, causation and so forth – because they’re going to have to take that very complex graph and translate it into something that an ordinary mortal can understand. Not everyone has the ability to present in an interesting, engaging and thought-provoking way and, of course, answer questions and take criticisms with grace – because you’ll always get criticized.
The last thing that I would recommend in terms of skill sets is the ability to write concisely and clearly because instead of a verbal presentation, a data interpreter may have to create a written one. If they can’t write in a way that people can understand, they’re going to fail. They’re just simply not going to be the trusted advisor of that CEO.
So that’s the skill set for the data interpreter.
What else can aid the data interpreter in insuring that the data used for analytics is trusted and readily available for analysis?
Claudia Imhoff: There are a number of courses that I recommend when I teach the class. Believe it or not, they have very little to do with technology. But the first one that I highly, highly recommend for anyone who wants to jump into the shoes of the data interpreter is to take an analytical or critical thinking course. So many people don’t know how to think critically. It’s probably in a philosophy department, but it really hones that analytical mind and those analytical capabilities to ask the next logical question – to question the actual results and be able to understand the results themselves.
The next one is a technical writing course. Data interpreters need to be able to write because they will be writing a lot of business case studies, a lot of data stories, a lot of content and so forth.
Public speaking is the third one. I'd recommend a course from Toastmasters International or something like that group because all data interpreters will have to be comfortable speaking to various audiences.
The fourth one – and I’ll apologize for this one up front – is an accounting course. A data interpreter has to be able to speak in the terminology of the business. Well, accounting is the lingua franca of all businesses and government entities. When someone says, “What’s the bottom line?” that’s an accounting term, and the data interpreter needs to understand what that means.
The last one is a color theory course. This is a course that I hope is taken by everyone who does visualizations, these beautiful graphics. A color theory course provides practical guidance to color-mixing visual effects with specific color combinations. A color theory course can be found at an art or design school, or for any of these five, you can go to online courses or whatever, but those are the five courses that someone who wants to be a data interpreter should take.
Well, Claudia, that is great description of the role and skill set of a data interpreter. I understand that you’re going to be giving a half-day course on data catalogs – such as Alation – at TDWI in Chicago in May. Do you see data catalogs as a critical component of a company’s strategy to become data driven so that they can harness the benefits of BI and analytics?
Claudia Imhoff: I sure do. What we have today in most analytic environments is unfortunately a lot of chaos. The data catalog is something that mitigates that chaos. I hear all the time, “There is data everywhere, there are reports everywhere, and there are analytics everywhere but I can’t find them.” Companies are suffering from this embarrassing wealth of analytic products that they can’t find because they’re all over the place. They are in multiple BI and visualization tools, multiple analytical tools, and platforms all over the place; but the data catalog is one of the most important tools that a company and especially the data interpreter can have to find out more information about a specific analytic, report or the data itself. To understand what the data catalog is, let me tell you a story that a friend of mine who is a co-founder of a data catalog company tells.
This is how he describes the data catalog. He says it’s not just data. He says, “Think about the largest catalog in the world, Amazon. Amazon started out selling books – they had a book catalog. Today, Amazon has everything – books, electronics, movies, almost anything you can think of. It tells you how much each offering is and provides a detailed description of it.” And that’s what I see as the future for the data catalog. It will be so much more than just data. It’s going to contain analytics. It’s going to contain content. It’s going to have information about who you should contact if you want more information about a particular piece of data, or analytic or report or visualization. Think of the data catalog as the Amazon catalog for analytics. It’s will be a very big and critical part of any company’s strategy. I hope that helps.
That helps a lot, Claudia. I want to thank you for being my guest today, and I’m looking forward to your presentation on data catalogs at TDWI in Chicago. I believe it’s the week of April 28, and it would be great to do a follow-up podcast with you at the event.
Claudia Imhoff: I would love to do that! That would be my pleasure.
Thank you so much, Claudia.
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