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Interview with Dr. Rado Kotorov, Vice President of Product Marketing at Information Builders

by Jon Hazell, Administrator, Dashboard InsightTuesday, December 3, 2013

Recently, Dashboard Insight had the opportunity to sit down with Dr. Rado Kotorov, VP of Product Marketing for Information Builders (IBI), and pick his brain on a number of different items, including: how he became involved in the business intelligence (BI) field; the BI space today and where it is going; and dashboards and data visualization specifically.

On getting involved in the BI space

“Some fluke and chance” was Dr. Kotorov’s immediate response with a slight chuckle. He went on to explain that after receiving his doctorate in Decision and Game Theory and Institutional Economics his first job involved building information management systems. It was at this job where he ended up moving into a C level role.

His next career opportunity moved him into advanced analytics. While the concept of “big data” hadn’t yet become part of mainstream BI strategies, it was during this time that he was asked to do his first “big data” projects for a pharmaceutical company and another fortune 500 company.

From this experience Dr. Kotorov moved to Information Builders, where he has been for 8 years. Dr. Kotorov was originally hired to start the strategic project management group but has since moved into the role of Vice President of Product Marketing.

When asked what keeps him interested in the field he responded “I’m always surprised by what I find in the data… there is always something interesting.”

Dr. Kotorov has a couple of pieces of advice for those entering the BI field today:

Develop inter-disciplinary skills:

  1. Understand the databases and structures behind it. Become familiar with data modelling. This will help with moving to larger and larger datasets.
  2. Get integrated with statistical analysis. While Dr. Kotorov believes this should be taught in an intuitive way (instead of teaching formulas there should be more of a focus on how to understand them and glean insights). This helps to deal with multi-dimensional data. If you don’t understand how the whole process works you can end up with the wrong conclusions.
  3. Understand the business. Familiarize yourself with use cases, accounting, etc. If you know how the business works then you can tailor BI solutions to simplify the decision making of the business people.

He says that when you have groups who only understand one of the above concepts it can be like having people who are speaking different languages. If you have someone or a group that understands all of the concepts then they can translate for others and the business intelligence process becomes much easier.

On Business Intelligence

Dr. Kotorov believes the biggest challenge facing BI today is widespread adoption. While we are starting to see BI being pushed into mainstream business strategy, it’s not considered an integral element yet. Figuring out how to make BI more prevalent is the challenge. Dr. Kotorov talked about how Jack Welch was one of the first people in the business world who understood that everyone needs to have information in order to make more informed decisions; that the democratization of information is only going to allow people to become more effective. Everyone needs to make decisions, better-informed decisions.

Information Builders has done a number of studies on how to overcome this challenge. One issue is that the BI industry has been pushing a lot of tools to people, self-service tools included. As Information Builders continued with its studies, it found that this was the wrong approach. Professionals who need BI tools need to have options for better tools; however, the professionals who simply need to have BI information need to have applications that suit this purpose.

The key, he explains, is to deliver a software tool to people who do analytical work and develop the applications, rather than the professionals who just need to look at the data and make decisions.

Dr. Kotorov describes a “fast” and a “slow” brain. The fast brain makes decisions on the spot (fight or flight) while the slow brain takes time to really analyze a situation.

  • All professionals familiar in their own field use the fast brain when viewing information that they are familiar with and is applicable to their field – fast brain
  • Analysts need to sit down and rationalize everything – slow brain

Big Data

It’s easy to see that there is a lot of hype surrounding ‘big data’ so it can be hard to discern what’s true.

Dr. Kotorov estimates less than 5% of enterprises ever need or are actually using big data and that we should be focusing more on ensuring data, big or small, is analyzed properly. He says, “A lot of people have been realizing that big data has no meaning, they don’t have it and have no need to analyze it.” On the other hand, he recognizes that there are some fields where it does play an important role. Pharmaceutical companies are an example; as Dr. Kotorov says, “[they] had big data before it was even coined.”

Dr. Kotorov sees telematics and machine-generated data developing as a field around big data. We can use big data information to optimize fuel efficiencies and lengthen the life of machines. We will ultimately be able to make accurate predictions as a result of big data.

When it comes to big data created through social media, Dr. Kotorov explains that, while we can collect a lot of data, this type of data has a short life. Organizations are likely only going to store a year’s worth of social media data or only information they have deemed important.

Dr. Kotorov says we will learn how to weed out the noise and start using the data from big data that is important and relevant. While the significant hype around it may wane, he does believe we are finding more and more useful things to do with it.

Predictive Analytics

While Dr. Kotorov does believe there is some hype around predictive analytics he notes that it has been around for a significant period of time, and the hype comes from greater visibility. He points to an application Information Builders created for a police department four years ago, which gives officers on shift the ability to see where crime is predicted to occur, taking what he called “the gut feeling out of the decision making.”

He says one of the limitations to predictive analytics had been the cost, with sixty percent or more of the cost for advanced analytics laying in the preparation of the data, but that integrated open source engines like R have helped to reduce costs. As predictive analytics has become more affordable it has increased its availability and use.

Mobile BI

Dr. Kotorov is in step with the perspective that Information Builders has taken, to be device agnostic. One of the biggest reasons around this is cost effectiveness. Information Builders’ focus has been on web applications enabled for all technologies. Applications that morph to the gestures and UI paradigm of each device rather than applications built for specific devices.

One of the most common ways Information Builders has made use of mobile is by sending an email attachment that, when opened, is recognized like a mobile app regardless of the device.

Dashboards

Dr. Kotorov estimates that about twenty-five percent of companies he sees are using dashboards at the moment. He regards dashboards as severely underutilized, and believes it may be a generational issue. He does see think this trend will change drastically, however. Another issue to adoption he raises is the dichotomy of tools vs. applications, where tools are used by the developers and analysts, and applications are used by the layman or typical business user. He sees a number of dashboard companies caught in between the two when they may only offer one. “If companies start creating one off applications for each need that people have, maintenance would become a nightmare.” Tools are necessary for more technical groups within organizations in order to deliver customized and sophisticated dashboards. More generic dashboard applications are necessary when dealing with standardized issues (a financial dashboard application for example).

“Mobile devices will tremendously help with this,” he responded when asked about other ways to improve adoption. “A dashboard is one thousand times more valuable on an iPad than a PDF report.” He recalls one company he worked with that has eliminated excel spreadsheets in favour of dashboards, saying “You can pack more information for making a decision in a dashboard.” Touch screens are also a feature he feels will aid adoption rates, as people feel they can interact with the dashboard more.

The biggest issue facing dashboards? “Shortage of people who can design and implement good dashboards.”

Dr. Kotorov also issues a warning about data visualization in general, however. He sees a lot of confusion in the market, where organizations are offering data visualization as an easy way into pattern recognition, but there is a danger in drawing conclusions from data visualizations without drilling down and looking at the base data for clarification.

“People aren’t aware how much damage can be done in pattern detection.” He cites the Simpson paradox in which a trend that appears in different groups of data disappears when these groups are combined, and the reverse trend appears for the aggregate data. “Some correlations can be random. Correlation on aggregate levels can be completely different on the base level.”

He believes that we have hyped the use of data visualization but not the need for analysts. “Statisticians can run the numbers through a machine and come up with the meaningful patterns instead of looking at the visuals and expecting to glean something magical.” He also stresses that we must absolutely ensure validity and accuracy of the information we are viewing in data visualizations.

Where are we going?

For Dr. Kotorov the answer is clear: adoption. There will be a drive for adoption as we begin to see a generational shift in the workplace. He sees the younger generations (Gen X, Y / millennials) as much more receptive to business intelligence, and, as their influence has grown, so too has adoption. When he started at IBI, it focused mainly on reporting, dashboarding, and MS Office integration. Now, the need for advanced visualization and advanced and predictive analytics has increased nearly tenfold. The last three years in particular have been marked by an explosion of new technology in the BI space.

Dr. Kotorov also sees a lot of potential in unstructured data and has noted vendors moving to jump on this – Oracle (Endeca), SAP (Business Objects).

Overall he is excited for where the industry is going and growing.

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