Data is growing in volume and complexity, and with it, more organizations are moving to a distributed model for their business intelligence and analytics efforts. That is the conclusion of Lance Walter, chief marketing officer at Datameer.

Information Management caught up with Walter at the recent Gartner Business Intelligence Summit in Grapevine, TX, and asked what he heard most from attendees this year in terms of analytics efforts and vendor needs.


Information Management: What are the most common themes that you heard from conference attendees?

Lance Walter: The Gartner BI and Analytics Summit is always about how companies use analytics to get more value out of the data in their organizations. This year, there was more of an emphasis on distributed models instead of the classic, centralized "BI Competency Center" approach of years past.

It was clear that many attendees have moved their organizations to more distributed models for analytics that can enable critical business velocity while sacrificing some, but not all control.

"Modern BI Platforms" was a recurring theme. The analytical challenges have evolved from things like "How much did customers buy of Product X compared to Product Y last quarter?" to "What customers of Product X are the best cross-sell targets for Product Y, and what does their consideration journey look like, online, offline, and on mobile?"

Self-service data preparation was an element of "Modern BI Platforms" that's also getting attention - there is clearly an increasing expectation that analysts and business users should be able to get at the data and make sense of it without a lot of IT involvement. Many of the analysts view data preparation as a “feature” rather than a solution, but for the class of users that only worries about getting the data together for someone else to analyze, it makes sense.

This generated a bit of controversy. There were traditional vendors who reject the premise of a new class of platforms or a separate magic quadrant, as well as attendees who are trying to “make black and white out of grey” in understanding current and future tools. Clearly a good chunk of the attendees just think, “It’s all BI,” without consider for old vs. new platforms.


IM: What are the most common challenges that attendees are facing with regard to data management and data analytics?

LW: Attendees are definitely dealing with data of different shapes and sizes compared to years past. Five years ago, nearly all of the data for analytics was well-structured and lived in relational databases. Now there's social, sensor, logfile and other data out there that business analysts want to harness.

Many companies don't know how to access, integrate, economically store, secure, and govern that kind of data. There's a lot more to it than just the cool business questions that that data now makes it possible to ask.

Enabling end user self-service was another key challenge. The cloud and other forces have generally shrunk the IT department, and IT doesn't want to be the bottleneck between data-hungry business users and their data. But they also don't want information chaos and users showing up at a meeting and arguing over who has the "right" numbers. So they're trying to provide the right amount of IT control while significantly increasing end user access and autonomy.


IM: What are the most surprising things that you are hearing from attendees?

LW: The tone around cloud deployments was markedly different this year. BI and analytics has moved more slowly to the cloud than categories like CRM or expense management, mostly due to security concerns. People are getting more comfortable trusting the cloud, and they're becoming less patient to wait for hardware and software procurement and configuration to be done before they can start mining their data for insight.

I was also surprised at the level of interest in governance as a topic around big data. The market is maturing rapidly as organizations evolve from their "1.0" big data initiatives and realize that if you really want big data to become an integrated part of your infrastructure and your business processes, you have to be able to govern it effectively - to control who can see what, to know where any piece of information came from, who touched it and how, etc.


IM: What does your company view as the top data issues or challenges in 2016?

LW: Gartner predicted that through 2017, 60 percent of big data projects will fail to go beyond piloting and experimentation and will be abandoned. The conversation has shifted from technology development to how to get business value from it.

Second, as big data analytics becomes more mainstream, the market will need to determine how to effectively establish data governance for the Hadoop ecosystem, especially as new technologies are introduced.


IM: How do these themes and challenges relate to your company’s market strategy this year?

LW: We've focused on simplifying the entire big data analytics process much as possible. People don't care what's under the hood - they just want it to work, and work well. We recently announced Datameer Cloud so that business analysts can get up and running right away without the time and cost to implement hardware and software infrastructure or having to find scarce, expensive Hadoop skills.

We are also focusing on helping companies find value in their big data beyond just the technology conversation. We want to help companies understand how they can figure out their use cases and get the best value from their investment.

In regards to governance, we realize it can't be a second-class citizen. We are committed to giving businesses transparency into their data pipeline while providing IT with tools to audit diligently for compliance with internal and external regulations. We announced new data governance capabilities last year, but it continues to be a common theme in our strategy.

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