Data professionals are all about speed in 2016, according to recent discussions at the Strata & Hadoop World conference in San Jose, CA. The reason: most believe they now have the proper data management frameworks in place at their organizations, and it’s time to cash in on the potential benefits.

According to Jana Eggers, CEO at Nara Logics, there is a definite fly in that ointment, however: the continued limitations caused by data silos throughout most organizations. This is causing continued frustration for data pros, who are anxious to see action from their efforts to date.

 

Q: What are the most common themes that you heard among conference attendees and how do those themes align with what you expected?

Jana Eggers: The most common theme was one of urgency. What I heard from attendees was that they believe they have at least the right framework for data management and policies. Now, it is time to get to using that data for more action. Many are still working through how to bring data into current applications so that better decisions are made real-time and in context.

For some this is a move from supporting analyses to enabling fast decisions. For others, it is a focus on bringing together the right data at the right time in context of internal and external applications. It was an energetic conference based on this!

 

IM: What are the most common challenges that attendees are facing?

JE: The silos of data are still causing problems. People created data in one area, and don't, or even aren't allowed to, share with another internal group. This is frustrating for the data scientists who see all the unlocked potential in data that's being held back.

Another silo is data stored in enterprise apps and not easily co-mingled with other data. This means we don't get full pictures of customers, for example, and how they are interacting with the company, leaving at best frustrated, if not angry, customers.

 

IM: What are the most surprising things that you heard?

JE: While big data is still a big phrase to throw around, I heard many people talking about better utilizing the data they have. For example, whereas before, I heard a lot about using external sources for data augmentation, I heard more about bringing data together that enterprises have already on their customers.

So, along with the theme of silos, I heard about people busting silos to accomplish more with "big enough" data. There is absolutely a great opportunity in big data, but many companies are focusing first on data that's closer to them and their customers -- whether it is actually big or not.

 

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

JE: As we are in the artificial intelligence space, we are excited about the opportunities that AI brings to the table with deeper and richer data analysis. For example, the work done in deep learning has proven incredible results from personalization to fraud detection. People have not fully realized how integrated AI is into business even right now.

The challenge that we see is moving AI from an R&D project at most companies into production. More people need to understand the capabilities and limitations of where we are now with this new technology. Right now, we have great test pilots flying these planes, and now is the time to move to a more generalized understanding what projects are possible and how those can be delivered and measured.

 

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

Our platform produces recommendations -- for which anomalies in a supply chain could lead to an actual issue OR which account manager should get a lead OR which offer to make to a customer. So, the move to action from analysis fits well with the problem we are solving for customers.

With each of our customers, we start with a pilot project, which is meant to (1) demonstrate how the system works with a real business problem and (2) show valued results. So overall, these themes and challenges haven't changed our strategy, just made us busier. And that's a good thing.