Big Data's Big Picture: An Insider's View

IW: So what are some examples of new data and bigger questions at Edmunds?

Werther: Their clickstream data, for example, was tagged with all sorts of important attributes that gave them segmentation data and other augmentations that weren't possible in the conventional database environment. The big step was making it accessible to business users. With Platfora, they've enabled the business analysts to do data discovery and visualization from Hadoop.

The future is where it gets really exciting, because instead of just doing path analysis and Web analysis to optimize clicks, they're doing path analysis to optimize revenue. They're connecting the dots across the different types of data -- clickstreams, downstream transactions, and auto-dealer-network data -- so business users can optimize to the metric that matters and not just be stuck with the fiction, feeling, and faith that comes from data that gives you a limited view of events.

IW: BI vendors have talked about "data-driven enterprises" for years. What's really different here?

Werther: What's different is that the whole industry has been built around a traditional data warehousing structure where you have a fact table in the middle and then dimensions around that. But that makes it very hard to connect the dots across different types of events and ask questions about patterns of behavior. We've inverted that so you have the subject, the customer, for example, in the middle and all the event streams around that.

IW: Plenty of vendors talk about developing a more holistic view that spans the silos. Is this really unique to the emerging big data trend?

Werther: Companies are talking about it, but most vendors are just working on rebuilding SQL on this new stack. That doesn't address the big questions I'm talking about because SQL isn't designed for doing event-correlation with behavior.

IW: And yet one of the big trends in 2013 has been the SQL-on-Hadoop movement because people are saying we can't rely on data scientists and code writing to ask all these questions. Doesn't the SQL option at least give more people access to big data?

Werther: BI and the traditional ways of looking at data are designed for certain types of questions and certain types of data. People are starting to realize it's not about re-creating the old. With big data analytics, you can actually develop a 360-degree view of customer behavior. It makes the old questions look pretty thin.

BI might give you pretty dashboards, but they don't really contain the data that you need to make fact-based decisions. There are plenty of good, smart people trying to work with the technologies, but their ability to ask the right questions has been very limited. Big data analytics is going to change that. It's not about trying to re-create BI in this new world and it's not about coming up with crazy ways to use data science. It's about basic business questions like customer lifetime value and the ability to understand patterns of behavior that let you directly change the way you work with customers.

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