Utilities: Forget about Big Data! (Start with small data, then work your way up)



By Jesse Berst


Here's one of the biggest mistakes utilities make when confronting Big Data.


They start big.


Don't get me wrong. I am opposed to the piecemeal approach to data analytics. I don't think all the business lines should assemble dinky one-off analytics projects on their own. Rather, I think utilities ultimately need a "platform" - a powerful set of tools and algorithms that can be leveraged over and over again to create new solutions.


But the platform approach requires enterprise-class software. And that means an enterprise-class procurement process. Multiple vendor visits. Multiple use cases. Pilots and trials. Competitive RFPs. And months (years?) of effort before something is finally in place.


(Not to mention months of effort to pry the needed information from the various databases where it's currently squirreled away.)


There's a better approach, as I learned recently when interviewing experts in preparation for our upcoming April 2nd, 2014 webinar on how to get started with utility analytics. (Click to reserve a spot where you can get advice from CenterPoint Energy, Duke Energy and eMeter. It's free to Smart Grid News readers while space remains.)


The start-small approach instead

While you are waiting for your company to figure out its enterprise data analytics approach, why not take the meter data you've got already and use inexpensive, cloud-based analytics tools to get some quick wins and quick paybacks?


Here's the thing about meter data as a starting point - it "plays a role in analytics no matter what direction the utility wants to go," explains Aaron DeYonker, Vice President of Products at Siemen's eMeter subsidiary. So even if you will ultimately end up with an enterprise data warehouse, you'll have a head start on understanding and exploiting the meter data that will eventually end up there.


And since you can use lightweight, cloud-based tools to get started, you're not out of pocket for a big investment in hardware and IT staff to support it.