You may have been successful with a center of excellence for your business intelligence or analytics practice. But big data success requires a different approach, a bus.
So you want to invest in big data capabilities? You may be asking yourself who should be on the big data team, and what project should this team work on first? How do you put together the capability -- the team -- to tackle the big questions?
Organizations may find themselves hung up on these types of questions, whether they are just starting out with big data or even if they already have projects underway. Tamara Dull and Anne Buff recommend turning around the way you think about your Organization's big data capability and staffing if you want to succeed in big data.
They should know. They've been thinking about how to succeed with big data projects for years.
Buff is Business Solutions Manager and Thought Leader for SAS Best Practices. Dull is Director of Emerging Technologies for SAS Best Practices. Buff and Dull spoke to InformationWeek in an interview about how organizations can avoid the stumbling blocks that trip up so many when they put together a big data practice, and they'll also address the topic during a session at Interop ITX, designed to help any Organization that is starting or in the middle of a big data project.
"Big data is not new," said Dull. "It's a lot of data that we've had for decades, and we've been dealing with it already. What's new is all these technologies that have come on board -- a lot of them are open source -- that enable the capabilities of mixing and matching all of our data. You can take your social media data and mix it up with your CRM data and mix that up with your sales records.
"This is not BI 2.0," Dull said. "This is a bit different."
These efforts don't replace your BI and analytics programs. This is "in addition to," Buff said.
Part of the problem that organizations encounter when they start with big data is that the factors that lead to success with these projects are different from the factors that helped people succeed with business intelligence. Business intelligence and analytics practices are often housed in centers of excellence. But you don't want or need a big data center of excellence.
