Build the Right Team for Big Data Success


(Image: ponywang/IStockphoto)

(Image: ponywang/IStockphoto)

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."

[Read the rest of the story about how build your big dat team for success at InformationWeek.]

Jessica Davis, Senior Editor, Enterprise Apps, Informationweek

Jessica Davis has spent a career covering the intersection of business and technology at titles including IDG's Infoworld, Ziff Davis Enterprise's eWeek and Channel Insider, and Penton Technology's MSPmentor. She's passionate about the practical use of business intelligence, predictive analytics, and big data for smarter business and a better world. In her spare time she enjoys playing Minecraft and other video games with her sons. She's also a student and performer of improvisational comedy. Follow her on Twitter: @jessicadavis.

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Re: Taking the first step
  • 3/6/2017 2:59:52 PM
NO RATINGS

And then "the capabilities of mixing and matching all of our data," calls for getting the staff mix just right for the various combinations of analysis we are doing and sending to marketing to use to their advantage in an efficient and manageable manner.

Re: Taking the first step
  • 3/6/2017 2:41:39 PM
NO RATINGS

Yes that should help considering though that other companies and even some associates may not want to share, expecially if they consider their work proprietary or their superiors don't allow that type of association with other firms.

Re: Taking the first step
  • 3/2/2017 5:03:25 PM
NO RATINGS

I agree. You need to always counter the not invented here attitude that some data scientists have, however.

Re: Taking the first step
  • 3/2/2017 5:03:25 PM
NO RATINGS

I agree. You need to always counter the not invented here attitude that some data scientists have, however.

Re: Taking the first step
  • 2/28/2017 8:06:23 PM
NO RATINGS

No question, drawing from the experiences of others helps avoid potential pitfalls while providing a level of confidence for that initial first step.

Re: Taking the first step
  • 2/28/2017 6:14:22 PM
NO RATINGS

The first steps can be painful and filled with anxiety. Start with small experiements and take tiny steps first.   Here networking with friends and other companies can help layout a path using other people's experience.

Taking the first step
  • 2/28/2017 12:17:06 PM
NO RATINGS

Great article on a subject that is pivotal to any organization. The big picture is important but the first step can set the tone for success or failure. Configuration of the team that will drive the big data initiative can be intimidating but a must to get right.

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