May 08, 2012

1. Empower business users. "Move modeling outside of IT," advises Rita Sallam, research director for Gartner. "Business users need to make predictions based on what happed -- without having a Ph.D. in statistics."

2. Establish good governance. "Put data governance processes in place to reduce the risk of data silos, data fracture and definition fracture," Sallam says.

3. Develop a fact-based culture. "Ensure your culture is ready for fact-based trading," says Sallam. "Old-school traders are accustomed to other methodologies."

4. Ensure a solution scales. "It's about retrieval times," emphasizes Scott Burrill, managing director at Rosenblatt Securities. "As well as whether, and how easily, a solution integrates a variety of data sources."

5. Look for quick wins. "The days of taking months to implement are gone," says Tableau Software CMO Elissa Fink. "Choose a solution that permits learning as you go."

6. Consider your mobile strategy. "Will you provide access for people dashing between meetings within your building or for mobile employees off-site?" asks Fink. "Make sure your analytics solution aligns with your needs."

7. Manage in-memory correctly. "In-memory solutions aren't a panacea for performance," warns Gartner's Sallam. "They must be properly sized, tuned and managed."

8. Encourage data literacy. "Successful organizations encourage everyone, regardless of job function, to become numbers literate by using that data to ask questions and get answers," Tableau's Fink says.

[Big Data Payday: Rosenblatt Visualizes Success With a Proprietary Platform.]

ABOUT THE AUTHOR
Anne Rawland Gabriel is a technology writer and marketing communications consultant based in the Minneapolis/St. Paul metro area. Among other projects, she's a regular contributor to UBM Tech's ...