Access your Pro+ Content below.
Forging a BI strategy in a user-centric, tablet-crazed, big data world
This article is part of the CIO Decisions issue of May 2012 Volume 13
Call it survival of the fittest, but business intelligence (BI) strategies at many companies seem to be mutating at warp speed these days. Take the example of Sonic Automotive Inc., which, with 120 dealerships, is one of the nation's largest automotive retailers. We view the utilization of data and data analytics as our secret sauce. If you're not using analytics to drive business process and decisions, you will be left behind. When Heath R. Byrd became CIO at the company five years ago, its BI strategy was run on spreadsheets. Executives at its Charlotte, N.C., headquarters lugged big binders full of them to their monthly dealership reviews. Moreover, most of the company's mission-critical business applications were outsourced and the data was housed in databases around the country. That made it hard to have an enterprise data-driven BI solution. Today, Sonic's data is consolidated in a data warehouse, which is monitored continuously for data quality. BI reports are issued daily. Now Byrd's team is extending the reach of BI, ...
Access this PRO+ Content for Free!
By submitting your email address, you agree to receive emails regarding relevant topic offers from TechTarget and its partners. You can withdraw your consent at any time. Contact TechTarget at 275 Grove Street, Newton, MA.
Features in this issue
Most organizations sit on a gold mine of business intelligence. Extracting it requires knowing how analytics projects differ from day-to-day IT work.
News in this issue
Driven by business pressures and user demand for BI and mobility, many companies are developing their BI strategy at what seems like warp speed.
OFS Brands Application Manager Tim Hopper explains why the national furniture supplier pursued a mobile BI strategy and the ways it's paying off.
Big data makes the problem of data silos even bigger. Or does it? Either way, CIOs must make big changes to get the most out of big data analytics.