Four trends are changing the face of business intelligence, according to a new report by Forrester Research. Here's the analyst's take on the shift along with ten suggested best practices for forging an up-to-date strategy.
Business intelligence (BI) sits at the top of the IT priority list for many enterprises. Enterprises that haven't paid enough attention now see a need to act, and those that have kept up with BI want to consolidate their siloed implementations.
How do you get started? Enterprises face many choices, and they cannot begin with vendor selection. Tasks like data governance, matching requirements with logical architectures, and picking an experienced architect and implementer should be at the top of the list.
This synopsis of Forrester's recent report, "It's Time to Reinvent Your BI Strategy," offers an abbreviated look at the paper's insight on four trends and ten best practices you should look toward to reshape you BI strategy.
BI: No Longer Just About Reporting
Forrester defines BI as a set of processes and technologies that transform raw, meaningless data into useful and actionable information. The crowded market segment of BI often gets mislabeled, can be very complex, and constantly changes. The BI market pulses with alternative approaches, contradictory technologies, and hundreds of vendors that constantly move to consolidate, innovate, and leapfrog one another. Enterprises at the beginning of a perilous BI journey need guidance and help untangling the web of BI complexities.
BI First-Time Purchase Plans (click image for larger view)
For first-time purchases, BI applications actually lead the pack of application software priorities with 13 percent of enterprises planning a purchase in 2007 (see "BI First-Time Purchase Plans" chart). Here's why:
Enterprises can't just focus on being efficient anymore. Squeezing more efficiency from operational applications such as ERP, CRM, or SCM no longer helps enterprises to stay competitive. BI-enabled applications are needed for business processes and business operations to become more effective. For example, workflow and rules can be used to efficiently process a customer credit application, but BI analytics can effectively segment a customer population and target credit offers to specific customer segments for a better response and improved cross-sell and up-sell ratios.
Explosive data growth demands serious attention. Digital data volumes — both structured and unstructured — are growing by 30 percent per year. The kind of lightweight spreadsheet-based BI applications common today won't be enough for reporting on and analyzing mountains of data tomorrow.
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