Rethinking the Data Warehouse for Business Intelligence

By
  • Ben Tai
Published
  • July 27 2016, 6:47am EDT

Because IT has to create business intelligence reports and analysis, there is essentially an extra layer of work required for business end users to obtain the data they need.

This extra layer of data handling on top of IT’s lack of functional business savvy expose the reporting process to the potential for errors.

The longer it takes to create complete and useful reports, the older the data in them becomes and the greater the chance it is invalid. All things considered, it isn’t unheard of for a data warehouse to exhaust more resources than it generates.

Research from Gartner indicates that fewer than 30 percent of BI initiatives actually achieve the goals they were designed to reach. Despite huge investments in building sophisticated data warehouse systems, BI projects often falter because business end users and their reporting facilitators in IT have trouble working in sync to collect the right information in a timely manner.

Inflexible Warehouse Misses the Mark

Depending on how a data warehouse is built, responding to new reporting or analysis requirements can be a challenge. When new data sources need to be established to create a particular report or analysis, it can take IT days, weeks or even months of intensive labor to make the required changes to the data warehouse structure and ensure its integrity. During this process, existing reports and analytics can actually be broken.

Even with daily data updates to a data warehouse, reporting cannot happen in real time. Data is most often filtered in such a way that by the time it is shared in a report or analysis, it is days or even weeks old. Reporting that relies on stale data does not facilitate agile responses to changes in the marketplace. Such a rigid BI system may function well for limited defined analytics, but it doesn’t accommodate ad hoc data requests or dynamic analyses.

A Better BI Platform

While managing business analysis without this traditional on premise system is a novel idea, relying on IT staff and a static data warehouse is no longer the only way to satisfy BI needs. Cloud-based business intelligence platforms are gaining momentum as the choice alternative to expensive and cumbersome data warehouse solutions. These agile, self-service cloud BI tools save users the time and expense of depending on IT to build and manage a complex data warehouse.

Next-generation cloud BI is fully functional to business end users within days of its implementation. It’s a server-free solution that features a simple interface through which users can talk to the system to tap robust intelligence that’s stored in the cloud. There are no servers, programming or problematic technology tools needed to create multi-dimensional reports that would be impossible to compile through a traditional data warehouse model.

Cloud BI can even run by itself, saving users countless hours of manual data transfer with its automated importing and reporting features.

Today, organizations need to function at the speed of business dynamics to remain competitive. Thankfully, there is pioneering technology that dramatically boosts access to the BI needed to stay agile. Cloud-based, self-service BI is the most efficient way for companies to stay ahead of the curve with timely insights that drive innovation and bigger profits.

(About the author: Ben Tai is the chief executive officer at DrivenBI)

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