Why power shift in Business Intelligence and Analytics fuels disruption

Traditional business intelligence (BI) and analytic models are being disrupted as the balance of power shifts from IT to the business.

"New approaches have the potential to transform how and which users can derive insights from data discovery tools.

“The potential business benefit will lead to a shift resulting in smart data discovery becoming standard features of most data discovery platforms.”

Moreover, Sallam says that this evolution will likely facilitate accelerated growth of the citizen data and make new sources of information accessible, consumable and meaningful to organisations of all sizes, even ones that don't have extensive advanced analytics skills or in-house resources.

Sallam believes that through 2016, less than 10 percent of self-service BI initiatives will be governed sufficiently to prevent inconsistencies that adversely affect the business.

End-user clamour for access to business data, combined with IT's inability to satisfy this need, has manifested in self-service BI initiatives in many organisations.

The growing increase in data volume, velocity and, especially, variety has further fuelled this trend. Vendors have responded with mass consumable, broadly deployable, easy-to-use and, often, cloud-based technologies for basic query, analysis and reporting.

Often, these solutions are implemented by business units that have circumvented IT and as a result, they are disposed to analytic sprawl — an inconsistent or incomplete use of data, capricious development of metrics and formulae, and either too-restrained or unrestrained sharing of results.

"As a result of the limited governance of self-service BI implementations, we see few examples of those that are materially successful — other than in satisfying end-user urges for data access," adds Doug Laney, research vice president, Gartner.

"This, combined with increasing examples of data privacy and security breaches, along with anticipated instances of public disclosure inconsistencies, will temper businesses leaders' enthusiasm for self-service BI.

“From unfortunate occurrences like these, we expect resulting investor and customer blowback for organisations with ungoverned, or loosely governed, BI initiatives."

To counter these adverse effects, Laney believes a return to more controlled enterprise BI implementations is expected, or the deployment of self-service BI technologies within a better governed, IT-led project environment.

On the technology front, Laney says vendors will to continue to play both sides, but more conscientiously — selling simple data discovery technologies broadly throughout their prospects' businesses, while re-emphasising the advantages of controlled, centralized and more-robust enterprise BI technologies.

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