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Traditional business intelligence (BI) and analytic models are being disrupted as the balance of power shifts from IT to the business, according to Gartner. The rise of data discovery, access to multistructured data, data preparation tools and smart capabilities will further democratize access to analytics and stress the need for governance. Gartner predicts that by 2017, most business users and analysts in organizations will have access to self-service tools to prepare data for analysis.
"Data preparation is one of most difficult and time-consuming challenges facing business users of BI and data discovery tools, as well as advanced analytics platforms," said Rita Sallam, research vice president at Gartner. "However, data preparation capabilities are emerging that will provide business users and analysts the ability to extend the scope of self-service to include information management, and extract, transform and load (ETL) functions, enabling them to access, profile, prepare, integrate, curate, model and enrich data for analysis and consumption by BI and analytics platforms."
Predictions about BI by Gartner
By 2017, most data discovery tools will have incorporated smart data discovery capabilities
As data discovery capabilities are becoming smarter to streamline pattern detection in data discovery, self-service data preparation capabilities are evolving and becoming more capable of semiautomating and enhancing the data preparation activity of data discovery, and making it accessible to a business analyst. The two advances in combination will create a next-generation data discovery user experience that makes advanced types of analysis accessible to a broader range of users.
Through 2016, less than 10 percent of self-service BI initiatives will be governed to prevent inconsistencies
End-user clamor for access to business data, combined with IT's inability to satisfy this need, has manifested in self-service BI initiatives in many organizations. The growing increase in data volume, velocity and, especially, variety has further fueled 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.
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