Big data value requires purposeful application
Big data value requires purposeful application

While big data has the potential to unleash deeper insights from business intelligence (BI) analytics, deploying these technologies demands a strategy and support for effective implementation. 

Smart Data Collective contributor Matt Davies stated that before using big data tools, enterprises must first define the objective for these initiatives, and how to then empower executives with that information for more actionable purpose. Big data, he explained, is about eliminating silos for a more comprehensive, connected view of information that can transform a business' strategies. In order to leverage these benefits, enterprises will be taking a "data first" approach to collection, storage and management. As a result of effective data integration and management, companies can create a unified view of customers, products and risks. Then, by using database administration services to connect data stores with reporting capabilities, BI analytics can drive better business decisions. However, the challenge lies in making those trends and opportunities actionable. Business process automation, he explained, allows businesses to react more immediately to data.

Other experts have emphasized the importance of big-data-driven decisions. Sandra Zoratti, vice president of marketing at Ricoh, reported for Forbes on the significance of data management for better marketing intuition. While big data initiatives may seem overwhelming to some firms, resulting insights have the potential to enhance insight for more predictive instincts that fuel success. Zoratti explained that big data requires not only adequate analytic solutions for mining high volumes of structured and unstructured data, but also the ability to act on those insights for measurable results.

Value comes from application
Rapid Racking, a manufacturing company for shelving and racking products, is one example Zoratti cited of a company that benefited from applying these analytics. Using software that efficiently processed customer data, the firm was able to create an algorithm to make predictions regarding potential prospects and deliver customized product catalogs based on those analytics. As a result, the company was able to simultaneously increase revenue by 8 percent and decrease acquisition costs by 47 percent. Zoratti also reported that Capital One runs almost 80,000 tests annually and mines results for opportunities to maximize ROI. 

Successful big data strategies start with efficient collection and analysis of information, and are driven by analysis and application. By defining specific goals for big data mining, enterprises can draw more meaning and actionable analysis that demonstrates tangible positive impact.

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