Governmental business intelligence due for transformation

New data sources and analytical methods have led to a renaissance of sorts in business intelligence processes. The effects of big data and the technology that makes unstructured information usable have been felt in the public sector as well as in enterprise settings. According to a recent report by the TechAmerica Foundation, governmental agencies may be closer than they think to big data transformation, with existing systems providing the framework for the move.

Improvement possible soon
The TechAmerica research found two important factors converging at government agencies. Big data is becoming widely available for use just as the technology to harness it becomes affordable. The source suggested that organizations in a number of different fields will be able to transform their core processes through more accurate data analysis. For example, healthcare providers, educational organizations and scientific research entities all have unique and powerful ways to grow via previously incomprehensible data.

One of the first steps to making use of a new resource is defining it. The definition of big data has been a point of contention in the IT industry as a variety of companies have hurried competing big data products to the market. According to the TechAmerica report, however, big data is large in volume, as well as "high velocity, complex and variable." The source noted that it cannot be captured or harnessed with standard analytics tools and requires specialized processes.

The unique data management software companies and government departments crave, however, may be easy to acquire and deploy. TechAmerica noted that organizations do not need to start fresh when adding big data, as they can likely build upon their previous innovations in the data management field. Employee skills are one area companies may need to adapt to become big data experts. The source suggested using key worker insights to identify each agency's specific needs for the programs.

Two kinds of data
The next step in data usage and management could involve acknowledging the difference between structured information and the new, unpredictable insight sources that have appeared. Information Management contributor Jim Harris explained that IT leaders may have to shelve their assumptions about data management and analytics best practices when dealing with new inputs.

Harris maintained that firms have codified certain approaches to data quality and storage over the past few years. These may have to fade in the face of new information sources. In losing them, however, organizations could gain vital improvements to performance.

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