Big Data, the next frontier in IT, allows organizations to change how they analyze information to boldly go where no business has gone before. Thanks to technology advances, we live in a world where a vast amount of data is discovered, developed and shared every day and with current projections on IT spend, Big Data is only getting bigger. While Big Data is most commonly associated with size, we actually evaluate data along three dimensions: Volume, Variety, and Velocity.
These three components add to the difficulty of storing, measuring and processing data. A successful data management policy will help organizations overcome these challenges by addressing four key areas: 2/3 of IT leaders claim their data is stored in disparate systems that cannot communicate with each other. These organizations must evaluate their current structure and build new platforms, aligning any infrastructure needs with business objectives. Software is not the only element that needs to be able to communicate.
Data Management Policies
Big Data projects require collaboration and cross-team input to build a workable solution. Data management policies define guidelines for interaction, assigning ownership of data sets. Only accurate data will yield useable insight. Yet more than 1/2 of IT leaders and IT professionals say their organizations lack accountability to ensure data quality. Reporting and record-keeping may require special training, and teams may need to build additional time into the workflow process to accommodate for extra quality control.
To properly plan and execute Big Data projects, organizations require a uniquely specialized staff with diverse skills including business analysis, project management, statistics, data mining and collaboration. By partnering with an experienced staffing and training provider, organizations can secure and optimize the right talent. To capitalize on the infinite possibilities of the Big Data universe, organizations must develop a data management policy that can live long and prosper.