| Big Data is a problem for many organizations in many different industries because current data processing technologies do not provide the capabilities to process Big Data effectively. This Delphi Study addresses how organizations prepare and clean Big Data for better governance by helping organizations extract information more efficiently from Big Data and provide better value for the organizations' bottom line. A traditional Delphi study is used to discover what data governance experiences do IT managers tasked with Big Data encounter when preparing Big Data for cleaning and analysis, and to identify a set of standard techniques or best practices for Big Data managers for the preparation and cleaning of Big Data. This researcher found that the main reason to prepare and clean Big Data was to decrease regulatory, technical, and value risk for the organization and provide for higher profits. The preparation and cleaning of Big Data would allow organizations to analyze Big Data to provide better decisions to ensure the future viability of the organization. The Delphi participants helped to begin the formulation of a set of best practices for the preparation and cleaning of Big Data. In future research, the BD equation developed for this research, BD = SBD + MBD + UBD, should be applied to every industry, and specific data formats should be studied and scripts should be provided to prepare and clean Big Data. |
