Balancing Self-Service with Enterprise Requirements 

Data is an essential component of every aspect of business, and organizations that use it well are likely to gain advantages over competitors that do not. A variety of needs drive organizations to deploy information derived from this data; the most common are to support analytics and decision-making, enable effective process improvements and optimize the customer experience.

To accomplish these purposes requires that data be prepared for use. This typically involves a sequence of steps: accessing the data, perhaps through search; aggregating it; and enriching, transforming and cleaning data from different sources to cre¬ate a single uniform data set. To do this job of data preparation properly, businesses need flex¬ible tools that enable them to enrich the context of data drawn from multiple sources, collaborate on its preparation and govern the process of preparation to ensure security and consistency. Users of these tools range from analysts to operations professionals in the lines of business to IT professionals.

This benchmark research examined existing and planned approaches to data reparation as well as related technologies, best practices for implementing them and market trends in this area. The research investigates how organizations are implementing data preparation tools to support operational and business intelligence processes. In particular, it investigates current levels of understanding of data preparation requirements, reasons for adopting data preparation technologies and barriers to adoption.