12 Guidelines for Success in Data Quality Projects

Most organizations recognize that the quality of their data is not always at the level they would like it to be. Diverse data sources, multiple touch points across several departments, and a varying integrity at data entry introduce a host of quality issues including misspellings, incorrect formatting, misplaced fields, and more. The solution is implementing a data quality program.

A data quality program provides consistent, accurate, and reliable information for decision-making, reporting, and day-to-day operations. To be successful, a data quality program must include standards, policies, processes, and education to ensure that everyone involved understands and supports the initiative, and a data quality tool that can parse, standardize, and cleanse data to be used across the entire enterprise.

Learn the key characteristics of successful data quality initiatives and get actionable guidelines to help make your data quality project a success, from conception, to implementation, and on to tracking your positive ROI.