Getting Data Quality Right - Success Stories

Good data is like good water: best served fresh, and ideally well-filtered. Data management strategies can produce tremendous procedural improvements and increased profit margins across the board, but only if the data being managed is “of sufficient quality.” This program provides a useful framework guiding for those approaching data quality challenges. In specific, data quality must be approached as an engineering discipline. Data quality engineering must be approach as a specific ROI-based discipline or it cannot effectively support business strategy. Better understanding of how to do ‘data quality right’ allows for speedy identification of business problems, delineation between structural and practice-oriented defects in data management, and proactive prevention of future issues. Program learning objectives include:
•  Vivid demonstrations of how chronic business challenges
    for organizations are often rooted in broader kinds of data
    quality that suggested treatments can address
•  Helping you to understand foundational data quality
   concepts, guiding principles, best practices, and an
   improved approach data quality at your organization
•  The basis of a number specific case studies illustrating
    the hallmarks and benefits of data quality success