Poor data quality can lead to increased costs, hinder revenue growth, compromise decision-making, and introduce risk into organizations. This leads to employees, customers, and suppliers finding every interaction with the organization frustrating.
Practical Data Quality provides a comprehensive view of managing data quality within your organization, covering everything from business cases through to embedding improvements that you make to the organization permanently. Each chapter explains a key element of data quality management, from linking strategy and data together to profiling and designing business rules which reveal bad data. The book outlines a suite of tried-and-tested reports that highlight bad data and allow you to develop a plan to make corrections. Throughout the book, you’ll work with real-world examples and utilize re-usable templates to accelerate your initiatives.
By the end of this book, you’ll have gained a clear understanding of every stage of a data quality initiative and be able to drive tangible results for your organization at pace.
Explore data quality and see how it fits within a data management programme
Differentiate your organization from its peers through data quality improvement
Create a business case and get support for your data quality initiative
Find out how business strategy can be linked to processes, analytics, and data to derive only the most important data quality rules
Monitor data through engaging, business-friendly data quality dashboards
Integrate data quality into everyday business activities to help achieve goals
Avoid common mistakes when implementing data quality practices