Book Image

Practical Data Quality

By : Robert Hawker
Book Image

Practical Data Quality

By: Robert Hawker

Overview of this book

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.
Table of Contents (16 chapters)
Part 1 – Getting Started
Part 2 – Understanding and Monitoring the Data That Matters
Part 3 – Improving Data Quality for the Long Term

Governing remediation activities

Once the prioritization is complete, the approach has been identified, and the effort involved has been understood, the remediation activities begin. Just as with any other project-style activity, remediation must be governed.

Governance in this instance means the following:

  • Tracking the remediation activities against the expected effort/elapsed time
  • Reporting to senior leaders on the progress of the activity
  • Understanding risks, issues, and “blockers” that need to be managed or mitigated
  • Ensuring that when the project activity is done, ongoing work is transitioned into a business-as-usual process

When organizations start to remediate data quality issues for the first time, it has to be managed quite formally. This is simply because the organization has no established processes, best practices, and institutional knowledge in this area. Some organizations that I have worked with have decided to simply assign...