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

Introduction to data quality reporting

Data quality reporting should provide an entire hierarchy of reporting – from a high-level summary, down to the individual rows of failed data. These different levels of reporting are aimed at different stakeholders of varied seniority.

This is to cover the diverse requirements of different users of the reporting. For example, a list of failed records is very useful for an operational person who has been asked to make corrections, but would not serve a Chief Data Officer very well. A level of aggregation is required for a senior stakeholder so that they can see an overall picture of the data in the area(s) that they are responsible for.

This section will outline the types of reporting required, who they are aimed at, and how they might look.

Different levels of reporting

In my experience, there are three main levels of reporting required in a data quality initiative. These are mentioned in the following table: