Everything You Need To Know About Data Quality Management

Everything You Need To Know About Data Quality Management

Data is already the lifeblood of modern business.

Yet, with organisations collecting and processing more data than ever before, managing the quality of this data has become no less than indispensable. 

Data quality is a measure of the health of the data coursing through your business. It is neither good nor bad, high nor low. Rather it is a range, a gauging of the risks and issues surrounding data – wherever they may lie.

This is where data quality management comes in. Data quality management provides a context-specific process for improving the fitness of data that is used for analysis and decision making. The aim of it is to create insights into the health of a given data set, using several processes and technologies.

Why Do We Need Data Quality Management?

Bottom line: data quality management helps you make sense of your data. It is, in a word, essential.

These are the three reasons why.

Firstly, good data is the foundation for good business initiatives. Without accurate, reliable data your business will surely make mistakes.

Secondly, up-to-date data will give you a clear understanding of how your company is operating. Poor quality data will lead to costly oversights and missteps in the day-to-day running of your business, much like losing track of your orders or spending.

And finally: data quality management is necessary to meet compliance and risk obligations. Alongside solid underlying data, good data governance requires clear procedures and communication. For example, a data governance committee may define what is acceptable for data health. But how do you define it? How do you monitor such policies? Enter data quality management.

Data Quality In An Era Of Big Data

Big data will continue to disrupt businesses. Fact.

Just think of the massive volumes of streaming data that will ensue with the Internet of Things. Or the innumerable shipment tracking points that are already flooding into businesses, which need to be combed through for analysis. And this is just the start.

Faced with these challenges – plus many, many more – data quality management will become more important than ever. After all, with all that big data, comes bigger data quality management problems.

Want to learn more? This is where you’ll learn everything you need to know about data quality management.

Share this post