5 Best Ways to Build a Business Case for High-Quality Data

Many organizations consider themselves “data driven.” This is understandable: they believe they make decisions based on objective metrics rather than instinct or historical bias. But no organization can be successfully data-driven when making decisions using faulty data.

Data may be defective in many ways. Sometimes, the data is incomplete (the entire record or a field within the record is missing). Sometimes the data is misleading or inaccurate. Sometimes the rules (for naming conventions or abbreviations, for example) aren’t followed consistently. Metadata may be missing or inaccessible. Sometimes the data on-premises is duplicated in a cloud repository, creating uncertainty about which record to use.

As organizations modernize legacy systems in favor of cloud applications, it becomes more complex. And it becomes particularly acute if the organization does not address data quality.