The terms “data hygiene” and “data quality” are both well-known and oft used in Big Data circles, but how interchangeable are they? What is the difference between hygiene and quality as applied to stored information? Understanding the language of data maintenance is essential for ensuring your company’s most valuable asset — your business data — is accurate, reliable, and complete.
Data hygiene
Data hygiene refers to the disparate steps your company employs to keep data accurate and up to date. This is typically accomplished through a collection of rigid processes for standardizing data sets, removing unnecessary or outdated data, and organizing it for use throughout your business. While data hygiene can help to optimize productivity and informed decision-making, it can easily go wrong — with disastrous results up to and including the loss of critical data. Data hygiene processes must be done with careful attention to best practices.
Despite the potential risks, data hygiene can be helpful for avoiding redundancy, improving data accuracy, and updating data sets. But it’s only a subset of data quality management for accurate — and useful — data. Data hygiene is a good start, but where do you go from there?
Data quality solutions
Gartner defines data quality solutions as “the processes and technologies for identifying, understanding and correcting flaws in data that support effective data and analytics governance across operational business processes and decision making.” Data quality solutions are complete, end-to-end, customized processes for solving a variety of data problems in one go. Ensuring data quality is more comprehensive than simply cleaning up redundant data and keeping what you need updated. Data quality solutions encompass the full range of data management processes in one neat package from one vendor partner.
Instead of using different, laborious processes for solving data problems, these solutions are customized to fix quality issues and ensure ongoing data accuracy and consistency. Custom solutions are based on data sources, industry priorities, and individual company goals, and their interconnectivity allows you to unify information across different teams and divisions of your business to ensure decision-makers at every level are working from the same — accurate and reliable — data. Data quality solutions simplify day-to-day processing and the business operations that incorporate data.
Why it matters
Data hygiene is a subset of data quality, but pursuing it without considering the potential consequences of disparate processes invites problems. Disparate processes can miss data issues — and even create a few new ones. Redundant processes waste time and money and frequently fall short of your intended goals — not to mention the problems that can arise from a lack of proper management.
Data quality solutions cover more than data hygiene. They are complete solutions to your company’s data challenges, and they continue to safeguard your data against new issues that arise over time. This comprehensive approach to data management improves your valuable data and establishes a custom framework for ongoing, consistent, and efficient processing.
In short, data hygiene processes are only a part of improving your data. They are useful on their own when managed carefully, but data quality solutions improve data — quickly and efficiently — for better business decision-making. For a comprehensive answer to your company’s data challenges, data quality solutions beat standalone data hygiene techniques every time.
Contact the data experts at Xcelerated Data today to talk about data quality solutions for your business, or sign up to take the database challenge for free. We will find problems in your data you didn’t even know existed.