Data quality management is the practice of maintaining a high quality of information within an organization. Across many different industries, such as healthcare, financial firms and higher education institutions, data is used to make important decisions every day. In today’s world, organizations are collecting more data than ever before., which increases the importance of managing the quality of that data.
There are regular headlines in the news relating to incidents such as data breaches, fines for non-compliance, identity theft and fraud. With good data quality management, the frequency of these incidents can be reduced or even prevented. To find out more about data quality management, ids take a more in-depth look into why it is so important.
What does data quality management mean?
Data quality is a range or measure of the condition of the data within your business or organization. By managing this data effectively, you have the chance to improve the condition and the value of the data.
When it comes to data that affects decision making and analysis, having a clear understanding of what’s in front of you can be achieved through effective data management. Essentially, it can help you make sense of your data and create a data set that you can use to reach your business goals.
Why is it important?
The practice of data quality management can make a huge difference to your business in a number of ways. Without it, you could be left with unreliable, incomplete, duplicated or outdated data.
In particular, outdated or unreliable data can be very costly for your business. By having accurate data, you can obtain a much clearer picture of your business’ systems and applications. Good data management can provide the useful insights you need to better understand the condition of your business’ operations.
It is also required in order to meet compliance and any risk objectives, preventing incidents that may jeopardize your business in any way. Effective management will also ensure that all data is optimized for its intended use.
Finding the right data quality management tools
It can be achieved through the right suite of tools, offering test data management and quality assurance. These tools can provide robust, comprehensive capabilities, with the ability to cleanse and organize your data. This gives you a better understanding of your data and allows you to ascertain its integrity.
What’s more, by investing in the right management tools, you are able to generate synthetic data or obfuscate data, in order to support testing practices. The right tools can also help you to validate email addresses for marketing and sales purposes.
Data quality management tools are there to ensure you can carry out the right practices, starting with data cleansing. This can correct duplications, nonstandard inputs or outdated data, leaving you only with useable and up-to-date information. What’s more, the right tools can assist with data profiling, to determine the accuracy, completeness and validity of your data and in turn expose any inconsistencies.
Data reporting and monitoring are also crucial tasks within data quality management. Both of these functions can offer better visibility into the condition of your data at times when it’s needed most.
