Data is behind every decision we make. But if we’re going to make decisions about our businesses based on our data, we have to be able to trust that this data is accurate, reliable and trustworthy. How do we do this? By making sure we maintain proper data integrity practices. However, as data volumes continue to increase exponentially, maintaining data integrity becomes more difficult.
Data integrity involves making sure that your people, processes, and technology are all working together to ensure that your data is complete, reliable, searchable, and traceable. When proper data integrity practices are in place, you can be confident that your employees are making decisions based on good data.
What is Data Integrity?
Data integrity can be described as the completeness, accuracy, consistency, and compliance of the data within your systems. Data integrity is a state that we aim to achieve as well as the processes that we use to achieve it.
Data integrity covers several areas:
Physical integrity: Data is stored on a safe, reliable physical platform.
Logical integrity: Data is accurate and correct, and unchanged, even if it is used in different contexts in a relational database.
Compliance: Data meets necessary compliance standards, such as the standards for GDPR.
Why is data integrity important?
Performance: Minimizing or removing incomplete records and eliminating duplicate records can help improve database performance.
Reliability: You need to know that the data your employees are using to make business decisions is reliable. Data integrity processes can help ensure that your data is as reliable as possible.
Access: Your employees need access to data to do their jobs. When you know that the hardware and software supporting your data is reliable, you know that your employees will be able to access the data they need when they need it.
Reputation: While data integrity is not exactly the same as data security, you can’t have data integrity if you have a data leak or data theft. Your company’s reputation can be damaged if you have issues with data security.
How Do You Maintain Data Integrity?
Maintaining proper data integrity involves making sure that the people, processes, and technology in your organization are all working in support of your goals.
User error is a common problem that can impact data integrity. Therefore, looking at your people and how they interact with data can help improve data integrity.
Train your users on how to enter and maintain data. Training helps keep employees invested in data integrity.
Appoint a data steward
Who is ultimately responsible for data integrity? This isn’t always apparent. That’s why many organizations are now creating the role of data steward. A data steward is responsible for the management and oversight of an organization’s data or a specific set of data. In addition to helping with data integrity, the data steward can help make sure that the data is high quality and that users can access it when they need to.
Data isn’t a static entity. It’s constantly being updated, getting moved, being cleansed and then becoming messy again. Regularly implementing the following processes can help support data integrity.
Build in Validation
Add validation processes into your databases to minimize the chance that data is entered incorrectly. For example, using field types ensures that the data is a number if it’s supposed to be a number, and letters if it’s supposed to be letters. Using drop-down lists or multiple choice for fields also ensures that the information entered is free from errors.
Rely on Testing
Make sure to put proper testing processes in place to confirm data integrity. Testing is particularly important after transferring data from one location to another. Using commercial ETL software can also be helpful for ensuring that your data transfers are completed without damaging data integrity.
The technology we use to store, access and maintain our data plays an important role in data integrity.
Cleanse your data
Make sure to perform data cleansing and data maintenance processes regularly. An ETL application can be helpful here. The transform step can be used to detect and remove or repair invalid, duplicate, or inconsistent data. As data volumes increase and there are increasing types of data within our organizations, the data cleansing process is essential for making sure that employees are using clean, accurate data for their analysis and decision making.
Keep antiviral software up to date
Viruses can impact your data integrity. If you are hosting your own databases, make sure to keep the antiviral software on your servers up to date. If you are storing your data in the cloud, take advantage of the antiviral services offered by your cloud provider.
While data security and data integrity are not synonymous, you can’t have data integrity if your data is not secure. If you are maintaining your own servers, it’s important to have proper security measures in place. Similarly, if your data is in the cloud, review the security practices of your cloud provider.
Want to Learn More About Data Integrity?
Matillion ETL can help your organization maintain data integrity with a number of features, including:
- Automation of data tasks to prevent manual errors
- Self-validation of pipelines and jobs
- Support for Git and Change Data Capture
- Error handling and data lineage
Matillion Data Loader is a free SaaS product for getting your data into the cloud without the need for coding or other manual intervention.