When it comes to the data that your company collects and stores, quality is always going to be necessary. After all, if the data is inaccurate or incomplete, it can lead to many problems down the road. That’s why ensuring your information is as high-quality as possible is essential.
Fortunately, there are a few things that you can do to help improve the quality of your data, such as following routine quality checks and using a modern data platform to collect and store your data.
What Is Quality Data?
Quality data is data that is accurate, complete, and timely. Data quality is vital to a business because it can impact customer satisfaction and company revenue.
Let’s say your company manufactures athletic socks. You receive an order for 200 pairs of socks from a retailer. You ship the socks, but the retailer later discovers they are not the correct size. The retailer then issues a refund, and you must pay for the return shipping. This scenario exemplifies how poor data quality can cost the business money. Not only has money been lost, but the manufacturer risks its business relationship with the retailer.
Now that we know how vital quality data is, let’s look at ways to ensure your data is of the highest quality.
1. Understand the Different Types of Data Quality
There are several different types of data quality, each of which can impact your business differently. For example, accuracy is one type of data quality that refers to how accurate or precise your data is. Accuracy is essential because if your information is inaccurate, it can lead to incorrect decisions being made.
Completeness is another type of data quality that refers to whether or not all the data you need is present. If some of your data is missing, your reports and analysis will not reflect the complete picture, leading to wrong decisions.
Timeliness is another type of data quality that refers to how up-to-date your data is. Having timely data to make decisions based on the most current information is crucial. For example, if you’re trying to decide whether or not to launch a new product, you’ll need to have the most up-to-date data on your sales, inventory, and customer trends.
2. Implement Quality Checks
There are several ways to implement quality checks into your data collection and storage processes. One way is to use data validation rules. Data validation rules are criteria that data must meet to be considered valid. For example, a data validation rule for an email address might stipulate that the data must contain an “@” symbol.
Another way to implement quality checks is to use data cleansing tools. Data cleansing tools are used to identify and fix errors in your data. For example, if you have a customer list with duplicate entries, a data cleansing tool can help you remove the duplicates.
Finally, you can also use data sampling to quality-check your data. Data sampling is selecting a representative sample of data from a larger dataset to test its quality. Sampling can identify errors, such as inaccurate, missing, or incorrect data.
3. Use A Data Platform
Using a modern data platform can also help improve the quality of your data. A data platform is a cloud-based system that enables you to collect, store, and manage your data. It includes features like data cleansing and data validation to help ensure your data is of the highest quality.
In addition, a modern data platform can help you keep your data organized and accessible. It can also help you track changes to your data over time and see who made those changes. This is important because it can help you quickly identify and correct errors.
4. Follow Data Standards
There are several data standards that you can follow to help ensure the quality of your data. Data standards are rules and guidelines that dictate how data should be collected, stored, and managed. Following these standards can help improve your data’s accuracy, completeness, and timeliness.
One data standard is ISO 27001. These security guidelines include risk management requirements, data backup and recovery, and data destruction.
Another data standard is the GDPR. The GDPR is a set of regulations governing personal data collection and use. It includes requirements for obtaining consent, ensuring data accuracy, and protecting data from unauthorized access.
5. Hire A Data Quality Specialist
To ensure the highest possible quality for your data, you may want to hire a data quality specialist. Data quality specialists are responsible for assessing data quality and developing plans to improve it. They have expertise in areas like data cleansing, data validation, and data management.
A data quality specialist can help you develop and implement processes to ensure the quality of your data. They can also help you assess the impact of changes to your data, such as new software or hardware upgrades.
Concluding thoughts…
Data quality is vital for any organization that relies on data to make decisions. By following these tips, you can improve the quality of your data and make sure that it is accurate, complete, and timely. Implementing quality checks, using a data platform, following data standards, and hiring a data quality specialist are all great ways to improve the quality of your data.
