The use of data has become pervasive in recent times, mainly due to the increase in technological advancement in the business world. The truth, however, is that while several businesses have understood the need to collect data from customers and other stakeholders, they haven’t fully grasped the best ways to make this data work for them. This leads to many data quality problems that translate into other aspects of the organization. Continue reading for tips to ensure data quality.
Ensure data consistency.
If you’re wondering how to ensure data quality within your organization, your first step should be to control the data you collect in the first place. The data you end up working with comes from varying sources, be it different departments or different companies. With this in mind, you should know that not all data you receive will be of good quality. To improve the quality you receive, you’ll need to rigorously control the varying data streams with help from a well-designed data profiling tool.
These tools are specially designed to cater to data consistency, checking the completeness of collected data, the data patterns and formats, and data abnormalities and distributions. The best part about these tools is that they come with automation features, which means you can automate the profiling process and receive real-time alerts on all incoming data and their quality levels and what needs to be changed.
Create option sets and highlight key data entries.
As much as possible, never leave it to the business user to place values into a text box, especially for fields that require a defined set of values. Take “country of origin,” for example. A country like the United States of America can be written as the U.S., the USA, and even America. To avoid all thousand variants, offer the user clear options to choose from to make your data analysis process easier.
Also, it would be best if you worked with time when collecting data from a customer. For organizations that need this high-quality data for relevant transactions, be sure to determine the necessary data and ask for just that. Highlight all relevant entries as mandatory to prevent some users from spending a chunk of their time putting in extraneous data you won’t use.
Enforce data integrity.
Various techniques enable business owners and personnel to properly enforce data integrity. Some of these techniques include check constraints, foreign keys, and triggers. The volume isn’t that high; thus, all your datasets can be stored on a single database system. As your organization grows, it demands more data, and the huge volumes require that you consider other systems and applications for proper storage and data quality management.
In comes the use of integration tools. Integration tools are systems that allow you to streamline all data coming in from multiple systems within your organization. These systems can be automated to enable record creation, where data existing in one system can be transferred to another system when needed without having to be re-keyed manually. The automation process helps speed up your work processes, which ultimately allows for information continuity across all departments in your organization.
Training your staff.
You might be a fully technological firm, but there are aspects of your business handled by real people. These people need to know about all your company’s processes and procedures when collecting and processing data. It’s key to take them through in-depth education sessions, where they are taught to appreciate the benefits of high data quality to them, their department, and the business at large. Scheduled quality reviews and consistent feedback should follow data training sessions.
All in all, when managing data quality, it’s better to start at the basics. Try to understand what affects the quality of data you collect or analyze, and how you and every other department in the business can help fix that.