How can we resolve the problem? Easy: use these 5 steps to achieve lasting high data quality.
Step 1: Become Aware of the Problem
Recognize how important high data quality is, which problems can result from poor data quality, and how these problems affect us all. Inform and train those who work with you about this issue.
Step 2: Define Criteria for Quality
Assemble your experts to determine what your key performance figures are and which rules to apply to test their accuracy and plausibility.
Consider which entities and attributes are used in your critical processes. For each entity, you should find out exactly which rules and criteria are necessary for the process to function efficiently and without errors. Consider also what determines whether a data set is of insufficient quality.
Step 3: Analyze Data Quality
Despite increasing digitalization in all branches and processes of enterprise, error and manipulation rates remain high. This makes data analysis more important than ever. You need to have oversight of your data.
With help from BiG EVAL, you can check your data automatically or with the push of a button. BiG EVAL will alert you to errors, so that you can react in time before greater damage is done. Analyze the test results in the dashboard and continue to Step 4.
Step 4: Define Methods for Dealing with Flawed Data
How will you handle flawed data? Consider your options and make a plan. Follow this plan strictly in order to clean up your data as quickly as possible.
Step 5: Test Data Quality Continuously
Don’t forget that data is generated constantly, which naturally increases the risk of errors. Test your data quality continuously and automatically. Feel good about your data. Regain trust in your KPI’s and reports. Your data quality is now guaranteed.