A data quality checklist is often used by companies that want to utilize a tool that will locate and fix any errors related to data entry. The everyday nature of dealing with data, including entering the data, reviewing the data and signing off on the data can leave the potential for lots of errors. These errors can also be overlooked during data review, therefore managing data quality is required. With data being used in so many industries for so many reasons, it is critical that the number of errors is limited. A data quality checklist template is an effective tool for every data quality manager, a tool that will help to reduce the number of mistakes and errors that occur.
Data Quality Checklist Template
Basic Data Checks
This part of the template should include the tasks that are performed every time the data is reviewed. Some of the tasks that should be considered are:
- Verify formatting is correct
- Confirm the data is what is expected
- Compare data to previous values to spot change is information where change is not expected
- Identify values that are not valid
- Perform random spot checks
Once basic data checks have been completed, advanced data checks should take place.
Advanced Data Checks
Advanced data checks include the review and submission process, it should be completed when data is reviewed for submission and/or approval. Tasks that should be completed during this part of the data quality checklist template include:
- Accuracy – data should reflect reality
- Confirm that all red flags and errors were identified, fixed before data is submitted or approved
- Confirm that information on reports are the same as the original documents
- Determine if the information was recorded by someone with direct knowledge
Once all of the tasks have been completed, there are several more steps that must be completed before the data can be submitted or approved. The data must be checked to ensure that all of the records required are there. Any blank entries in the data should be intentional and not omissions of information.
All fields with text should include complete information and not abbreviations or nicknames. For example, if a person’s name is “David”, it should not be shortened to “Dave” in the text field.
There should also be an inquiry as to whether any hard copies of additional data have been submitted since the report was completed. If so, the additional information will have to be entered correctly.
It is also important to ensure the information is unique. Alphabetical sorting may be necessary to spot duplicate entries. There should also be a check to compare the current information to last year’s or last quarter’s information.
The data checklist should also include the timeliness of the data reported. The timestamp should be checked to confirm the version of data received is the most current.
Finally, the data should be checked for consistency. The information that is being reviewed and submitted should be the same in all of the departments within the organization.
A data quality checklist template is critical in making sure an organization’s data is entered and submitted properly and that the data quality objectives are reached. This will help to improve efficiency and maintain good customer relations.
In need of data quality solution? RingLead Data Management Solutions (DMS) is your one stop platform to solve all of your data quality needs. In minutes, RingLead can capture, clean, protect and enrich all of the data in your Salesforce org, leading to increased organizational efficiency, reliable business intelligence and maximized ROI on CRM and marketing automation investments. RingLead is the only cloud-based, fully scalable data management solution that will help your team reach peak performance, with minimal effort.
Watch DMS in action today by clicking the box below to schedule a demo today!