How can data errors be reduced in a business?
Efficiency question :
Data-integrity problems are a real issue for organizations. Errors can arise during data entry, while information is being processed or when reports are produced.
Reducing these errors requires controls at different stages of data processing. The objective is to prevent errors, detect them when they occur and verify the integrity of the results produced.
Several methods can be used, but they must be adapted to the way data flows through the organization.
Key considerations:
Every organization has its own processes and data-processing methods, so sources of error can differ significantly from one company to another.
Data may be entered manually, come from a form, be retrieved from a system or be extracted from an email before being transformed and recorded.
There is therefore no single method that eliminates every error. Controls must be adapted to the organization’s different data sources and processes.
Challenges:
The first challenge is to establish a sound diagnosis.
Before developing controls, understand how data is entered, how it moves through the organization and which steps are likely to generate errors.
A clear understanding of data flows helps identify where controls will be most effective and supports a plan before error-management processes are automated.
Technology:
Several Microsoft technologies can be used to improve data integrity.
Excel provides functions for managing or detecting certain errors. Power Query can retrieve, transform and control data from different sources.
Power Apps can create applications and forms that better control data entry, while Power BI can support analysis and help identify results requiring attention.
The choice of technology therefore depends mainly on where errors occur and which process needs to be controlled.
Developer's advice:
A first method is to control data at the point of entry. Whether it comes from a form, an email or another source, important information should be controlled as early as possible.
Customer lists, product lists, dates and other entry parameters should also be used as references when reports are created. Using the same parameters or calculation constants at different stages helps maintain greater data consistency.
A second method is to create a control report. It compares downloaded, entered or stored data with the results produced in reports.
Detailed reports may use different conditions to segment data. A control report can use calculations with fewer conditions to verify overall results. Comparing these calculations helps confirm that the various segments, once combined, match the source data.
A third method is to program systematic validation before data is saved. Dialog boxes can alert users when information is missing or incorrect, and the program can verify that all required fields are complete before allowing the record to be saved.
The objective is to move as many controls as possible to the beginning of the process rather than discovering errors only when reports are produced.