- Check Data Sources
- Check Data Formats
- Check Data Relationships
- Check Data Transformations
- Check Data Outputs
- Check Data Feedback
- Here’s What Else To Consider
1. Check Data Sources
One of the first steps to ensure data quality is to check the sources of the data that feed into the ERP system. Data sources can include internal databases, external systems, manual inputs, or third-party providers. You should verify that the data sources are reliable, secure, and up to date, and that they follow the same standards and formats as the ERP system. You should also identify and eliminate any duplicate, redundant, or irrelevant data sources that may affect the quality of the ERP data.
2. Check Data Formats
Another important data quality check is to check the formats of the data that are stored and processed by the ERP system. Data formats can include numeric, text, date, time, currency, or other types of data. You should ensure that the data formats are consistent, accurate, and compatible with the ERP system and the reporting tools. You should also check for any missing, invalid, or incorrect data values that may cause errors or distortions in the ERP reports.
3. Check Data Relationships
A third data quality check is to check the relationships between the data elements that are used for ERP reporting. Data relationships can include hierarchies, dependencies, associations, or calculations. You should ensure that the data relationships are logical, coherent, and aligned with the business rules and objectives. You should also check for any broken, inconsistent, or circular data relationships that may affect the integrity and validity of the ERP data.
4. Check Data Transformations
A fourth data quality check is to check the transformations that are applied to the data during the ERP reporting process. Data transformations can include filtering, sorting, grouping, aggregating, or summarizing the data. You should ensure that the data transformations are appropriate, accurate, and transparent, and that they do not alter or lose any essential information from the original data. You should also check for any errors, anomalies, or outliers that may result from the data transformations.
5. Check Data Outputs
A fifth data quality check is to check the outputs of the ERP reporting process. Data outputs can include tables, charts, graphs, dashboards, or other forms of data visualization and presentation. You should ensure that the data outputs are clear, concise, and relevant, and that they convey the intended message and insights to the target audience. You should also check for any discrepancies, inaccuracies, or ambiguities that may confuse or mislead the users of the ERP reports.
6. Check Data Feedback
A sixth and final data quality check is to check the feedback that is received from the users of the ERP reports. Data feedback can include comments, questions, suggestions, or complaints that indicate the level of satisfaction, understanding, and usefulness of the ERP reports. You should ensure that the data feedback is collected, analyzed, and acted upon, and that it leads to continuous improvement and enhancement of the ERP data quality and reporting process.
7. Here’s What Else To Consider
This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?
