Data Quality Issue Log
This log is designed to document and manage data quality issues systematically. It includes comprehensive details such as issue descriptions, affected data sets, identification dates, severity levels, resolution actions, and status updates. The objective is to maintain high data integrity and support prompt and effective resolution of data quality issues to ensure reliable and accurate data across all systems.
Log Overview
Identification Date | Issue Description | Affected Data Sets | Severity Level | Resolution Actions |
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2050-07-01 | Duplicate records in customer database | Customer Information | High | Merge duplicates and clean data |
2050-07-02 | Missing fields in sales reports | Sales Data | Medium | Update data entry forms and retrain staff |
2050-07-03 | Incorrect data formats in transaction logs | Transaction Records | High | Correct formats and update system validation rules |
2050-07-04 | Outdated data in inventory system | Inventory Records | Medium | Refresh data and verify with suppliers |
2050-07-05 | Data inconsistency in user profiles | User Profiles | High | Perform data reconciliation and standardize profiles |
2050-07-06 | Missing data in financial reports | Financial Records | High | Retrieve missing data from source and update reports |
2050-07-07 | Incorrect calculations in KPI dashboards | KPI Dashboards | High | Review formulas and correct calculations |
2050-07-08 | Data entry errors in marketing database | Marketing Data | Medium | Implement data validation checks and re-enter corrected data |
2050-07-09 | Data integration issues between systems | Integrated Data Sets | High | Address integration points and synchronize data |
2050-07-10 | Inconsistent data tags in datasets | Various Datasets | Medium | Standardize data tagging and update documentation |
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Notes:
Regularly update the log to maintain an accurate record of all data quality issues.
Use the Severity Level to prioritize resolution actions.
Review the log periodically to track progress and ensure timely resolution of data quality issues.
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