Data Quality Issue Log

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

  • Date: [Date]

  • Prepared by: [Your Name]

  • A detailed record of data quality issues, capturing all relevant information to facilitate effective management and resolution.

Identification Date

Issue Description

Affected Data Sets

Severity Level

Resolution Actions

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Outdated data in inventory system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

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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