Data Quality: Enhance data quality and management practices
System: Data Management
Actor: Data Analyst, Data Engineer, Data Architect
Scenario:
The Data Engineer wants to automate the process of data tagging and onboarding new data to reduce data duplication and improve data quality.
The Data Engineer develops scripts or workflows to automatically tag new data based on predefined rules and standards.
Additionally, the Data Engineer sets up an automated onboarding process to efficiently bring in new data, ensuring proper validation and integration with existing datasets.
By automating data tagging and onboarding, the company can reduce manual effort, minimize data duplication, and enhance data quality.
Use Case
Use Case Name: Automate Data Tagging and Onboarding for Data Duplication Reduction
Primary Actor: Data Engineer
Goal: To automate the process of data tagging and onboarding new data to reduce data duplication and improve data quality.
Pre-conditions: Data tagging and onboarding processes are manual and prone to errors.
Post-conditions: Data duplication is reduced, and new data is tagged and onboarded efficiently, reducing manual effort and improving data quality.
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