Guidance on how to automate and scale data discovery and data identification tasks in Cloud Data Catalog (CDGC). Review how to use profiling results, filter and drill into details, review profiling trends.
- Basic knowledge of Cloud Data Profiling functions
- Refer to DGP-002: Getting Started & Deploy CDGC, CDQ and CDMP
This engagement provides advisory services only, offering guidance without direct implementation or technical troubleshooting. For technical issues with product, please reach out to Global Customer Support. For assistance with implementation, you may want to consider Informatica Professional Services.
- Basic capabilities of data discovery
- Identification of data anomalies
- Drill down analysis of profile results
Data Quality Analysts are able to profile data sources for identifying data anomalies and are able to assess the business impact
Discuss the following:
- Profile data to examine its structure and context using out-of-the-box templates
- Drill down to see details and filter on results
- Compare profile runs to identify trends over time
- Review CLAIRE insights on profiling results
- Best practices shared
- Reference to product documentation and digital contents
- Data Quality Analyst
- Data Quality Developer
Cloud Governance & Data Quality
Cloud Data Quality
Best Practices
Implement
Adoption
Data Discovery
Data Quality Governance
DGP-014
Disclaimer
- Catalog offers Engagements for Informatica Cloud Services on IDMC platform only.
- All Engagement Topics in this Catalog are intended to be delivered in guidance and advisory mode only. This is implicit and it will not be called out explicitly under each engagement’s scope separately.
- Customers need to include their relevant technical/business team highlighted in each engagement topic to derive the best out of each engagement.
- Customers need to perform any hands-on work by themselves leveraging the guidance from these engagements.
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