Forum Discussion
Post ProdigyHow implementing a data product/data mesh in Microsoft Fabric
Hi pmscorca
Several of Microsoft Fabric's features directly support the data product concept:
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Unified Data Platform: Fabric brings together various data tools and technologies into a single platform. This simplifies data integration, management, and access for data professionals, allowing them to focus on building and refining data products .
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Data Integration and Ingestion: Fabric excels at seamlessly integrating data from disparate sources. This is crucial for data products, which often rely on combining data from various internal and external sources to generate insights .
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Data Governance and Security: Fabric offers robust security features and centralized governance policies. This ensures the data used in data products is secure, reliable, and adheres to organizational compliance standards.
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Collaboration and Sharing: Fabric empowers teams to collaborate and share data easily. This fosters a collaborative environment for developing and refining data products.
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Empowering Business Users: Fabric integrates with Microsoft 365, allowing business users to access and analyze data directly within their familiar applications. This broadens the potential user base for data products.
In summary, Microsoft Fabric's features streamline data access, management, security, and collaboration – all essential aspects of bringing data products to life.
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Post ProdigyOk, but which are the specific Fabric's features to allow to implement data quality in a Fabric domain?
Thanks
Hi pmscorca
While Microsoft Fabric itself isn't directly a data quality tool, it offers several features that can be leveraged to implement and improve data quality within a Microsoft Fabric environment:
1. Unified Data Lake and Data Governance:
- Open data lake: Fabric stores data in its original location, avoiding unnecessary movement and ensuring accessibility for various analytics tools. This eliminates the risk of inconsistencies arising from data copies.
The Ultimate Guide to Microsoft Fabric | by Diksha Upadhyay | Data Empowerment | Medium - Centralized governance: Purview, integrated within Fabric, provides centralized management, access control, and data lineage tracking. This ensures data security and helps identify the origin of any quality issues.
Use Microsoft Purview to govern Microsoft Fabric - Microsoft Fabric | Microsoft Learn
https://learn.microsoft.com/en-us/fabric/governance/endorsement-overview
2. Data Lineage and Tracking:
Fabric facilitates data lineage tracking, allowing you to see how data flows through the system. This helps identify where data quality issues might be introduced and simplifies impact analysis of changes.
Data Engineering in Microsoft Fabric Design: Create and Maintain Data Management (brickclay.com)
3. Data Integration:
Azure Data Factory integration: Fabric integrates with Azure Data Factory, which enables building data pipelines with data cleansing and transformation steps. This allows you to address data quality issues during the data integration process.
4. Reporting and Monitoring:
Fabric's data pipeline capabilities can be used to create reports that track data quality metrics over time. This enables you to monitor trends and identify areas needing improvement.
https://learn.microsoft.com/en-us/fabric/admin/monitoring-workspace
https://centricconsulting.com/blog/monitoring-in-microsoft-fabric/
5. Fostering a Data Culture:Fabric provides a unified platform for data access and analysis, encouraging collaboration between data teams and business users. This shared environment fosters a data culture where data quality becomes a collective responsibility.
By combining these features with additional data quality tools within the Fabric ecosystem, you can establish a robust data quality framework for your organization.
Hope this helps. Please let me know if you have any further questions.
Hi pmscorca
We haven’t heard from you on the last response and was just checking back to see if you have a resolution yet. Otherwise, will respond back with the more details and we will try to help.
Thanks