@Federico Sardo - Thanks for the question and using MS Q&A platform.
Unfortunately, Azure HDInsight is not supported on Microsoft Purivew.
Appreciate if you could share the feedback on our feedback channel. Which would be open for the user community to upvote & comment on. This allows our product teams to effectively prioritize your request against our existing feature backlog and gives insight into the potential impact of implementing the suggested feature.
Alternative findings as per my research:
If Purview is not an option for connecting with HDInsight, there are alternative approaches you can consider to meet the data governance, lineage, and data masking requirements in your HDInsight environment. Here are a few options:
Apache Atlas: Apache Atlas is an open-source data governance and metadata framework that can be integrated with HDInsight. It provides features for data classification, lineage tracking, and metadata management. You can set up Apache Atlas on your HDInsight cluster and configure it to capture and manage metadata for your data assets.
Custom Lineage Tracking: You can develop a custom solution for capturing lineage information within your HDInsight environment. This would involve instrumenting your data processing pipelines to record the lineage information as the data flows through various transformations. You can store this lineage information in a separate database or metadata repository for future reference.
Third-Party Tools: There are several third-party data governance and lineage tools available in the market that can integrate with HDInsight. These tools often provide more advanced features and user-friendly interfaces for managing data governance. Some popular options include Collibra, Informatica Axon, and Alation. You can evaluate these tools based on your specific requirements and choose one that integrates well with HDInsight.
Custom Data Masking: To implement data masking in HDInsight, you can develop custom scripts or use frameworks like Apache NiFi or Apache Ranger. These tools provide capabilities for masking sensitive data as it moves through your data pipelines. You can define rules and policies to determine how the data should be masked based on your client's requirements.
Remember to thoroughly evaluate and test any solution you choose to ensure it meets your specific needs and aligns with your client's data governance requirements.
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