New Azure SQL & Snowflake Scan Levels in MS Purview Preview
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Microsoft Purview
Dec 31, 2023 1:00 PM

New Azure SQL & Snowflake Scan Levels in MS Purview Preview

by HubSite 365 about Microsoft

Software Development Redmond, Washington

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Optimize Azure SQL & Snowflake scans with Microsoft Purviews new selective scan levels feature - Flexible, Efficient & Secure!

Key insights

 

Microsoft Purview has introduced a public preview of a feature that allows for separation of scan levels for Azure SQL Database and Snowflake. Previously, scan levels couldn't be separated, limiting flexibility in the scanning process.

  • L1 scan: Retrieves basic information like file name, size, and fully qualified name.
  • L2 scan: Gathers schema details for structured file types and database tables.
  • L3 scan: Collects schema and samples the file for system and custom classifications.

Data source administrators can now customize scan levels to better suit their needs, with an "Auto detect" setting available by default which selects the highest scan level. For example, Azure SQL Database will default to a Level-3 scan since it supports classification.

This new feature streamlines scanning by automatically applying the most appropriate scan level to data sources based on their capabilities. Moreover, administrators can select a lower scan level to reduce workload impacts or a higher one for comprehensive data analyses.

  • Scans at Level-1 will return basic metadata without the need for schema extraction or classification.
  • Level-2 scans provide table schema information without performing data classification.
  • With Level-3, users get the full benefits of data sampling and classification.

These flexible scanning options accommodate various usage scenarios, such as fast data profiling at Level-1 or detailed classification for governance at Level-3. This feature is part of an ongoing expansion, currently available for Azure SQL Database and Snowflake on Azure IR and Managed VNet IR v2.

Understanding Microsoft Purview's Scan Level Customization

Microsoft Purview's data management capabilities ensure that organizations can keep a handle on their data assets across diverse platforms like Azure SQL Database and Snowflake. With the introduction of customizable scan levels, administrators can now exercise greater control over the scanning process, ensuring that they can tailor the scope and detail of the scans to their specific requirements. Rather than employing a one-size-fits-all approach, the ability to distinguish between L1, L2, and L3 scans empowers teams to parse through their data swiftly for basic insights or dive deeper for meticulous classification and schema extraction. This not only enhances efficiency and saves resources but also aligns with the growing demand for flexible, scalable data governance frameworks that can adapt to different operational demands and compliance requirements.

 

Microsoft has announced a public preview of a feature enabling separation of scan levels in Microsoft Purview. This feature applies to Azure SQL Database and Snowflake scanning processes. Scan levels determine the depth of metadata analysis, with higher levels providing more detailed insights.

There are three primary scan levels defined: L1 scan gathers basic file information, L2 scans extract schema details for structured files and databases, and L3 scans incorporate data sampling and apply classification rules. Until now, these levels were inseparable in the scanning process. This meant users were unable to disable specific aspects like data sampling on classifications.

This new feature introduces flexibility, allowing users to customize scanning processes for different databases, such as Azure SQL Database and Snowflake. When setting up new scans or adjusting existing ones for Azure SQL Database, administrators will notice an option to set scan levels. This can tailor scanning operations to specific needs, enhancing usage scenarios.

Read the full article Public Preview: Separation of scan levels for Azure SQL Database and Snowflake in Microsoft Purview

 

Microsoft Purview - New Azure SQL & Snowflake Scan Levels in MS Purview Preview

 

 

People also ask

Does Microsoft Purview Work with Snowflake?

Microsoft Purview, previously known as Azure Purview, is a unified data governance service that helps organizations manage and govern their on-premises, multi-cloud, and SaaS data. As of the last update, Microsoft Purview has been expanding its capabilities to work with various data sources. However, to get an up-to-date answer regarding direct compatibility with Snowflake, checking the official Microsoft documentation or the latest updates from Microsoft would be recommended.

What is the Difference Between Full Scan and Incremental Scan in Purview?

In Microsoft Purview, a full scan refers to the process where the entire data source is scanned and catalogued. This includes all objects and metadata within the data source. It's typically performed the first time a data source is registered in Purview, or when a complete refresh of metadata is needed. On the other hand, an incremental scan only processes changes that have occurred since the last successful scan. This type of scan is quicker and less resource-intensive, as it scans only new or modified data.

How to Connect Azure SQL Database to Purview?

To connect an Azure SQL Database to Microsoft Purview, users need to follow a set of procedures that include creating and registering the Azure SQL Database as a source in Purview, setting up a scan, and then running the scan to catalog the data. The process involves using the Purview portal to create the data source, defining credentials with appropriate permissions for scanning, and setting up scan rules.

Is Azure Purview Now Microsoft Purview?

Yes, Azure Purview has been rebranded to Microsoft Purview. This change is part of Microsoft's effort to integrate their governance services across their cloud offerings more tightly, and the rebranding helps reflect the service's capabilities to govern data across various platforms, not only within Azure.

 

Keywords

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