Microsoft Azure Synapse Data Warehouse, formerly known as Azure SQL Data Warehouse, is a big data analytic service that queries and analyzes your data. Create a Microsoft Azure Synapse Data Warehouse catalog source to access data from Microsoft Azure SQL Data Warehouse.
Objects extracted
The metadata extraction capability extracts the following objects from a Microsoft Azure Synapse Data Warehouse catalog source:
•Database
•Table
•Schema
•View
•Materialized View
•Function
•Stored Procedure
•Column
•External Table
•External Column
Note: Effective in the November 2023 release, Metadata Command Center retrieves the database name from the source system instead of the Azure DW JDBC URL. If you extracted database objects before the November 2023 release, and the name of a database that you entered in the Azure DW JDBC URL uses a different case than the original database name, you might extract duplicate assets when you run the catalog source job again. To ensure that you extract the correct database structure, select Delete in the Metadata Change Option and rerun the catalog source job.
Data profiling for Microsoft Azure Synapse Data Warehouse objects
Configure data profiling to run profiles on the metadata extracted from a Microsoft Azure Synapse Data Warehouse source system.
You can run data profiles on the following Microsoft Azure Synapse Data Warehouse objects:
•Tables
•External Tables created in the following file formats on the Microsoft Azure Serverless SQL pool:
- Delimited text
- Parquet
•Views
Configure the following data profiling properties in the Data Profiling tab of the Configuration page in Metadata Command Center:
Property
Description
Azure Blob Container
Name of the Blob container that is used to stage profiled data.
Applies to the Azure Blob storage type.
ADLS FileSystem Name
Name of the file system that is used to stage profiled data.
Applies to the ADLS Gen2 storage type.
Staging File Format
File format to use when you stage the profiled data.
Select one of the following formats:
- Delimited Text. Select if the external table is created in the Delimited text file format.
- Parquet. Select if the external table is created in the Parquet file format.
Applies to external tables created on the Microsoft Azure Serverless SQL pool.
Field Delimiter
Character used to separate fields in a file. Default is 0x1e. Non-printable characters must be specified as hexadecimal characters.
Note: Use the field delimiter that you used while creating the external table in the Delimited text file format.
Quote Character
Specifies the quote character to skip when you read data from Microsoft Azure Synapse SQL.
The quote character that you specify must not exist in the source table. If it exists, enter a different quote character value. Default is 0x1f.
Note: Use the quote character that you used while creating the external table in the Delimited text file format.
You can view the profiling statistics in Data Governance and Catalog. The data profiling task runs profiles on the following data types for Microsoft Azure Synapse Data Warehouse objects:
•Bigint
•Bit
•Char
•Date
•Datetime
•Datetime2
•Decimal
•Float
•Int
•Nchar
•Nvarchar
•Real
•Smalldatetime
•Smallint
•Time
•Tinyint
•Uniqueidentifier
•Varchar
Sampling type
Determine the sample rows on which you want to run the data profiling task. You can choose one of the following sampling types for a Microsoft Azure Synapse Data Warehouse catalog source:
- All Rows
- Limit N Rows
- Random N Rows
Data classification for Microsoft Azure Synapse Data Warehouse objects
Configure data classification for Microsoft Azure Synapse Data Warehouse catalog sources to classify and organize data in your organization. You can view the data classification results in Data Governance and Catalog.
Data Lineage
The following lineage data is available for Microsoft Azure Synapse Data Warehouse assets:
•From table to view
•Stored Procedures linked to tables or views
•Functions linked to tables or views
•Procedure calling a procedure
•Procedure calling a function
For more information about data lineage, see Data Lineage in the Working With Assets help.