Supported transformation details
Collibra Data Lineage supports the most commonly used transformations in the following sources:
- Azure Data Factory
- Databricks Unity Catalog
- dbt
- Google Dataplex
- IBM DataStage
- Informatica PowerCenter
- Informatica Intelligent Cloud Services
- Snowflake
- SQL Server Integration Services
Azure Data Factory
Collibra Data Lineage supports the most commonly used transformations and data sources in Azure Data Factory.
Supported transformations
The following tables shows a non-exhaustive list of supported and unsupported transformations.
Supported data sources
The following table shows a non-exhaustive list of supported sources with the corresponding dataset and linked service types.
CollibraData Lineage supports all data format types that are supported in Azure Data Factory, including binary, Excel file, Delimited text, JSON, Parquet, and so on.
Data sources |
Dataset type |
Linked service type |
---|---|---|
Amazon Redshift | AmazonRedshiftTable | AmazonRedshift |
Azure Blob storage | AzureBlob | AzureBlobStorage |
Azure Data Lake Storage Gen2 | AzureBlobFSFile | AzureBlobFS |
Azure Data Lake Store | AzureDataLakeStoreFile | AzureDataLakeStore |
Azure Databricks Delta Lake | AzureDatabricksDeltaLake | AzureDatabricksDeltaLake |
Azure SQL Managed Instance | AzureSqlMITable | AzureSqlMI |
Azure SQL Server database | AzureSqlTable | AzureSqlDatabase |
Azure Synapse Analytics | AzureSqlDWTable | AzureSqlDW |
DB2 data source | Db2Table | Db2 |
Google Cloud Storage | GoogleCloudStorageLocation | GoogleCloudStorage |
Microsoft Access | MicrosoftAccessTable | MicrosoftAccess |
Microsoft Azure Cosmos Database | CosmosDbSqlApiCollection | CosmosDb |
Open Database Connectivity (ODBC) | OdbcTable | Odbc |
On-premises Oracle database | OracleTable | Oracle |
REST | RestResource | RestService |
Salesforce | SalesforceObject | Salesforce |
Salesforce Marketing Cloud | SalesforceMarketingCloudObject | SalesforceMarketingCloud |
Salesforce Service Cloud | SalesforceServiceCloudObject | SalesforceServiceCloud |
SAP Business Warehouse (open hub) | SapOpenHubTable | SapBW |
SFTP server | SftpLocation | Sftp |
Snowflake | SnowflakeTable | Snowflake |
SQL Server | SqlServerTable | SqlServer |
Supported activity types
A Data Factory can have one or more pipelines. A pipeline is a logical grouping of activities that together perform a task. There are three groupings of activities: data movement activities, data transformation activities, and control activities. For a complete list of Azure Data Factory activity types and descriptions, see Microsoft's documentation on pipelines and activities.
Collibra Data Lineage currently supports the following activity types:
Activity type | Activity group |
---|---|
Copy | Data movement |
Data Flow | Data transformation |
Execute Pipeline | Control |
For Each | Control |
Get Metadata | Control |
If Condition | Control |
Lookup | Control |
Set Variable | Control |
Web Activity | Control |
Databricks Unity Catalog
-
Collibra Data Lineage retrieves lineage information from the lineage system tables that build on the Unity Catalog's data lineage feature, and visualizes lineage down to the column level. Specifically, Collibra Data Lineage ingests lineage for Databases, Schemas, Tables, and Columns, but does not ingest any other assets such as Notebooks or Workflows. So, while Collibra Data Lineage retrieves lineage information from notebooks, CollibraData Lineage does not ingest or include the notebook assets in the technical lineage.
Note Currently, Databricks system tables don't include DLT (Delta Live Tables) column lineage.
-
Collibra Data Lineage retrieves lineage information from the lineage system tables and does not parse the language used to develop notebooks and jobs in Databricks to generate technical lineage. Therefore, you can use any supported language in Databricks. For examples of how Unity Catalog captures and presents data lineage, go to Capture and view data lineage with Unity Catalog in the Databricks documentation.
-
Collibra Data Lineage for Databricks Unity Catalog supports external delta tables referenced by external paths.
ExampleIf the following SQL is used in Databircks Unity Catalog, lineage will be created in Collibra.
CREATE OR REPLACE TABLE table_from_direct_delta_query AS (SELECT * FROM delta.`s3://kktesting/testfolder`)
- Databricks Unity Catalog does not provide source code for each transformation. Therefore, the source code pane in the technical lineage graph generated by Collibra Data Lineage will not display any source code.
- Technical lineage for Databricks Unity Catalog supports only column lineage. Table lineage is not supported.
dbt
Collibra Data Lineage supports the following adapters in dbt:
- Azure Synapse
- Databricks
- Google BigQuery
- Greenplum
- Hive
- IBM Db2
- Microsoft SQL Server
- MySQL
- Oracle
- Postgres
- Redshift
- Snowflake
- Spark
- Teradata
dbt Cloud
Collibra Data Lineage supports materialization, and tables and views are treated like tables by default. You can customize the setting in one of the following ways so that the tables and views are treated like views:
- If you use technical lineage via Edge, specify the
materializedMapping
property in the <source ID> configuration file. - If you use the lineage harvester, specify the
materializedMapping
property in the Source Configuration field in the Technical Lineage for dbt Cloud capability.
Google Dataplex
- Collibra Data Lineage visualizes lineage for Google Dataplex down to table level. To view the technical lineage for Google Dataplex, ensure that you select Objects in the toolbar of your technical lineage graph.
- Google Dataplex Data Lineage can start from GCS or BigQuery and end in BigQuery.
- Currently, stitching is not supported for the table level lineage. This support will be added in a future release with the addition of column level lineage support. When this support is available, stitching will work, regardless of whether you integrated Google Dataplex or registered Google BigQuery databases by using the BigQuery JDBC connector.
- Transformations are ingested by calling the GCP Process and subsequently the GCP Jobs. Therefore, the Service Account user that is defined in the Edge connection requires, at a minimum, the bigquery.jobs.get permission, and optionally the bigquery.admin role, which lets the capability ingest the details of all the jobs in the project.
- Interactive queries that are run in GCP are not shown in the source code pane in the Technical lineage viewer.
IBM DataStage
IBM DataStage uses jobs with stages instead of transformations. IBM Datastage has three job types: parallel jobs, sequence jobs and server jobs. For a list of all job stages per job type in IBM DataStage, read the IBM documentation.
Technical lineage for DataStage supports the following parameters and expressions:
-
Runtime parameters in parameter set files.To include the runtime parameters, ensure to export DataStage files with executables. For more information about exporting DataStage files, go to Prepare an external directory folder for the lineage harvester if you use the lineage harvester, or Create a technical lineage via Edge for DataStage.
- Parameter sets.To include parameters, export the parameter sets as part of your environment file. For more information about exporting DataStage files, go to Prepare an external directory folder for the lineage harvester if you use the lineage harvester, or Create a technical lineage via Edge for DataStage.
- Expression format. The analysis result displays the DATASTAGE_EXPRESSION message when a complex format with advanced functions is parsed.
Informatica PowerCenter transformations
The following table shows a non-exhaustive list of supported and unsupported transformations in Informatica PowerCenter.
Supported transformations |
Unsupported transformations |
---|---|
|
|
|
Informatica Intelligent Cloud Services
The following table shows a non-exhausitive list of supported taskflows and unsupported tasks in Informatica Intelligent Cloud Services.
Supported taskflows |
Unsupported tasks |
---|---|
|
|
The following table shows a non-exhaustive list of supported and unsupported transformations and constructions in Informatica Intelligent Cloud Services. Specifically, transformations and constructions in the Cloud Data Integration service.
Supported transformations |
Unsupported transformations, functions and constructions |
---|---|
|
|
Snowflake
You can create technical lineage for Snowflake by using SQL Snowflake ingestion mode or SQL-API Snowflake ingestion mode. Collibra Data Lineage supports different queries and transformations for each ingestion method. For more information about the ingestion methods, go to Technical lineage for Snowflake ingestion methods.
SQL Snowflake ingestion mode
With the SQL Snowflake ingestion mode, Collibra Data Lineage does not support the following non-exhaustive list of transformations:
- Snowpark
SQL-API Snowflake ingestion mode
With the SQL-API Snowflake ingestion mode, Collibra Data Lineage supports the Data Manipulation Language (DML) statements from the following sources. The table also shows a non-exhaustive list of unsupported queries and transformations.
Supported transformations |
Unsupported queries and transformations |
---|---|
|
|
Note
|
SQL Server Integration Services (SSIS)
Collibra Data Lineage supports the following non-exhaustive list of transformations and component types in SQL Server Integration Services:
Supported transformations |
Supported component types |
---|---|
|
|
- Collibra Data Lineage supports SQL, but cannot parse other languages or scripts, for example SHELL and BAT scripts.
- SQL statements from Excel are not supported.
- Collibra Data Lineage does not create lineage for disabled executables.