Configure Lineage

Alation Cloud Service Applies to Alation Cloud Service instances of Alation

Customer Managed Applies to customer-managed instances of Alation

The OCF connector for Azure Power BI automatically calculates lineage information during metadata extraction. The lineage information you get in Alation depends on the Alation version and the connector version:

  • Lineage for Power BI dataflow objects is supported from Alation version 2023.3.3

  • Column-level lineage is supported from Alation version 2024.1.2

By default, the connector generates report-level lineage (dataset > report > dashboard). You have the ability to perform additional configurations to get more lineage information on lineage charts:

Configure Cross-System Lineage

You have the ability to configure cross-system lineage to generate lineage between your Power BI Scanner BI source and an RDBMS data sources supported by the connector for lineage:

  • Amazon Redshift

  • Azure Databricks

  • Azure SQL DB

  • Azure Synapse Analytics

  • Databricks on AWS

  • Databricks Unity Catalog

  • Google BigQuery

  • MySQL

  • Oracle

  • PostgreSQL

  • Snowflake

  • SQL Server

  • Teradata

Note

RDBMS data sources must be cataloged in Alation and be connected with the corresponding OCF connector.

Cross-system lineage is configured in the settings of an RDBMS data source. To generate cross-system lineage, configure the BI Connection Info field (Additional datasource connections field) on the RDBMS connector’s General Settings tab in the format host:port (for example, adb-8443049157651279.19.azuredatabricks.net:443). Find more information in Configure Cross-Source Lineage.

The screenshot below shows cross-system lineage configuration on the General Settings tab of a supported RDBMS data source:

../../../_images/powerb17.png

Column-Level Lineage

From Alation version 2024.1.2, you have the ability to enable lineage calculation for columns. With column-level lineage enabled, Alation will generate lineage information for Power BI reports on the report field level. With both column-level lineage and cross-system lineage configured, users will be able to trace lineage from a specific RDBMS column to a specific report field in Power BI:

../../../_images/powerb20.png

Enable Column-Level Lineage

Applies from version 2024.1.2

Column-level lineage can be activated by a Server Admin in Admin Settings > Feature Configuration.

Note

On versions before 2024.1.2, Power BI Scanner OCF sources only support report-level and table-level lineage.

To enable column-level lineage:

  1. Log in to Alation as a Server Admin.

  2. Click the three gears icon on top right to open the Admin Settings page.

  3. Under the Server Admin section, click Feature Configuration.

  4. Locate the toggle Automatically extracts Column Level Lineage from Power BI Scanner data source. Click the toggle to activate the feature.

  5. Click Save changes on the top right of the page to apply the change.

  6. Go to connector General Settings page for your BI Source.

  7. Enable Enable Report Fields Extraction flag and click Save.

  8. Click Run Extraction Now to extract metadata.

Now, lineage for Power BI Scanner OCF sources will be generated at the column level.

Note

Enabling the report field extraction can increase the extraction time, as it is dependent on the PBIX report export and parsing, which might take more time depending on file size.

Note

For information on using the Lineage Settings tab for configuration, contact Alation Support.

Expressions Supported by Lineage

Lineage between data source tables and Power BI datasets is built through parsing dataset expressions which are Power BI M Queries (Power Queries). Alation gets these expressions as responses from the getScanResult API. Lineage between tables and datasets will only be generated if expressions are in one of the formats shown below.

Database Name

Connection Type

Sample Expression

Azure Databricks

Table

"let\n    Source = Databricks.Contents(\"adb-8651250466505288.8.azuredatabricks.net\", \"sql/protocolv1/o/8651250466505288/
0622-214404-awash362\", [Database=null, BatchSize=null]),\n    SPARK_Database = Source{[Name=\"SPARK\",Kind=\"Database\"]}
[Data],\n    default_Schema = SPARK_Database{[Name=\"default\",Kind=\"Schema\"]}[Data],\n    diamonds_Table =
default_Schema{[Name=\"diamonds\",Kind=\"Table\"]}[Data]\nin\n    diamonds_Table";

AWS Databricks

Table

“let\n Source = Databricks.Catalogs(\"dbc-25e69bfd-44ed.cloud.databricks.com\", \"sql/protocolv1/o/7841352139603430/
0118-050057-4xra3flu\", [Database=null, BatchSize=null]),\n       hive_metastore_Database = Source{[Name=\"hive_metastore\",
Kind=\"Database\"]}[Data],\n           technology_Schema = hive_metastore_Database{[Name=\"default\",Kind=\"Schema\"]}[Data],
\n               strm_dems_Table = technology_Schema{[Name=\"student2\",Kind=\"Table\"]}[Data]\n          in\n
strm_dems_Table\n”;

“let\n    Source = DatabricksMultiCloud.Catalogs(\"dbc-25e69bfd-44ed.cloud.databricks.com\", \"sql/protocolv1/o/
7841352139603430/0210-085930-oexhpgse\", [Catalog=null, Database=null, EnableAutomaticProxyDiscovery=null]),\n
hive_metastore_Database = Source{[Name=\"hive_metastore\",Kind=\"Database\"]}[Data],\n    default_Schema = hive_metastore_
Database{[Name=\"default\",Kind=\"Schema\"]}[Data],\n    student2_Table = default_Schema{[Name=\"student2\",Kind=\"Table\"]}
[Data]\n in\n    student2_Table\n”;

Unity Databricks

Table

“let\n    Source = Databricks.Catalogs(\"adb-8443049157651279.19.azuredatabricks.net\", \"sql/protocolv1/o/
 900788168547414/1031-122656-8zrkv0jk\", [Catalog=\"default\", Database=null, EnableAutomaticProxyDiscovery=null]),\n
 hive_metastore_Database = Source{[Name=\"hive_metastore\",Kind=\"Database\"]}[Data],\n  default_Schema = hive_metastore_
 Database{[Name=\"default\",Kind=\"Schema\"]}[Data],\n    t1_Table = default_Schema{[Name=\"t1\",Kind=\"Table\"]}
 [Data]\nin\n    t1_Table”;

SQL Server

Table

"let\n    Source = Sql.Databases(\"ifac-sqlsrv.ceeyrlqdpprr.us-west-2.rds.amazonaws.com\"),\n    Sales = Source{[Name=\"Sales\
"]}[Data],\n    dbo_Customer_Orders = Sales{[Schema=\"dbo\",Item=\"Customer_Orders\"]}[Data]\nin\n    dbo_Customer_Orders";

"let\n    Source = Sql.Databases(\"tcp:ifac-sqlsrv.ceeyrlqdpprr.us-west-2.rds.amazonaws.com,1433\"),\n    AdventureWorks =
Source{[Name=\"AdventureWorks\"]}[Data],\n    Sales_vPersonDemographics =
AdventureWorks{[Schema=\"Sales\",Item=\"vPersonDemographics\"]}[Data]\nin\n    Sales_vPersonDemographics";

"let\n Source = Sql.Databases("tcp:sqlwrhlondonprod.b05aaf70da1f.database.windows.net"),\n LONDON = Source{[Name="london"]}
[Data],\n london_pbi_SHIFTREPORT_REACHSTAT_Allinone = LONDON{[Schema="london",Item="pbi_SHIFTREPORT_REACHSTAT_Allinone"]}
[Data],\n #"Filtered Rows" = Table.SelectRows(london_pbi_SHIFTREPORT_REACHSTAT_Allinone, each [P_sysdate] >= RangeStart and
[P_sysdate] <= RangeEnd)\nin\n #"Filtered Rows""

Query

"let\n    Source = Sql.Database(\"ifac-sqlsrv.ceeyrlqdpprr.us-west-2.rds.amazonaws.com\", \"pubs\", [Query=\"select * from
jobs\"])\nin\n    Source";

"let\n    Source = Sql.Database(\"synapse-edw-d.sql.azuresynapse.net\", \"edwsyndsql\", [Query=\"SeLeCt#(lf)    s.f_name,#(lf)
t.f_name#(lf)from #(lf)    tmp.src_test s#(lf)inner JOIN  #(lf)    tmp.tgt_test t#(lf)ON  #(lf)    s.f_name = t.f_name\"])\nin
\n    Source";

"let\n    Source = Sql.Database(\"synapse-edw-d.sql.azuresynapse.net\", \"edwsyndsql\", [Query=\"select#(lf)    s.f_name,#(lf)
t.f_name#(lf)from #(lf)    tmp.src_test s#(lf)inner JOIN  #(lf)    tmp.tgt_test t#(lf)ON  #(lf)    s.f_name = t.f_name\"])\nin
\n    Source";

"let\n    Source = Sql.Database(\"10.13.12.200:1433\", \"test_database\", [Query=\"select * from
\"\"test_profilling_main.arcs.test\"\".\"\"arcstable\"\"\"])\nin\n   Source";

MySQL

Table

"let\n    Source = MySQL.Database(\"ifac-mysql.ceeyrlqdpprr.us-west-2.rds.amazonaws.com:3306\", \"employees\",
[ReturnSingleDatabase=true]),\n    employees_departments = Source{[Schema=\"employees\",Item=\"departments\"]}[Data]\nin\n
employees_departments";

Query

"let\n    Source = MySQL.Database(\"ifac-mysql.ceeyrlqdpprr.us-west-2.rds.amazonaws.com:3306\", \"crm\", [ReturnSingleDatabase
=true, Query=\"select c.customerNumber , c.customername, c.city, c.country from customers c , orders o where
c.customernumber=o.customernumber\"])\nin\n    Source";

Azure SQL

Table

"let\n    Sql.Database(\"tf-testal-94619nimeshkuma-17.database.windows.net\", \"SqlServerAzDB_1\"),\n
schemaWithViews01_testView01 = Source{[Schema=\"schemaWithViews01\",Item=\"testView01\"]}[Data]\nin\n
schemaWithViews01_testView01";

Azure Synapse

Table

"let\n    Source = Sql.Database(\"synaptestal125371ayush24-ondemand.sql.azuresynapse.net\", \"master\"),\n
dbo_MSreplication_options = Source{[Schema=\"dbo\",Item=\"MSreplication_options\"]}[Data]\nin\n
dbo_MSreplication_options";

Oracle

Table

"let\n    Source = Oracle.Database(\"ifac-orcl.ceeyrlqdpprr.us-west-2.rds.amazonaws.com:1521/orcl\", [HierarchicalNavigation=
true]),\n    IFAC_ADMIN = Source{[Schema=\"IFAC_ADMIN\"]}[Data],\n    ORDER_ITEMS1 = IFAC_ADMIN{[Name=\"ORDER_ITEMS\"]}[Data]\
nin\n    ORDER_ITEMS1";

Postgres

Table

"let\n    Source = PostgreSQL.Database(\"ifac-pgsql.ceeyrlqdpprr.us-west-2.rds.amazonaws.com:5432\", \"postgres\"),\n
public_events = Source{[Schema=\"public\",Item=\"events\"]}[Data]\nin\n    public_events";

Amazon Redshift

Table

"let\n    Source = AmazonRedshift.Database(\"redshift-cluster-1.csjsqfswsudr.us-east-1.redshift.amazonaws.com:5439\", \"dev\",
[BatchSize=null]),\n    public = Source{[Name=\"public\"]}[Data],\n    category1 = public{[Name=\"category\"]}[Data]\nin\n
category1";

Snowflake

Table

"let\n    Source = Snowflake.Databases(\"alation_partner.us-east-1.snowflakecomputing.com\", \"LOAD_WH\", [Role=null,
CreateNavigationProperties=null, ConnectionTimeout=null, CommandTimeout=null]),\n    TABSFDC_Database =
Source{[Name=\"TABSFDC\",Kind=\"Database\"]}[Data],\n    PUBLIC_Schema = TABSFDC_Database{[Name=\"PUBLIC\",Kind=\"Schema\"]}
[Data],\n    ACCOUNT_Table = PUBLIC_Schema{[Name=\"ACCOUNT\",Kind=\"Table\"]}[Data]\nin\n    ACCOUNT_Table";

Non-Quoted Strings:

"let\n    Source = Snowflake.Databases(DS_CONN,DW_CONN,[Role=DS_ROLE]),\n    ANALYTICS_DB_Database =
Source{[Name=DB_CONN,Kind=\"Database\"]}[Data],\n    INSIGHT_REPORT_Schema = ANALYTICS_DB_Database{[Name=DSCH_CONN,Kind=\
"Schema\"]}[Data],\n    CUSTOMER_DIM_G_AGREEMENT_DIM_G_VW_View =
INSIGHT_REPORT_Schema{[Name=\"CUSTOMER_DIM_G_AGREEMENT_DIM_G_GBI_RGG_VW\",Kind=\"View\"]}[Data],\n    #\"Removed Other Columns
\" = Table.SelectColumns(CUSTOMER_DIM_G_AGREEMENT_DIM_G_VW_View,{\"CustomerKey\", \"CustomerCd\", \"CustomerDesc\",
\"MasterAgreementDesc\"})\nin\n    #\"Removed Other Columns\"

Query

"let\n    Source = Value.NativeQuery(Snowflake.Databases(\"hg51401.snowflakecomputing.com\",\"RESTAURANTS\"){[Name=\"FIVETRAN\
"]}[Data], \"select * from fivetran.restaurants_global_postsales.sc_new_monthly_churn\", null, [EnableFolding=true])\nin\n
Source";

Google BigQuery

Table

Extraction from a Table:

"let\n   Source = GoogleBigQuery.Database(),    #\"eng-scene-228201\" = Source{[Name=\"eng-scene-228201\"]}[Data],
HR_Data_Schema = #\"eng-scene-228201\"{[Name=\"HR_Data\",Kind=\"Schema\"]}[Data],   HR_Recruiting_Table = HR_Data_Schema{
[Name=\"HR_Recruiting\",Kind=\"Table\"]}[Data]
in
HR_Recruiting_Table";

Extraction From a View:

“let\n  Source =
GoogleBigQuery.Database(), #\"test-alation-database-1\" = Source{[Name=\"test-alation-database-1\"]}[Data], profiling_Schema =
#\"test-alation-database-1\"{[Name=\"profiling\",Kind=\"Schema\"]}[Data],\n   gbq_profile_View = profiling_Schema{[Name=
\"gbq_profile\",Kind=\"View\"]}[Data]\n
in\n  gbq_profile_View”;

GBQ has default hostname - www.googleapis.com

Query

"let\n    Source = Value.NativeQuery(GoogleBigQuery.Database(){[Name=\"test-alation-database-1\"]}[Data], \"select * from
`test-alation-database-1.CAPITALDATASET.columnprofiler`\", null, [EnableFolding=true])\nin\n  Source";

Teradata

Table

"let\n    Source = Teradata.Database(\"10.13.25.7\", [HierarchicalNavigation=true]),\n    test_query_ingestion =
 Source{[Schema=\"test_query_ingestion\"]}[Data],\n    test2 = test_query_ingestion{[Name=\"test1\"]}[Data]\nin\n    test2";

Query

"let\n    Source = Teradata.Database(\"10.13.25.7\", [HierarchicalNavigation=true, Query=\"SELECT * from test_query_ingestion.
test1 t1 left join test_query_ingestion.test2 t2 on 1=1\"])\nin\n    Source";

Parameterised Expressions Supported by Lineage

Azure Power BI Scanner connector supports the parameterized expressions mentioned in the below table for Lineage:

Note

All parameterized expressions in the table below work with all supported data sources mentioned in Expressions Supported by Lineage.

Types of Parameterized Expressions

Example Parameters used in Dataset Expression

Name of the parameterized expression

Example: BQEnv

let
Source = GoogleBigQuery.Database(),
#"test-alation-database-1" = Source{[Name=BQEnv]}[Data],
PowerBiSchema_Schema = #"test-alation-database-1"{[Name="PowerBiSchema",Kind="Schema"]}[Data],
joinedTable_Table = PowerBiSchema_Schema{[Name="joinedTable",Kind="Table"]}[Data]
in
joinedTable_Table

Parameterized expression preceding with #

Example: #”BQEnv”

let
Source = GoogleBigQuery.Database(),
#"test-alation-database-1" = Source{[Name=#"BQEnv"]}[Data],
PowerBiSchema_Schema = #"test-alation-database-1"{[Name="PowerBiSchema",Kind="Schema"]}[Data],
joinedTable_Table = PowerBiSchema_Schema{[Name="joinedTable",Kind="Table"]}[Data]
in
joinedTable_Table

Parameterized expression used with skip character &

Example: “”&BQEnv&””

let
Source = GoogleBigQuery.Database(),
#"test-alation-database-1" = Source{[Name=""&BQEnv&""]}[Data],
PowerBiSchema_Schema = #"test-alation-database-1"{[Name="PowerBiSchema",Kind="Schema"]}[Data],
joinedTable_Table = PowerBiSchema_Schema{[Name="joinedTable",Kind="Table"]}[Data]
in
joinedTable_Table

Scenarios Supported by the Connector for Parameter Usage

The connector is expected to accurately parse the parameters in critical parts of expressions and establish lineage. The critical parts of expressions are the host, database, schema, table, query, and any renamed columns. Parameters placed in these parts of an expression are essential for extracting the connection information required for lineage tracing. Parameters situated outside of these parts of an expression are less likely to impact the accuracy of the lineage.

Direct Usage

Parameters can act as placeholders for different variables in a dataset expression. For example, the expression below includes placeholder parameters HostParameter, DatabaseParameter, SchemaParameter, and TableParameter. The connector is expected to parse such parameters and extract the necessary connection information for lineage.

"let\n    Source = MySQL.Database(HostParameter, #\"DatabaseParameter\",
[ReturnSingleDatabase=true]),\n    employees_departments =
Source{[Schema=\"\"&SchemaParameter&\"\",Item=TableParameter]}[Data]\nin\n
employees_departments";

Usage of the Ampersand Operator

The ampersand operator & may be used in expressions to concatenate text within hostnames or queries. In the example below, the ampersand operator is used to concatenate parts of a hostname and a query. The connector is expected to parse such expressions accurately.

"let\n    Source = Value.NativeQuery(Snowflake.Databases(\"hg51401.\"
& hostParameter & \".com\",\"RESTAURANTS\"){[Name=\"FIVETRAN\"]}[Data],
\"select * from \" & SchemaNameParameter & \".restaurants_global_postsales.sc_new_monthly_churn\",
null, [EnableFolding=true])\nin\n    Source";

Note

Using the ampersand operator at the beginning or end of a hostname or query may result in incorrect parsing by the connector, potentially causing incomplete lineage.

Column-Level Lineage Expressions

Datasets

"let\n    Source = Sql.Databases(\"ifac-sqlsrv.ceeyrlqdpprr.us-west-2.rds.amazonaws.com:1433\"),\n
Sales = Source{[Name=\"Sales\"]}[Data],\n
dbo_Orders_Details = Sales{[Schema=\"dbo\",Item=\"Orders_Details\"]}[Data],\n
#\"Renamed Columns\" = Table.RenameColumns(dbo_Orders_Details,{{\"Discount\",
\"Discount_field_of_dataset\"}, {\"OrderID\", \"OrderID_field_of_dataset\"},
{\"ProductID\", \"ProductID_field_of_dataset\"}})\nin\n    #\"Renamed Columns\"";
"let\r\n    Source = Sql.Database(#\"Warehouse server\", #\"Warehouse name\"),\r\n
Warehouse_Date = Source{[Schema=\"Warehouse\",Item=\"Date\"]}[Data],\r\n
#\"Renamed Columns\" = Table.RenameColumns(#\"Removed Other Columns\",
{{\"Calendar YWD Week Of Year_Caption_1033\", \"YWD Week Of Year\"},
{\"Calendar YWD Week_Caption_1033\", \"YWD Week - Year\"},
{\"Calendar YWD Year_Caption_1033\", \"YWD Year\"}, {\"Calendar YQMD Month Of Year_Caption_1033\",
\"YQMD Month Of Year\"}, {\"Calendar YQMD Month_Caption_1033\",
\"YQMD Month - Year\"}, {\"Calendar YQMD Quarter Of Year_Caption_1033\",
\"YQMD Quarter Of Year\"}})\r\nin\r\n    #\"Renamed Columns\"";
"let\r\n    Source = Cds.Entities(#\"Dynamics 365 URL\", [ReorderColumns=null,
UseFormattedValue=null]),\r\n    entities = Source{[Group=\"entities\"]}[Data],\r\n
msfp_questions = entities{[EntitySetName=\"msfp_questions\"]}[Data],\r\n
#\"Renamed Columns\" = Table.RenameColumns(msfp_questions,{\r\n{\"createdby\",
\"Created By\"},\r\n{\"createdon\",\"Created On\"}, \r\n{\"createdonbehalfby\",\"Created By
(Delegate)\"},\r\n{\"importsequencenumber\",\"Import Sequence Number\"},\r\n{\"modifiedby\",
\"Modified By\"},\r\n{\"modifiedon\",\"Modified On\"},\r\n{\"modifiedonbehalfby\",
\"Modified By (Delegate)\"}\r\n})\r\nin\r\n    #\"Renamed Columns\""
"let\n    Source = OData.Feed(Company1, null, [Implementation=\"2.0\"]),\n
PBICloseIncStmtGLEntries = Source[PBIClosingGLEntries],\n
#\"Renamed Columns\" = Table.RenameColumns(PBICloseIncStmtGLEntries,\n
{{\"G_L_Account_No\", \"G/L Account No.\"}}),
#\"Changed Type\" = Table.TransformColumnTypes(#\"Renamed Columns\",
{{\"Posting_Date\", type date}}),\n
#\"Renamed Columns1\" = Table.RenameColumns(#\"Changed Type\",
{{\"Posting_Date\", \"Posting Date\"}, {\"Amount\", \"Amt.\"}}),\n
#\"Renamed Columns2\" = Table.RenameColumns(#\"Changed Type2\",
{{\"SmallIconUri\", \"Thumbnail\"}, {\"Description\",
\"Description Full\"}, {\"ReleaseDate\", \"Release Date\"}, {\"AppVersion\",
\"Version\"}, {\"NumberOfRatings\", \"# of Ratings\"}, {\"AverageRating\",
\"Average Rating\"}, {\"Tags\", \"Certified\"},
{\"ShortDescription\", \"Description\"}})\nin\n    #\"Changed Type\""

Dataflows

"section Section1;\r\nshared Query = let\r\n  Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText(\"i45WMlTSUTIyVorViVYyBjJNzZRiYwE=\",
BinaryEncoding.Base64), Compression.Deflate)),
let _t = ((type nullable text) meta [Serialized.Text = true]) in type table
[#\"test 1\" = _t, #\"test 2\" = _t]),
\r\n  #\"Changed column type\" = Table.TransformColumnTypes(Source, {{\"test 1\", Int64.Type},
{\"test 2\", Int64.Type}}),\r\n  #\"Renamed columns\" = Table.RenameColumns(#\"Changed column type\",
{{\"test 2\", \"test 4\"}})\r\nin\r\n
#\"Renamed columns\";\r\nshared #\"Query (2)\" = let\r\n
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText(\"i45WMlTSUTICYmOlWJ1oMMsEiM2UYmMB\",
BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true])
in type table [Column1 = _t, Column2 = _t, Column3 = _t]),
\r\n  #\"Renamed columns\" = Table.RenameColumns(#\"Changed column type\",
{{\"Column3\", \"Column34\"}, {\"Column2\", \"Column23\"}})\r\nin\r\n
#\"Renamed columns\";\r\nshared Table = let\r\n
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText(\"i45WMlTSUTICYmOl2FgA\",
BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true])
in type table [#\"A 1 \" = _t, #\"A 2\" = _t, A3 = _t]),
\r\n  #\"Changed column type\" = Table.TransformColumnTypes(Source, {{\"A 1 \", Int64.Type}, {\"A 2\",
Int64.Type}, {\"A3\", Int64.Type}}),\r\n
#\"Renamed columns\" = Table.RenameColumns(#\"Changed column type\",
{{\"A 1 \", \"B1\"}, {\"A 2\", \"B2\"}, {\"A3\", \"B3\"}})\r\nin\r\n  #\"Renamed columns\";\r\n";

Lineage Limitations

Lineage

  • You must upgrade to Alation version 2023.3.2 or higher to be able to generate cross-system lineage from Databricks Unity Catalog with connector version 2.1.0 or higher.

  • To use lineage with UC Databricks in Alation version 2023.3.2, enable the flag alation.resolution.DEV_bi_connector_returns_db_for_two_part_schema. No flag is required from Alation version 2023.3.3 onwards for cross-system lineage to be generated between Databricks Unity Catalog and Power BI.

  • Lineage for paginated reports (RDL) is not supported. Paginated reports do not contain the dataset ID required to show lineage between a Power BI dataset and a Power BI paginated report.

  • Lineage between data source tables and datasets is built through parsing dataset expressions which are Power BI M Queries (Power Queries). Alation gets these expressions as a response from the getScanResult API. See Expressions Supported by Lineage for examples of supported expressions.

  • Power BI Scanner API doesn’t return datasets with object-level security. As a result, Alation will not show connections, fields, and lineage for such datasets.

Limitations Specific to Column-Level Lineage

  • Power BI column-level lineage is not supported for the following objects:

    • Power BI dashboards

      • Column-level lineage is not shown between a report and a dashboard or a tile and a dashboard

    • Power BI tiles

      • Column-level lineage is not shown between an upstream source and a tile

    • Power BI report measures

  • If a data source column name is modified in Power BI in a dataset or a dataflow, then column-level lineage is supported only if Alation gets the renamed column information in one of the supported formats as part of the dataset expression in the scanner API response.

Note

From Power BI Scanner OCF connector version 2.2.1, the connector supports the parsing of queries that contain table names with periods (.) in them. The table names must be enclosed in quotes to ensure correct parsing, for example:

SELECT a.name, a.id FROM schema.\"Table.name\" a