feat(ingest): extract powerbi endorsements to tags

metadata-ingestion/docs/sources/powerbi/powerbi_pre.md

@@ -95,3 +95,9 @@ combine_result
 `Pattern-2` is *not* supported for upstream table lineage extraction as it uses nested item-selector i.e. {Source{[Schema="public",Item="book"]}[Data], Source{[Schema="public",Item="issue_history"]}[Data]} as argument to M-QUery table function i.e. Table.Combine
 
 `Pattern-1` is supported as it first assign the table from schema to variable and then variable is used in M-Query Table function i.e. Table.Combine
+
+## Extract endorsements to tags
+
+By default, extracting endorsement information to tags is disabled. The feature may be useful if organization uses [endorsements](https://learn.microsoft.com/en-us/power-bi/collaborate-share/service-endorse-content) to identify content quality.
+
+Please note that the default implementation overwrites tags for the ingested entities, if you need to preserve existing tags, consider using a [transformer](../../../../metadata-ingestion/docs/transformer/dataset_transformer.md#simple-add-dataset-globaltags) with `semantics: PATCH` tags instead of `OVERWRITE`.

metadata-ingestion/docs/sources/powerbi/powerbi_recipe.yml

@@ -16,6 +16,9 @@ source:
     client_secret: bar
     # Enable / Disable ingestion of user information for dashboards
     extract_ownership: true
+    # Enable / Disable ingestion of endorsements.
+    # Please notice that this may overwrite any existing tags defined to ingested entities!
+    extract_endorsements_to_tags: false
     # dataset_type_mapping is fixed mapping of Power BI datasources type to equivalent Datahub "data platform" dataset
     dataset_type_mapping:
         PostgreSql: postgres

metadata-ingestion/src/datahub/ingestion/source/powerbi/config.py

@@ -45,6 +45,7 @@ class Constant:
     CORP_USER_INFO = "corpUserInfo"
     CORP_USER_KEY = "corpUserKey"
     CHART_INFO = "chartInfo"
+    GLOBAL_TAGS = "globalTags"
     STATUS = "status"
     CHART_ID = "powerbi.linkedin.com/charts/{}"
     CHART_KEY = "chartKey"
@@ -139,6 +140,12 @@ class PowerBiAPIConfig(EnvBasedSourceConfigBase):
     extract_lineage: bool = pydantic.Field(
         default=True, description="Whether lineage should be ingested"
     )
+    # Enable/Disable extracting endorsements to tags. Please notice this may overwrite
+    # any existing tags defined to those entitiies
+    extract_endorsements_to_tags: bool = pydantic.Field(
+        default=False,
+        description="Whether to extract endorsements to tags, note that this may overwrite existing tags",
+    )
     # Enable/Disable extracting lineage information from PowerBI Native query
     native_query_parsing: bool = pydantic.Field(
         default=True,

metadata-ingestion/src/datahub/ingestion/source/powerbi/powerbi.py

@@ -40,11 +40,13 @@
     DashboardKeyClass,
     DatasetLineageTypeClass,
     DatasetPropertiesClass,
+    GlobalTagsClass,
     OwnerClass,
     OwnershipClass,
     OwnershipTypeClass,
     StatusClass,
     SubTypesClass,
+    TagAssociationClass,
     UpstreamClass,
     UpstreamLineageClass,
 )
@@ -238,8 +240,24 @@ def to_datahub_dataset(
             if self.__config.extract_lineage is True:
                 dataset_mcps.extend(self.extract_lineage(table, ds_urn))
 
+            self.append_tag_mcp(
+                dataset_mcps,
+                ds_urn,
+                Constant.DATASET,
+                dataset.tags,
+            )
+
         return dataset_mcps
 
+    @staticmethod
+    def transform_tags(tags: List[str]) -> GlobalTagsClass:
+        return GlobalTagsClass(
+            tags=[
+                TagAssociationClass(builder.make_tag_urn(tag_to_add))
+                for tag_to_add in tags
+            ]
+        )
+
     def to_datahub_chart_mcp(
         self, tile: PowerBiAPI.Tile, ds_mcps: List[MetadataChangeProposalWrapper]
     ) -> List[MetadataChangeProposalWrapper]:
@@ -421,8 +439,31 @@ def chart_custom_properties(dashboard: PowerBiAPI.Dashboard) -> dict:
         if owner_mcp is not None:
             list_of_mcps.append(owner_mcp)
 
+        self.append_tag_mcp(
+            list_of_mcps,
+            dashboard_urn,
+            Constant.DASHBOARD,
+            dashboard.tags,
+        )
+
         return list_of_mcps
 
+    def append_tag_mcp(
+        self,
+        list_of_mcps: List[MetadataChangeProposalWrapper],
+        entity_urn: str,
+        entity_type: str,
+        tags: List[str],
+    ) -> None:
+        if self.__config.extract_endorsements_to_tags and tags:
+            tags_mcp = self.new_mcp(
+                entity_type=entity_type,
+                entity_urn=entity_urn,
+                aspect_name=Constant.GLOBAL_TAGS,
+                aspect=self.transform_tags(tags),
+            )
+            list_of_mcps.append(tags_mcp)
+
     def to_datahub_user(
         self, user: PowerBiAPI.User
     ) -> List[MetadataChangeProposalWrapper]:
@@ -678,6 +719,13 @@ def report_to_dashboard(
         if owner_mcp is not None:
             list_of_mcps.append(owner_mcp)
 
+        self.append_tag_mcp(
+            list_of_mcps,
+            dashboard_urn,
+            Constant.DASHBOARD,
+            report.tags,
+        )
+
         return list_of_mcps
 
     def report_to_datahub_work_units(

metadata-ingestion/src/datahub/ingestion/source/powerbi/proxy.py

@@ -51,6 +51,8 @@ class Workspace:
         state: str
         dashboards: List[Any]
         datasets: Dict[str, "PowerBiAPI.PowerBIDataset"]
+        report_endorsements: Dict[str, List[str]]
+        dashboard_endorsements: Dict[str, List[str]]
 
     @dataclass
     class DataSource:
@@ -89,6 +91,7 @@ class PowerBIDataset:
         workspace_id: str
         # Table in datasets
         tables: List["PowerBiAPI.Table"]
+        tags: List[str]
 
         def get_urn_part(self):
             return f"datasets.{self.id}"
@@ -148,6 +151,7 @@ class Report:
         dataset: Optional["PowerBiAPI.PowerBIDataset"]
         pages: List["PowerBiAPI.Page"]
         users: List["PowerBiAPI.User"]
+        tags: List[str]
 
         def get_urn_part(self):
             return f"reports.{self.id}"
@@ -181,6 +185,7 @@ class Dashboard:
         workspace_name: str
         tiles: List["PowerBiAPI.Tile"]
         users: List["PowerBiAPI.User"]
+        tags: List[str]
 
         def get_urn_part(self):
             return f"dashboards.{self.id}"
@@ -313,6 +318,7 @@ def _get_report(
             description=response_dict.get("description"),
             users=[],
             pages=[],
+            tags=[],
             dataset=self.get_dataset(
                 workspace_id=workspace_id, dataset_id=response_dict.get("datasetId")
             ),
@@ -356,7 +362,6 @@ def get_dashboard_users(self, dashboard: Dashboard) -> List[User]:
     def get_dashboards(self, workspace: Workspace) -> List[Dashboard]:
         """
         Get the list of dashboard from PowerBi for the given workspace identifier
-
         TODO: Pagination. As per REST API doc (https://docs.microsoft.com/en-us/rest/api/power-bi/dashboards/get
         -dashboards), there is no information available on pagination
         """
@@ -394,14 +399,48 @@ def get_dashboards(self, workspace: Workspace) -> List[Dashboard]:
                 workspace_name=workspace.name,
                 tiles=[],
                 users=[],
+                tags=workspace.dashboard_endorsements.get(instance.get("id", None), []),
             )
             for instance in dashboards_dict
             if instance is not None
         ]
 
         return dashboards
 
-    def get_dataset(self, workspace_id: str, dataset_id: str) -> Any:
+    def get_dashboard_endorsements(self, scan_result: dict) -> Dict[str, List[str]]:
+        """
+        Store saved dashboard endorsements into a dict with dashboard id as key and
+        endorsements or tags as list of strings
+        """
+        results = {}
+
+        for scanned_dashboard in scan_result["dashboards"]:
+            # Iterate through response and create a list of PowerBiAPI.Dashboard
+            dashboard_id = scanned_dashboard.get("id")
+            tags = self.parse_endorsement(
+                scanned_dashboard.get("endorsementDetails", None)
+            )
+            results[dashboard_id] = tags
+
+        return results
+
+    @staticmethod
+    def parse_endorsement(endorsements: Optional[dict]) -> List[str]:
+        if not endorsements:
+            return []
+
+        endorsement = endorsements.get("endorsement", None)
+        if not endorsement:
+            return []
+
+        return [endorsement]
+
+    def get_dataset(
+        self,
+        workspace_id: str,
+        dataset_id: str,
+        endorsements: Optional[dict] = None,
+    ) -> Any:
         """
         Fetch the dataset from PowerBi for the given dataset identifier
         """
@@ -437,6 +476,10 @@ def get_dataset(self, workspace_id: str, dataset_id: str) -> Any:
         logger.debug("datasets = {}".format(response_dict))
         # PowerBi Always return the webURL, in-case if it is None then setting complete webURL to None instead of
         # None/details
+        tags = []
+        if self.__config.extract_endorsements_to_tags:
+            tags = self.parse_endorsement(endorsements)
+
         return PowerBiAPI.PowerBIDataset(
             id=response_dict.get("id"),
             name=response_dict.get("name"),
@@ -445,6 +488,7 @@ def get_dataset(self, workspace_id: str, dataset_id: str) -> Any:
             else None,
             workspace_id=workspace_id,
             tables=[],
+            tags=tags,
         )
 
     def get_data_sources(
@@ -678,6 +722,9 @@ def get_reports(
                     workspace_id=workspace.id, entity="reports", _id=raw_instance["id"]
                 ),
                 dataset=workspace.datasets.get(raw_instance.get("datasetId")),
+                tags=workspace.report_endorsements.get(
+                    raw_instance.get("id", None), []
+                ),
             )
             for raw_instance in response_dict["value"]
         ]
@@ -704,6 +751,8 @@ def get_workspaces(self):
                 state="",
                 datasets={},
                 dashboards=[],
+                report_endorsements={},
+                dashboard_endorsements={},
             )
             for workspace in groups.get("value", [])
             if workspace.get("type", None) == "Workspace"
@@ -843,6 +892,7 @@ def json_to_dataset_map(scan_result: dict) -> dict:
                 dataset_instance: PowerBiAPI.PowerBIDataset = self.get_dataset(
                     workspace_id=scan_result["id"],
                     dataset_id=dataset_dict["id"],
+                    endorsements=dataset_dict.get("endorsementDetails", None),
                 )
                 dataset_map[dataset_instance.id] = dataset_instance
                 # set dataset-name
@@ -877,6 +927,20 @@ def init_dashboard_tiles(workspace: PowerBiAPI.Workspace) -> None:
 
             return None
 
+        def scan_result_to_report_endorsements(
+            scan_result: dict,
+        ) -> Dict[str, List[str]]:
+            results = {}
+            reports: List[dict] = scan_result.get("reports", [])
+
+            for report in reports:
+                report_id = report.get("id", "")
+                endorsements = self.parse_endorsement(
+                    report.get("endorsementDetails", None)
+                )
+                results[report_id] = endorsements
+            return results
+
         logger.info("Creating scan job for workspace")
         logger.info("{}={}".format(Constant.WorkspaceId, workspace_id))
         logger.debug("Hitting URL={}".format(scan_create_endpoint))
@@ -902,7 +966,18 @@ def init_dashboard_tiles(workspace: PowerBiAPI.Workspace) -> None:
             state=scan_result["state"],
             datasets={},
             dashboards=[],
+            report_endorsements={},
+            dashboard_endorsements={},
         )
+
+        if self.__config.extract_endorsements_to_tags:
+            workspace.dashboard_endorsements = self.get_dashboard_endorsements(
+                scan_result
+            )
+            workspace.report_endorsements = scan_result_to_report_endorsements(
+                scan_result
+            )
+
         # Get workspace dashboards
         workspace.dashboards = self.get_dashboards(workspace)