Connect Facebook Ads to Microsoft Fabric — Unified Microsoft Analytics

Log into the Supermetrics Hub, create a new data transfer, select Facebook Ads as the source and Microsoft Fabric (OneLake) as the destination. Authenticate with your Microsoft account, choose your Fabric workspace and lakehouse, select your metrics and dimensions, set a schedule, and start the transfer. Supermetrics writes data directly to OneLake as Delta Lake tables — no Data Factory pipelines to build. Once the data lands, it's instantly available through the lakehouse SQL endpoint for T-SQL queries and through the Spark endpoint for notebook-based analysis, giving every team their preferred access method from day one.

Supermetrics is SOC 2 Type II certified and GDPR compliant. Data transfers are encrypted end-to-end. Once in Fabric, your data inherits Microsoft's full enterprise security stack: Entra ID authentication, workspace-level and item-level permissions, row-level security that flows all the way through to Power BI DirectLake reports, sensitivity labels from Microsoft Purview for data classification, and OneLake data access roles for fine-grained folder-level control within lakehouses. Supermetrics never stores your marketing data after delivery.

Yes — that is one of Fabric's core strengths. Once your Facebook Ads data lands in a lakehouse as Delta Lake tables, you can join it with data from any other source using two complementary access paths: T-SQL via the lakehouse SQL endpoint (familiar to any SQL analyst) or Apache Spark notebooks for complex transformations and data science workflows. Because every Fabric lakehouse stores data in OneLake's open Delta Lake format, there is no data duplication — the same physical data is accessible across the SQL endpoint, Spark, Power BI DirectLake mode, KQL databases, and Data Activator alerts. Supermetrics supports 170+ marketing data sources, all deliverable to the same Fabric workspace.

All standard Facebook Ads reporting fields are available, including Impressions, Clicks, Spend, ROAS, CPA, CTR, and more. You select the exact metrics and dimensions during setup. Data arrives in your lakehouse as Delta Lake tables, which means you get ACID transactions, time travel (query historical snapshots), and schema evolution out of the box. The data is immediately queryable from any Fabric experience and can power Power BI DirectLake dashboards that read the Delta tables in-place — no import or scheduled refresh required — delivering near-real-time reporting with no data movement.

Your transfer schedule controls data freshness. Supermetrics supports hourly, daily, weekly, or monthly transfers to Fabric. Most teams run daily refreshes to have yesterday's complete Facebook Ads data ready each morning. Incremental loading writes only new and changed records, keeping transfer times fast and Fabric capacity usage low. Because the data lands as Delta Lake tables, Power BI reports using DirectLake mode reflect the latest data without a separate import refresh — the moment Supermetrics delivers new Facebook Ads records, your dashboards are up to date.

Yes. Supermetrics writes data to your Fabric lakehouse in Delta Lake format. Delta tables support ACID transactions, schema evolution, and time travel. They are immediately queryable from the SQL endpoint, Spark notebooks, and Power BI DirectLake mode — no additional processing or conversion needed.

Yes. Once your Facebook Ads data lands in a Fabric lakehouse as Delta tables, Power BI can use DirectLake mode to read the data at in-memory speed without importing it into a semantic model. This gives you the performance of Import mode with the freshness of DirectQuery — your reports always show the latest transferred data.

No. Supermetrics replaces the need for custom Data Factory pipelines. It connects directly to the Facebook Ads API, handles authentication, pagination, rate limiting, and data transformation, then writes clean Delta tables to your Fabric lakehouse on a schedule. No pipeline authoring, no debugging API connectors, no maintenance.

Both are excellent choices. Fabric is ideal for teams already invested in the Microsoft ecosystem — Power BI, Azure, Entra ID, Teams. It offers tighter integration with Power BI through DirectLake mode and unified governance via Purview. BigQuery excels in pure SQL analytics and cross-cloud flexibility. Choose Fabric if Microsoft is your primary platform; choose BigQuery if you are on GCP.

Absolutely. Fabric notebooks run PySpark natively. Load your Facebook Ads Delta table into a Spark DataFrame and use pandas, scikit-learn, or any Python library for advanced analysis — audience segmentation, creative performance clustering, budget optimization modeling. The same data that feeds your Power BI dashboard feeds your data science workflows.

For most marketing analytics workloads, an F2 or F4 capacity is more than sufficient. Facebook Ads data is relatively small — even large accounts produce only a few GB of reporting data. The SQL endpoint and DirectLake Power BI reports handle typical query volumes comfortably on lower-tier capacities. Scale up only if you are processing data from hundreds of ad accounts or running complex Spark workloads.