Supermetrics for Microsoft Fabric
Connect Facebook Ads to Microsoft Fabric — Unified Microsoft Analytics
Bring your Facebook Ads data into Microsoft Fabric's OneLake. Store it as Delta tables in your lakehouse, query with T-SQL or Spark, build Power BI dashboards on live data, and combine with every other data source in your Fabric workspace — all managed from a single platform.
Why Connect Facebook Ads to Microsoft Fabric?
Land Facebook Ads data directly in your Microsoft Fabric lakehouse. Query with SQL or Spark, build Power BI reports on top, and unify your marketing data within the Microsoft ecosystem.
- Fabric eliminates the need to move data between separate tools. Your Facebook Ads data lands in a lakehouse via Supermetrics, analysts query it with SQL, data scientists explore it in Spark notebooks, and marketers view it in Power BI dashboards — all within the same workspace, no data movement required.
- Fabric's DirectLake mode lets Power BI read Delta tables directly from OneLake at in-memory speed, without importing data into a semantic model. Your dashboards always show the latest Facebook Ads data with no manual refresh needed. This combines the freshness of DirectQuery with the performance of Import mode.
- Every table in your lakehouse is automatically cataloged in Purview. Sensitivity labels propagate from the lakehouse to Power BI reports, so if your ad spend data is classified as confidential, that classification follows it everywhere. Row-level security and object-level permissions use Entra ID — the same identity management your organization already runs.
- The Fabric lakehouse exposes every Delta table through both a SQL endpoint and a Spark engine. A marketing analyst can write SELECT campaign_name, SUM(spend) FROM facebook_ads GROUP BY campaign_name in the SQL editor, while a data scientist runs PySpark code for audience clustering in a notebook — both hitting the same underlying data.
- Delta Lake brings warehouse reliability to lake storage. If a Supermetrics transfer fails midway, the transaction rolls back — your table stays consistent. Time travel lets you query historical versions of your data. Schema enforcement catches unexpected field changes before they break downstream reports.
- OneLake storage is priced at $0.023 per GB/month — identical to Azure Data Lake Storage Gen2. Compute is metered by Fabric Capacity Units (CUs), which you can pause when not in use. For marketing analytics workloads, even an F2 capacity handles most query loads without breaking a sweat.
How to Connect Facebook Ads to Microsoft Fabric
Three steps. Under two minutes. Zero code.
- 1
Create a data transfer
Log into Supermetrics, select Facebook Ads as your source and Microsoft Fabric as your destination.
- 2
Connect your Fabric workspace
Authenticate with your Microsoft account, choose your Fabric workspace and lakehouse, and select the metrics and dimensions you want to transfer.
- 3
Set schedule and start transfer
Choose your refresh frequency (hourly, daily, or weekly) and click Start. Your Facebook Ads data begins flowing into your Fabric lakehouse as Delta tables.
Facebook Ads Data Format in Microsoft Fabric
Supermetrics delivers your Facebook Ads data in clean, structured files ready for downstream processing.
Delta Lake format — ACID transactions, time travel, and schema enforcement. The native format for Fabric lakehouses, queryable from SQL, Spark, and Power BI DirectLake.
Columnar binary format — compressed and optimized for analytics. The underlying storage format for Delta tables, also readable by any tool that supports Apache Parquet.
Comma-separated values for maximum compatibility. Use when you need to inspect data manually or integrate with tools that do not support Parquet or Delta.
What to Build with Facebook Ads Data in Microsoft Fabric
Once your Facebook Ads data lands in Microsoft Fabric, here's what becomes possible.
Power BI DirectLake dashboards
Build Power BI dashboards that read Facebook Ads data directly from your lakehouse at in-memory speed. No import schedules, no stale data — always live.
Cross-channel Fabric notebook analysis
Use PySpark notebooks in Fabric to blend Facebook Ads with Google Ads, GA4, and CRM data. Run audience overlap analysis, channel attribution modeling, and creative performance clustering.
Real-time alerting via Data Activator
Connect Data Activator to your Facebook Ads lakehouse tables and trigger alerts when CPA spikes, budget pacing exceeds thresholds, or ROAS drops below target — all within Fabric.
Semantic model for self-service analytics
Create a Fabric semantic model on top of your Facebook Ads Delta tables. Business users explore data through Excel, Power BI, or Fabric copilot without writing SQL or knowing table structures.
Unified marketing data mesh
Organize marketing data by domain — paid media, organic, CRM — in separate Fabric lakehouses with shared governance. Supermetrics populates the paid media domain; other tools feed the rest. Cross-domain queries work seamlessly via shortcuts in OneLake.
What Facebook Ads Data Can You Pull into Microsoft Fabric?
Supermetrics gives Microsoft Fabric access to your full Facebook Ads reporting data — metrics and dimensions you already know from the Facebook Ads interface.
Key Metrics
- Impressions
- Clicks
- Spend
- ROAS
- CPA
- CTR
- CPM
- Conversions
- Reach
- Frequency
- Video views
- Link clicks
- Cost per action
- Purchase value
- Add to cart
Key Dimensions
- Campaign name
- Ad set name
- Ad name
- Age
- Gender
- Placement
- Device
- Country
- Region
- Platform (Facebook / Instagram / Audience Network)
- Objective
- Delivery status
- Instagram placement (Feed / Stories / Reels / Explore)
Resources & Guides
How to optimize your Facebook ad campaigns
Facebook Ads report templates
PPC reporting: extract insights from paid campaigns
Why Supermetrics for Microsoft Fabric?
Purpose-built for marketing data since 2009. 200,000+ companies trust Supermetrics to move 15% of global ad spend into reporting and analytics destinations.
No Vendor Lock-In
Your data lands in Microsoft Fabric — infrastructure you own and control. Use any BI tool, any transformation layer, any ML platform. If you ever switch providers, your data and dashboards stay with you.
170+ Marketing Data Sources
Purpose-built for marketing data — not a generic ETL tool. Supermetrics covers 99% of metrics and dimensions from each source, with pre-structured tables ready for analysis. No transformation layer required.
Flexible File Formats
Export your Facebook Ads data as CSV, JSON, or Parquet. Choose the format that fits your downstream tools — whether that's a query engine, ML pipeline, or custom ETL.
Your Data, Your Infrastructure
Supermetrics moves data directly to your destination — nothing is stored on our servers. SOC 2 Type II certified, GDPR and CCPA compliant. Your data stays in infrastructure you control, simplifying privacy and compliance reviews.
Flat-Rate, Predictable Pricing
Fixed annual pricing regardless of data volume — no per-row charges, no surprise bills during peak campaign seasons. Transfer as much Facebook Ads data as you need without worrying about cost spikes.
No Data Limits
Query any date range, any number of campaigns, any level of granularity. No row limits, no sampling, no restrictions on the data you can pull.
Frequently Asked Questions
- 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.
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