Connect Facebook Ads to Azure Synapse — Unified Ad Intelligence on Azure

Log into the Supermetrics Hub, create a new data transfer, select Facebook Ads as the source and Azure Synapse Analytics as the destination. Authorize your Facebook Ads account, enter your Synapse workspace endpoint and authentication details, choose your dedicated SQL pool and schema, select the fields you need, set a schedule, and start the transfer. No Azure Data Factory pipelines, custom SSIS packages, or PolyBase staging configurations required — Supermetrics handles the entire pipeline so your data lands in Synapse ready to query.

Supermetrics is SOC 2 Type II certified and fully GDPR compliant. All Facebook Ads credentials are encrypted at rest and in transit using TLS 1.2+. Data flows directly from the Facebook Ads API into your Synapse workspace — Supermetrics never stores your marketing data on its own servers. Azure Synapse provides enterprise-grade security through Azure Active Directory single sign-on, workspace-level firewall rules, column-level and row-level security on tables, and Transparent Data Encryption (TDE) for data at rest. Managed private endpoints keep traffic off the public internet entirely.

Absolutely — cross-source analysis is where Azure Synapse excels as a unified analytics platform. Once Facebook Ads data lands in your dedicated SQL pool, you can JOIN it with any other table in the pool. Need to pull in raw logs or archives? PolyBase and serverless SQL pools let you query Parquet, CSV, and JSON files directly in Azure Data Lake Storage without loading them into the warehouse. You can also connect Power BI natively to your Synapse workspace for live dashboards that blend Facebook Ads data with CRM, ERP, and product data — all within the Azure ecosystem. Supermetrics supports 170+ data sources that all load into the same Synapse workspace.

All standard Facebook Ads reporting fields are available, including Impressions, Clicks, Spend, ROAS, CPA, CTR, and many more. You select exactly which metrics and dimensions to transfer during setup, and you can add or remove fields at any time without losing historical data already loaded into Synapse. Because Synapse dedicated SQL pools use MPP (massively parallel processing) architecture, analytical queries across wide tables with many metric columns execute fast — the engine distributes work across compute nodes automatically.

Data freshness depends on your transfer schedule. Supermetrics supports hourly, daily, or weekly transfers into Azure Synapse. Most teams schedule daily transfers so yesterday's final numbers are available each morning. Incremental loading means only new and changed records are written, keeping DWU consumption and load times minimal. For ad-hoc exploration of the latest data, you can also use Synapse's serverless SQL pool to query staged files in Data Lake Storage on demand — no dedicated capacity required.

Supermetrics maps Facebook Ads fields to Synapse-native types. Dates become DATE, text fields like campaign_name are stored as NVARCHAR(512), monetary metrics like spend use DECIMAL(18,6) for sub-cent precision, and count metrics like impressions use BIGINT. Distribution and indexing settings are optimized for typical analytical query patterns.

Yes. Synapse supports both Import and DirectQuery modes in Power BI. DirectQuery means your Power BI reports always show the latest data without scheduled refreshes — every interaction queries the Synapse dedicated pool in real time. For high-concurrency scenarios, use result-set caching in Synapse to serve repeated queries from cache.

For most Facebook Ads workloads, use HASH distribution on campaign_name (or campaign_id) and a CLUSTERED COLUMNSTORE INDEX. This collocates data for the same campaign across the same distribution, minimizing data movement during GROUP BY queries. If your tables are small (under 60 million rows), ROUND_ROBIN distribution is simpler and works well. Supermetrics sets sensible defaults that you can adjust later.

Yes. Define an external data source pointing to your ADLS Gen2 container, create an external table over the Parquet or CSV files, and JOIN it with your facebook_ads table using standard T-SQL. A common pattern is joining Facebook Ads spend data with raw web analytics logs stored in the data lake to calculate true cost-per-session metrics.

Synapse pricing has two main components: compute (DWU-hours for dedicated pool) and storage (roughly $0.023 per GB per month). Facebook Ads datasets are typically small — even large accounts with years of history rarely exceed a few GB of storage. The main cost driver is compute, which you can pause entirely during off-hours to save money. Most teams spend under $50/month for a DW100c dedicated pool running during business hours.

Yes. The Facebook Ads API covers all Meta ad placements including Instagram Feed, Stories, Reels, and Explore. Data lands in the same Synapse table with a placement column. Filter with WHERE placement LIKE '%instagram%' to analyze Instagram-specific performance, or leave it unfiltered for a unified Meta Ads view across all placements.