Supermetrics for Databricks
Connect LinkedIn Ads to Databricks — B2B Ad Data on the Lakehouse
Load LinkedIn Ads campaign, lead gen, and demographic data into Databricks for B2B advertising analytics.
Why Connect LinkedIn Ads to Databricks?
Warehouse your LinkedIn Ads data in Databricks for unlimited historical analysis and cross-source SQL.
ML feature store for lead scoring
Transform LinkedIn lead gen data into ML features — rolling cost per lead by seniority, lead form completion rates by industry — and register them in the Databricks Feature Store. Use the same features for both offline model training and real-time inference.
PySpark for B2B audience clustering
Marketing analysts query LinkedIn data with SQL, while data scientists use PySpark to cluster professional audiences by engagement patterns. Both work on the same Delta table governed by Unity Catalog — no duplicate datasets.
Unity Catalog governance for sensitive data
LinkedIn demographic data includes job titles and company names. Unity Catalog lets you apply column masking on PII-adjacent fields and row filters so each business unit sees only their own campaigns — with full audit lineage.
How to Connect LinkedIn Ads to Databricks
Three steps. Under two minutes. Zero code.
- 1
Create a data transfer
Log into Supermetrics, select your data source and Databricks as your destination.
- 2
Authorize and configure
Connect your data source account, provide your Databricks workspace URL and access token, choose your catalog and schema, and select the data you want to transfer.
- 3
Set schedule and start transfer
Choose your refresh frequency (hourly, daily, or weekly) and click Start. Your data begins flowing into Databricks Delta tables automatically.
LinkedIn Ads Data Schema in Databricks
Supermetrics creates and maintains clean, typed tables automatically. Here's what your LinkedIn Ads data looks like in Databricks.
Data Freshness & Scheduling
LinkedIn Ads data is typically available in Databricks within 3-6 hours of the reporting period end.
What LinkedIn Ads Data Can You Pull into Databricks?
Supermetrics gives Databricks access to your full LinkedIn Ads reporting data — metrics and dimensions you already know from the LinkedIn Ads interface.
Key Metrics
- Impressions
- Clicks
- Spend
- CTR
- CPC
- CPM
- Conversions
- CPA
- Lead form opens
- Leads
- Lead form completion rate
- Video views
- Video completions
- Social actions
- Engagement rate
Key Dimensions
- Campaign name
- Campaign group
- Creative name
- Ad format
- Objective type
- Company name
- Company industry
- Company size
- Job title
- Job function
- Seniority
- Location
Resources & Guides
Why Supermetrics for Databricks?
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 Databricks — 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.
Managed Schema
Supermetrics creates and maintains your LinkedIn Ads tables automatically. Schema changes from the source API are handled for you — no broken pipelines, no manual migrations.
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 LinkedIn 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
How do I connect LinkedIn Ads to Databricks with Supermetrics?
Log into the Supermetrics Hub, create a new data transfer, select LinkedIn Ads as the source and Databricks as the destination. Authorize your LinkedIn Ads account, provide your Databricks workspace URL and access token, choose your catalog, schema, and Unity Catalog settings, select the fields you need, set a schedule, and start the transfer. No custom notebooks, Spark jobs, or Delta Lake plumbing required — Supermetrics writes directly to Delta tables and registers them in Unity Catalog so your data is governed, versioned, and queryable with both SQL and PySpark from the moment it lands.
Is my LinkedIn Ads data secure when transferring to Databricks?
Supermetrics is SOC 2 Type II certified and fully GDPR compliant. All LinkedIn Ads credentials are encrypted at rest and in transit. Data flows directly from the LinkedIn Ads API into your Databricks workspace — Supermetrics never stores your marketing data on its own servers. Unity Catalog provides centralized governance: fine-grained row-level and column-level security, attribute-based access control, and a full audit log of who queried what. Delta Lake's transaction log makes every write atomic and traceable, so you always have a verifiable lineage of your LinkedIn Ads data from ingestion to insight.
Can I combine LinkedIn Ads data with other sources in Databricks?
That is one of the defining advantages of the Databricks lakehouse architecture. Once LinkedIn Ads data lands as a Delta table, you can JOIN it with any other table in your lakehouse — raw event streams, CRM exports, product analytics, even ML Feature Store tables used for model training. Query in SQL from Databricks SQL warehouses or switch to PySpark and pandas for data science workflows — same data, no copying. Supermetrics supports 170+ connectors that all land in the same Unity Catalog namespace, and the Photon engine accelerates analytical queries on those Delta tables automatically.
What LinkedIn Ads metrics and dimensions are available in Databricks?
All standard LinkedIn Ads reporting fields are available, including Impressions, Clicks, Spend, CTR, CPC, CPM, 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 stored in your Delta tables. Delta Lake's time travel lets you query any previous version of your LinkedIn Ads data — useful for auditing retroactive metric recalculations or reproducing a dashboard state from last quarter. Schema evolution is handled automatically, so new fields appear as columns without breaking existing queries.
How fresh is LinkedIn Ads data in Databricks?
Data freshness depends on your transfer schedule. Supermetrics supports hourly, daily, or weekly transfers into Databricks. Most teams schedule daily transfers so yesterday's complete data is available each morning. Delta Lake's MERGE capability ensures only new and changed records are upserted, keeping cluster utilization and storage costs low. For teams that need near-real-time visibility, the Photon engine accelerates incremental queries so dashboards refresh in seconds, and you can set up Databricks SQL alerts to trigger notifications when key LinkedIn Ads metrics cross your thresholds.
Does the LinkedIn Ads connector include lead gen form data?
Yes. Lead form opens, completions, completion rates, and cost per lead are all available as metrics in your Delta tables.
Can I analyze LinkedIn Ads by professional demographics in Databricks?
Yes. Job title, job function, seniority, company size, and industry are available as dimensions you can GROUP BY or filter on.
Also Connect to Databricks
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