Integrate Databricks — ML Pipeline Data Flows
Connect machine learning workflows, cluster metrics, and job data from Databricks. Feed ML insights into Redash or your analytics stack.
Top performer: Brand campaigns at 8.1x ROAS.
Connect marketing data to Databricks automatically
Improvado extracts data from 500+ marketing platforms through native API connections and loads it directly into your Databricks lakehouse. The platform handles authentication, rate limiting, and data extraction schedules without manual intervention. Data refreshes run automatically every hour, ensuring your Databricks environment always contains the latest marketing performance metrics. No custom scripts or ETL development required.
From connection to autonomous action in three steps
Connect
Authenticate Databricks via OAuth in under 5 minutes. Improvado normalizes your data across 1,000+ sources automatically.
Ask
Your AI agent queries Databricks performance in natural language. Trends, anomalies, cross-channel comparisons — one conversation.
Act
The agent pauses underperformers, adjusts settings, generates executive reports, and monitors anomalies — every action logged.
Import your data into your Databricks data warehouse
Databricks is a cross-platform document-oriented database. So, unlike relational databases, it stores the data in JSON-like documents. The Databricks developers believe that this is the best way to store data and that it'ssuperior to relational databases. This also means easier for developers tolearn and use.
As part of its products, it offers companies Databricks Cloud. This service's coreis Databricks Atlas, a fully managed cloud database that companies can use for modern applications. As a result, companies can simplify their data infrastructure with an application data platform that gives them real-time analytics ability.
Some of the benefits of using the connector include:
- It's available across various platforms and provides best-in-class automation and best practices that guarantee availability, scalability, and compliance.
- It features integrations with the tools companies already use so that they can gain valuable insights from the business data in an instant.
- It features the necessary security features to ensure that a company's data stays safe.
Unified marketing data across all platforms
Improvado's Marketing Common Data Model (MCDM) standardizes data from different sources before loading into Databricks. Campaign metrics from Google Ads appear alongside Facebook data using consistent field names and formats. This normalization eliminates data silos and enables cross-platform analysis within your Databricks notebooks. Teams can build machine learning models on unified datasets without spending weeks on data preparation.
What teams ask their AI agent about Databricks
Real prompts from enterprise marketing teams. The agent reads your data, answers in seconds, and takes action when you ask.
Analyze customer journey across Google, Facebook, and email campaigns in unified Databricks tables
Your AI agent analyzes Databricks data and delivers actionable insights — automatically, in seconds.
Build ML models for budget allocation using normalized spend data from all advertising platforms
Your AI agent analyzes Databricks data and delivers actionable insights — automatically, in seconds.
Create executive dashboards combining CRM, advertising, and web analytics in single view
Your AI agent analyzes Databricks data and delivers actionable insights — automatically, in seconds.
Your agent doesn't just read Databricks — it acts on it
Read
Pull metrics, dimensions, and trends from Databricks — across every account and campaign. Your AI handles the query.
Write
Launch campaigns, pause underperformers, adjust settings. Every action logged and governed.
Monitor
Anomaly alerts, budget pacing watches, weekly auto-reports. Problems caught before they burn budget.
Query, write, and monitor Databricks through Claude, ChatGPT, Cursor, or any MCP client. Every action is logged and governed.
| Campaign | Spend | ROAS |
|---|---|---|
| Brand — Exact | $4,200 | 8.1x |
| Non-Brand | $12,800 | 4.7x |
| Retargeting — 30d | $3,100 | 4.2x |
| Competitor | $8,400 | 3.1x |
| DSA — Blog | $2,600 | 2.8x |
Send Databricks data anywhere
Load normalized data to your preferred warehouse, BI tool, or cloud storage.
They extract data. Improvado deploys an agent.
Traditional tools move data from A to B. Improvado gives you an AI agent that reads, acts, and monitors — with Databricks as one of 1,000+ integrated sources.
| Feature | Improvado | Supermetrics | Funnel.io | Fivetran |
|---|---|---|---|---|
| Data fields extracted | 200+ | ~90 | ~120 | ~80 |
| Total integrations | 1,000+ | ~150 | ~500 | ~300 |
| Cross-channel normalization (CDM) | ✓ Built-in | ✗ Manual | ● Basic mapping | ✗ Raw only |
| AI Agent access (MCP) | ✓ Read, Write, Monitor | ✗ | ✗ | ✗ |
| Data warehouse destinations | ✓ 16+ warehouses & BI tools | Sheets, Looker, BigQuery | BigQuery, Snowflake, Redshift | ✓ Broad warehouse support |
| Refresh frequency | Every 15 min | Scheduled triggers | Daily / 6hr | Every 15 min (premium) |
| SOC 2 Type II & HIPAA | ✓ | ✗ SOC 2 only | ✓ SOC 2 | ✓ |
| Best for | Teams that want an AI agent, not a pipeline | Small teams, spreadsheets | Mid-market, data teams | Engineering-led ELT pipelines |
Comparison based on publicly available documentation as of April 2026. Feature availability may vary by plan tier.
Frequently asked questions
Put an AI agent on your Databricks today
Connect in under 5 minutes. Your agent starts reading, acting, and monitoring immediately.