Supercharge Your Marketing Analytics with The CData Databricks Integration Accelerator

"With CData Sync, we reduced our integration build time by 90%, enabling faster insights and better decision-making across our organization." — Ameya Narvekar, Data Insights Supervisor, NJM Insurance

For marketing and data leaders, the promise of unified marketing analytics in Databricks often feels out of reach. This is primarily due to the complexity of integrating diverse marketing data sources via custom-coded pipelines that leverage diverse APIs, capturing metadata changes, and handling changes to tables incrementally (CDC). In this post, we examine the specific challenges of marketing data integration with Databricks and how CData can help reduce time-to-value in marketing integration by 90%.

The challenges of marketing data integration

Modern marketing teams rely on a wide array of platforms, including Google Analytics, Google Ads, LinkedIn, Twitter Ads, Salesforce Marketing Cloud, and HubSpot. Each of these platforms holds critical data about customer behavior, campaign performance, and ROI. Yet, integrating this data into a centralized analytics platform like Databricks presents three major challenges.

First, marketing data is inherently complex and multidimensional. For example, blending attribution data from Pardot with advertising costs from Google Ads and customer value data from Salesforce is essential for accurate ROI analysis. However, this requires reconciling disparate data models and relationships across platforms.

Second, marketing teams increasingly demand real-time or near-real-time access to performance data. Traditional batch processing methods often fail to meet the speed required for optimizing campaigns and budgets effectively. As Gartner notes, "Marketing data is high in volume and subject to frequent changes, making real-time or near-real-time capture essential for accurate, actionable analytics." Traditional ETL methods fail to support the level of near-real-time access required for marketing analytics use cases.

Finally, the technical complexity of integrating marketing platforms with Databricks is a significant barrier. Databricks does not natively support connectivity to most marketing platforms (Google Analytics, Salesforce Marketing Cloud, Hubspot, etc.), requiring custom API integrations that are resource-intensive, difficult to maintain, and prone to data quality issues.

How CData resolves marketing data integration challenges

The CData Databricks Integration Accelerator addresses these challenges head-on, providing a comprehensive solution that simplifies marketing data integration and accelerates time-to-value.

Universal connectivity to marketing platforms

CData offers pre-built connectors to over 270 enterprise systems, including the most challenging marketing platforms like Google Analytics, Google Ads, LinkedIn, Twitter Ads, Salesforce Marketing Cloud, and HubSpot. These connectors standardize and model marketing data relationally, making it ready for analytics in Databricks without the need for extensive data preparation.

No-code automation for simplified integration

CData’s no-code platform eliminates the need for custom API integrations, enabling business users and data engineers alike to ingest marketing data into Databricks with ease. Built-in automations, such as schema evolution, incremental replication, error detection, and active metadata management, streamline the entire process. For example, NJM Insurance reduced its integration build time by 90% and cut operational costs by 66% using CData Sync.

Performance and scalability

CData’s solution is designed to handle high-volume data pipelines efficiently. For instance one CData customer easily set up data pipelines to move over 175 million rows of data into Databricks, averaging 200 job runs daily. By delivering data in an append-only format, CData Sync integrates seamlessly with Databricks Delta Live Tables, reducing compute overhead and ensuring data integrity. Best of all, the solution also supports near-realtime data access – as Ameya Narvekar, Data Insights Supervisor at NJM Insurance notes: “It takes 4 hours max for any client to get up and running, and we can start looking at the data.”

Implementation guide: How CData fits into your Databricks architecture

Integrating CData into your Databricks environment is a straightforward process that supports both ETL workflows and live data access. Here’s how it works:

Technical architecture overview

CData enables two primary integration workflows:

• ETL workflows: Use CData Sync to extract and load marketing data directly into your Databricks environment for transformation and analysis.
• Live data access: Query real-time data directly from the source using the Databricks Spark engine via CData JDBC drivers, enabling up-to-date insights without data duplication.

CData Sync – ETL integration steps

1. Connect to marketing sources
   Set up secure connections to your marketing platforms, such as Google Analytics, Google Ads, and Salesforce Marketing Cloud. Configure authentication and access permissions and define data extraction parameters.
2. Configure Databricks as a destination
   Add Databricks as a target in CData Sync. Set up storage locations and table structures and integrate with Unity Catalog for governance.
3. Create, schedule, and run jobs
   Define ETL jobs for each marketing data source. Schedule incremental loading to ensure data freshness and monitor pipelines for seamless operation.

For a detailed walkthrough, watch this video on enterprise data replication and transformation in Databricks.

Looking ahead: Unlock the full potential of marketing analytics

As marketing data continues to grow in volume and complexity, the need for efficient, automated integration solutions becomes critical. CData’s approach aligns with Gartner’s vision of cohesive cloud data ecosystems, where metadata and governance are foundational elements.

The results speak for themselves. NJM Insurance accelerated its Databricks ingestion by 10x, enabling faster insights into customer lifetime value and marketing spend efficiency. Databricks customers using CData have eliminated surprise usage charges on data integration and gained full control over their data pipelines. With CData, marketing and data teams can unlock the full potential of their Databricks investment, delivering actionable insights that drive business growth.

Ready to transform your marketing analytics? Explore our Databricks Integration Accelerator and start your journey to streamlined data integration today.