Supercharge advanced analytics and AI insights on Databricks with accurate and consistent master data. This session explores how Informatica’s Master Data Management (MDM) integrates with Databricks to provide high-quality, integrated golden record data like customer, supplier, product 360 or reference data to support downstream analytics, Generative AI and Agentic AI. Enterprises can accelerate and de-risk the process of creating a golden record via a no-code/low-code interface, allowing data teams to quickly integrate siloed data and create a complete and consistent record that improves decision-making speed and accuracy.

Master Data Management (MDM) is the foundation of a successful enterprise data strategy — delivering consistency, accuracy and trust across all systems that depend on reliable data. But how can organizations integrate trusted third-party data to enhance their MDM frameworks? How can they ensure that this master data is securely and efficiently shared across internal platforms and external ecosystems? This session explores how Dun & Bradstreet’s pre-mastered data serves as a single source of truth for customers, suppliers and vendors — reducing duplication and driving alignment across enterprise systems. With Delta Sharing, organizations can natively ingest Dun & Bradstreet data into their Databricks environment and establish a scalable, interoperable MDM framework. Delta Sharing also enables secure, real-time distribution of master data across the enterprise ensuring that every system operates from a consistent and trusted foundation.

As part of Comcast Effectv’s transformation into a completely digital advertising agency, it was key to develop an approach to manage and remediate data quality issues related to customer data so that the sales organization is using reliable data to enable data-driven decision making. Like many organizations, Effectv's customer lifecycle processes are spread across many systems utilizing various integrations between them. This results in key challenges like duplicate and redundant customer data that requires rationalization and remediation. Data is at the core of Effectv’s modernization journey with the intended result of winning more business, accelerating order fulfillment, reducing make-goods and identifying revenue.

In partnership with Slalom Consulting, Comcast Effectv built a traditional lakehouse on Databricks to ingest data from all of these systems but with a twist; they anchored every engineering decision in how it will enable their data governance program.

In this session, we will touch upon the data transformation journey at Effectv and dive deeper into the implementation of data governance leveraging Databricks solutions such as Delta Lake, Unity Catalog and DB SQL. Key focus areas include how we baked master data management into our pipelines by automating the matching and survivorship process, and bringing it all together for the data consumer via DBSQL to use our certified assets in bronze, silver and gold layers.

By making thoughtful decisions about structuring data in Unity Catalog and baking MDM into ETL pipelines, you can greatly increase the quality, reliability, and adoption of single-source-of-truth data so your business users can stop spending cycles on wrangling data and spend more time developing actionable insights for your business.

Talk by: Maggie Davis and Risha Ravindranath

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