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Whitepaper: Implementing Master Data Management at Scale on Databricks with AI

By Roz King, Chief Architect, Frisco Analytics

Summary
In today's data-driven landscape, organizations grapple with fragmented data sources, inconsistent records, and the challenge of maintaining data integrity at scale. This whitepaper delves into the transformative approach of leveraging AI-powered Master Data Management (MDM) within the Databricks ecosystem. Discover how Frisco Analytics' LakeFusion, a native MDM solution for Databricks, addresses these challenges by providing scalable, efficient, and accurate data management capabilities.

Key Topics Covered

Here’s a preview of what’s inside:

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  • Why MDM is critical (and hard) at scale

  • How Databricks powers smarter data quality & governance

  • The role of AI and GenAI in next-gen MDM

  • A practical framework to implement MDM workflows on Databricks

  • How LakeFusion, our Databricks-native MDM solution, simplifies the journey

Why Choose LakeFusion for MDM?

  • Databricks-Native Integration:
    Built specifically for the Databricks platform, ensuring optimal performance and compatibility.
     
  • AI-Powered Entity Resolution:
    Utilizes advanced AI algorithms to accurately identify and merge duplicate records, creating a single source of truth.
     
  • Rapid Deployment:
    chieve full implementation in under six weeks, significantly faster than traditional MDM solutions.
     
  • Cost Efficiency:
    Streamlines MDM operations within Databricks, reducing the need for additional infrastructure and associated costs.
     
  • Scalability:
    esigned to handle large volumes of data, making it suitable for enterprises of all sizes.
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