Leveraging Enterprise Data for Trusted, High-quality RAG Models with Informatica and Databricks

In the rapidly evolving landscape of artificial intelligence (AI), particularly with the recent emphasis on generative AI (GenAI) and data analytics, organizations are increasingly embracing Retrieval Augmented Generation (RAG)-based architectures to enhance the accuracy of GenAI application outputs. As more organizations implement RAG, they are recognizing the critical importance of data management and the need for high-quality, reliable data to ensure the success of their models.

The integration of Informatica Intelligent Data Management Cloud (IDMC) with Databricks DBRX is paving the way for innovative RAG solutions in. This blog explores how IDMC's robust data management capabilities help transform data into actionable intelligence by enhancing RAG model performance and reliability with trusted, high-quality data. 

The convergence of Informatica IDMC and Databricks DBRX creates a powerful ecosystem for managing and analyzing data at scale. Informatica IDMC provides a comprehensive suite of tools for data integration, quality, and governance, ensuring that data is accurate, consistent and trustworthy. This high-quality data is essential for the success of RAG, as it relies on accurate and relevant information to generate precise and meaningful outputs.

Databricks Data Intelligence Platform complements IDMC by offering a unified platform for all data and AI, allowing organizations to scale the use of data and build new data products. Databricks also recently introduced DBRX, an open, general-purpose Large Language Model (LLM) to build high-quality generative AI applications customized for enterprises’ own unique data. Together, these technologies empower businesses to unlock the full potential of their data, driving innovation and achieving competitive advantage in today's data-driven world with scalable data processing, advanced analytics and enabling effective and efficient AI-driven insights.

Figure 1 - Reference Architecture

The success of generative AI relies on a robust data journey involving discovery, transformation, curation and readiness for RAG within the Databricks platform. Informatica provides over 250 connectors to bring data from various sources into the Databricks SQL Data Warehouse through ELT (extract, load, transfer). This data is processed using Informatica IDMC services like Cloud Data Integration and Cloud Data Quality, with governance through Cloud Data Governance and Catalog tightly integrated with Databricks Unity Catalog. Informatica Master Data Management ensures that Databricks customers have trusted, high-quality data for RAG scenarios. To support context-based retrieval in RAG, Informatica offers a metadata layer to ensure the data for generative AI applications is of high quality and from trusted sources, which is extremely important for enterprise users.

You can learn more about Informatica IDMC and related services here.

A pivotal component in the seamless operation of Informatica IDMC and Databricks DBRX is the Informatica metadata intelligence layer. It enhances the data management process by providing deep insights into the data lineage, quality, and governance, enabling organizations to gain a comprehensive understanding of their data's lifecycle, from creation to consumption. By leveraging metadata intelligence, businesses can ensure that only the most relevant and high-quality data is used in their RAG models. This not only improves the accuracy and reliability of the generated outputs but also facilitates compliance with regulatory requirements and internal data governance policies. Metadata intelligence acts as a vital bridge, connecting robust data management practices with advanced analytics and AI capabilities, driving more informed and confident decision-making across the enterprise.

The key benefit of using Informatica IDMC in conjunction with Databricks DBRX for retrieval augmented generation is that it enhances DBRX's ability to retrieve and enable diverse and complex datasets.

• IDMC can help RAG models leverage Databricks SQL Warehouse via native SQL ELT tooling, including full pushdown capabilities leveraging native Databricks functions.
• All critical IDMC services are validated with Databricks Unity Catalog, enabling a unified governance layer for data and AI, including DBRX applications, within the Databricks platform.
• Informatica’s metadata intelligence provides the ability to interact with the catalog of metadata to ensure only trusted data is part of the retrieval process and RAG systems can automate which data for what questions to be retrieved.
• Informatica IDMC's advanced data integration capabilities enable seamless data ingestion from various sources, including cloud, on-premises and third-party applications.
• Organizations can improve RAG model outcomes by running data through Cloud Data Quality to enhance the quality of the data.
• Informatica IDMC Integration ensures that the data fed into the RAG models is comprehensive and up to date.
• Databricks DBRX's scalable infrastructure and powerful processing capabilities allow for real-time analytics and machine learning model training, making it possible to generate insights and predictions at unprecedented speeds.

The combination of these technologies improves the accuracy and relevance of AI-generated content and reduces the time and effort required to manage and analyze large datasets, leading to more efficient and effective decision-making processes.

The integration of Informatica IDMC with Databricks DBRX supports transformative use cases across various industries. Below are a few examples:

• Banking and Financial Services: Organizations can improve customer experiences with enhanced, customer-centric retrieval and decision-making based on trusted data. It can also be used for more targeted credit card campaigns, marketing offers and loan products, as well as customer identification and predictive analytics (e.g., for delinquencies).
• Healthcare: Healthcare providers can conduct advanced research by leveraging seamless data integration from diverse, disparate sources. Additionally, they can improve patient care with master data management (MDM) and advanced analytics to improve care and reduce the cost of care and other similar outcome-based use cases.
• Retail and CPG:  Retail and CPG organizations can optimize supply chain operations and personalize customer experiences through precise, data-driven insights.

These success stories highlight the practical impact of combining high-quality data management with robust analytics, showcasing the tangible benefits of this integration for specific generative AI use cases.

The collaboration between Informatica and Databricks offers a comprehensive solution for organizations looking to harness the power of RAG. By ensuring data integrity and quality through Informatica IDMC and leveraging Databricks DBRX, you can achieve more accurate and actionable AI-driven insights. As you continue to navigate the complexities of big data and AI, the synergy between these technologies will be crucial in driving innovation and maintaining a competitive edge in the market.

For more information, please reach out to Infafordatabricks@informatica.com