Informatica brings Cloud Data Governance and Catalog to Google Cloud, empowering customers to build trusted AI and analytics apps faster and easier.
Informatica expanded its partnership with Google Cloud on Thursday to make its Cloud Data Governance and Catalog suite natively available on the tech giant’s platform.
The move aims to enable joint customers to develop trusted analytics and AI applications. In addition, the Cloud Data Governance and Catalog (CDGC) is now available on Google Cloud Marketplace.
Informatica’s CDGC is powered by the vendor’s Intelligent Data Management Cloud, an AI-fueled platform for integrating data from disparate sources and preparing it for development and analysis. Included are capabilities that help customers govern, classify, define, discover, index and measure their data.
According to Stephen Catanzano, an analyst at Informa TechTarget’s Enterprise Strategy Group, the expanded partnership significantly benefits joint customers by making CDGC natively available on Google Cloud Platform (GCP). Native integrations provide advantages over those configured by customers themselves.
“Native availability simplifies integration, improves performance and enhances security by leveraging GCP’s built-in features,” he said. “It also streamlines procurement via Google Cloud Marketplace, making adoption faster and more convenient.”
Based in Redwood City, Calif., Informatica is a longtime data management vendor whose platform enables customers to ready data for informing analytics and AI-driven analysis.
The expanded partnership with Google Cloud furthers Informatica’s ongoing focus on analytics and AI development by simplifying access to data governance and catalog tools that help users trust their data to build applications. Informatica already has similar partnerships with AWS and Microsoft Azure that make CDGC natively available on those platforms, according to Rik Tamm-Daniels, global vice president of strategic ecosystems and technology at Informatica.
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Native availability
Using trusted data is a critical part of developing analytics and AI tools.
If the underlying data used to train analytics and AI applications can’t be trusted, neither can the applications themselves. But if that data is trustworthy, meaning that it’s complete and accurate, users will have faith in their outputs and use them to inform decisions.
Among the potential results of deploying AI applications developed with trusted data are more widespread use of analytics — which has been shown to spur growth — through natural language assistants as well as increased efficiency through automation.
However, ensuring that data is trustworthy — and the applications built on top of that data are similarly trustworthy — is not simple.
Data governance frameworks establish policies and practices to ensure the proper use of data within an organization, helping to guarantee its trustworthiness. Data catalogs, meanwhile, are essentially indexes for data sets and products such as reports and dashboards—and increasingly AI-powered applications—where users can search for trusted assets to inform their work.
According to Catanzano, Informatica is simplifying the process of developing and delivering trusted data by making it easier for customers who use Google Cloud to access its data governance and data catalog capabilities.
“This is a major benefit for joint customers,” he said. “Native integration reduces operational complexity, accelerates analytics and AI initiatives, and ensures tighter alignment with GCP’s tools, driving better outcomes.”
While beneficial for joint customers, Informatica’s integration with Google Cloud is not unique, Catanzano added. For example, Collibra integrates with Snowflake, while Alation is closely aligned with Databricks.
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Like Catanzano, Kevin Petrie, an analyst at BARC U.S., said Informatica and GCP’s expanded partnership is meaningful for joint customers.
But beyond simplifying access to Informatica’s CDGC on Google Cloud, it simplifies the unification of complementary capabilities given that Google Cloud’s catalog tools don’t match those provided by Informatica.
“Cataloging is not Google’s strength,” Petrie said. “The limitations of their catalog, especially in connectivity, AI support and search capabilities, mean that many of their cloud users are hunting for alternatives. Informatica excels in these areas and offers Google users a cross-platform catalog to centralize metadata across multiple clouds and on-premises data centers.”
As a result, he continued that the partnership carries real significance for both Informatica and Google Cloud.
“This partnership is a win for Google, whose customers need cross-platform cataloging,” Petrie said. “It’s also a win for Informatica, which gains better access to Google’s extensive installed base.”
Regarding the impetus for the expanded partnership, the vendor’s goal of providing customers that use Google Cloud with the same native integrations it already provides to those that use AWS and Microsoft played a role, according to Tamm-Daniels.
“Ensuring that our full range of data management services are natively available on and tightly integrated with data, analytics and AI services for each of our cloud partners is a strategic objective,” he said.
He added that making CDGC available to Google customers not yet using Informatica and vendors that sell Google Cloud products on Google Cloud Marketplace was also motivation.
Looking ahead
With CDGC now natively integrated with Google Cloud, Informatica’s product development plans for 2025 will focus, in part, on adding AI to more of its capabilities, including data lineage, according to Tamm-Daniels.
Petrie, meanwhile, suggested that as more enterprises invest in developing AI applications, Informatica would be wise to continue emphasizing the preparation of the unstructured data needed to help train AI models. Unstructured data such as text and images now accounts for over 80% of all data, so making that usable is needed to accurately train AI to understand an organization’s operations.
“Informatica has a pretty solid track record of using AI to optimize the management and governance of structured data, which remains the most popular input for all types of analytics initiatives,” Petrie said. “But as enterprises adopt AI — generative AI in particular — they need to prepare, govern and deliver unstructured data.”
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He added that Informatica’s blueprints for AI development, unveiled in October 2024, are one example of what the vendor is already doing.
Catanzano likewise noted that more investment in tools that simplify AI development should be part of Informatica’s roadmap.
“Informatica could offer prebuilt AI models, tighter Vertex AI integrations and enhanced automation for data preparation,” he said, referring to Google’s generative AI and machine learning platform. “Expanding self-service AI tools and tutorials could further accelerate development.”
