Informatica natively integrates governance suite on GCP

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 put in place policies and practices to ensure the proper use of data within an organization, helping to guarantee it can be trusted. Data catalogs, meanwhile, are essentially indexes for data sets and data products such as reports and dashboards -- and increasingly AI-powered applications -- where users can search for trusted assets that can be used to inform their work.

By making it easier for customers who use Google Cloud to access its data governance and data catalog capabilities, Informatica is simplifying the process of developing and delivering trusted data, according to Catanzano.

"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 has an integration with Snowflake, while Alation is closely aligned with Databricks.

Like Catanzano, Kevin Petrie, an analyst at BARC U.S., said the expanded partnership between Informatica and GCP 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 the areas of 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, the partnership carries real significance for both Informatica and Google Cloud, he continued.

"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.

In addition, making CDGC available to Google customers not yet using Informatica as well as vendors that sell Google Cloud products on Google Cloud Marketplace was motivation, he added.

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."

Informatica's blueprints for AI development, unveiled in October 2024, are one example of what the vendor is already doing, he added.

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."

Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.