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Why Salesforce needs a data management platform

There are reports that Salesforce is looking to acquire Informatica, but such a move needs to fit with its AI and GenAI strategy

Salesforce may be making a bid to extend its reach in data management. Late last week, The Wall Street Journal reported that the software-as-a-service provider was in “advanced talks to acquire Informatica”.

In its 2024 AI and software themes report, analyst Macquarie argued that demand for generative artificial intelligence (GenAI) would drive the need for data layers. Informatica offers such a data layer with its Intelligent Data Management Cloud (IDMC).

The analyst predicts that enterprises will come to realise developing an AI strategy first requires developing a data strategy. “We think Salesforce understands that it will need to have an easy-to-use data layer that is rich with much-needed metadata to deliver on its generative AI product roadmap,” it stated.

Salesforce provides AI for predictive analytics on its platform, and is also offering GenAI, which can be integrated with chatbots to enhance enterprise workflows.

Speaking to Computer Weekly prior to the Wall Street Journal story, Salesforce senior vice-president of AI Jayesh Govindarajan gave an example of how datasets from enterprise systems could be combined with a conversation occurring with a chatbot. He said the chatbot would typically be programmed with a set of responses it needs to take based on a predefined flow chart. But, he said: “At runtime, this changes dynamically when I give it a task or an instruction to resolve.” 

He said that such a task requires a combination of contextual data, based on prior knowledge, plus a set of actions that have been registered with the system. The system then needs to orchestrate these in the right order to enable the chatbot to respond to a query. “The flow chart is actually being created dynamically based on the conversation with the customer,” said Govindarajan.

For predictive analytics, enterprise applications require a way to provide machine learning tools with access to enterprise data stores. GenAI applications such as chatbots can also be enhanced when integrated with enterprise data.

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In December 2023, analyst Gartner’s Magic quadrant for data integration tools highlighted Informatica’s robust data ecosystem and the strength of Claire, its active metadata-driven machine learning engine.

In the report, Gartner said Claire continuously analyses the discovered metadata to provide highly relevant insights to data engineers on data integration design and operations. As an example, Gartner said Claire uses the metadata collected by Informatica’s FinOps AI optimiser to recommend the most optimal price-to-performance map for designing cost-efficient data pipelines in its Advanced Data Integration tool.

However, in terms of competitive pressures and where more work needs to be done, Gartner said it had seen renewed competitive pressure. “Some Informatica prospects – especially those that were planning a cloud DBMS migration – were seen evaluating the native embedded data integration tools of cloud DBMS against Informatica. The prospects cited lower cost and/or ease of integration with native DBMS and analytics services.”

Gartner said it had also received feedback from a few of its clients raising issues relating to maintenance and support. “A small but significant number of Gartner clients and Peer Insights contributions reported a lack of consistency in their maintenance and support experience,” the analyst said.

Given that Salesforce’s Data Cloud has an annual subscription renewal rate of almost $400m, and grew almost 90% in the past quarter, Macquarie said: “We think Informatica’s cloud-agnostic IDMC platform would be an attractive asset to cross-sell into Salesforce’s customer base.”

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