Quest data management platform tackles AI’s biggest bottleneck

Quest data management platform tackles AI’s biggest bottleneck

Enterprises are eager to keep up with the rapid advances in AI. But there’s one major problem holding them back: Trusted data.

Data readiness is one of the biggest bottlenecks in making the most out of AI. Though enterprises generate a wealth of information throughout their operations, this data is often scattered across different software and wedged into multiple layers of an organization’s tech stack.

This fragmentation makes it difficult for an enterprise to understand what data they have at its disposal, let alone what it can trust, Bharath Vasudevan, vice president of product and go-to-market at Quest Software, told The Deep View. 

“The amount of inefficiency that that causes, coupled with the fact that data is all over the place, makes it increasingly difficult for organizations to create trusted data.” 

So Quest decided to do something about it. This week, the company launched the Quest Trusted Data Management Platform, a unified SaaS-native solution centered around delivering trusted data. The outcome? Companies can get AI-ready data at speed and scale. The platform brings together and automates five core capabilities: Data modeling, data cataloging, data governance, data quality, and a data marketplace. 

Along with giving enterprises a clear understanding of their data, Quest’s technology is “agnostic,” said Vasudevan. This means that Quest’s platform fits into any tech stack, no matter the database, cloud environment or data warehouse, he said. 

“We work with a lot of the assets that you've already invested in, so there isn't a net new set of tooling for each new environment you're choosing to operate in,” he said.  

And for early adopters, Quest’s platform is already starting to prove itself, offering: 

• Up to 54% faster time to data delivery

• Cost savings of up to 40% by delivering products with high reusability; 

• Improving data reuse by up to 50% by controlling data product sprawl through intelligent matching.

The goal, Vasudevan said, is to “take data that's all over the place inside of the fragment and make it trusted,” using AI and automation as the backbone. “Most of the data leaders we talk to now, they're dealing with data estates that are completely fragmented.”

See it action: Join Quest for Closing the Enterprise AI Trust Gap with the Quest Trusted Data Management Platform on March 3rd at 11AM EST

The AI Impact

AI is at the core of Quest’s new platform in multiple ways:

• The Automated Data Product Factory uses natural language prompts to automate the development of production-ready data products. All analysts need to do is describe what they want in a simple query, and the platform handles the rest.

• A nine-component trust score framework ranks data trustworthiness across several factors, including quality, user ratings, governance completeness and timeliness. And if data starts to go awry, Quest’s system uses AI to continuously monitor for drift and automatically update trust scores.

While AI is baked into the foundation of Quest’s new system, this tech also gives enterprises peace of mind around their data in a time when trust is vital, said Vasudevan.

As we move from the era of call-and-response generative AI to the era of agents, enterprises are taking their hands off the wheel. However, in order to trust what comes out of the models, we need to trust what they’re built on. That ethos is at the heart of the Quest Trusted Data Management Platform, Vasudevan said: Giving enterprises the trust they need to put agents to work.

“We're trying to solve bigger problems and then figure out where there's enough trust in the data, trust in the outcomes, to remove the human,” said Vasudevan. “The only way you're going to remove a human from the loop is if you trust the output.”

Explore how Quest is turning fragmented data into trusted, AI-ready assets.