Alation says new query feature offers 30% accuracy boost, helping enterprises turn data catalogs into problem solvers

The company announced today the latest group of artificial intelligence capabilities with the ability to enhance the data it calls “chatting with your data” that claims Improving the resolution of the answer by up to 30 %.

The transfer of the data catalog market reflects a fundamental shift in the institution’s expectations. Organizations no longer want separate systems to discover data, governance and analysis. They demand unified platforms that are democratically set to access data while maintaining the accuracy required for business decisions.

I think Obstetric artificial intelligence affects the work of data management and also affects the importance of data management And the construction of requests “,” Satin Sanjani, CEO and co -founder of Venturebeat.

Traditional data catalogs are operated on the destination model. Users moved to the basic system, and search for information and browsing through the results. This approach was made when data teams served as brokers between business users and data systems.

“In the past, an episode was sold to data management specialists in the first place,” Sanjani said. “Increasingly, we find CIOS, CTOS and CPO who build technology Those who are trying to offer technology, Benefit from an verification in order to be able to build agents And simultaneously make sure that these agents rule and manage appropriately. “

Simply put, business users wanted direct access to data without technical experience or an analyst intervention. These types of users only want to get the data they need and the correct answers without worrying about the complexity of the basic data platforms, as AI makes a big difference.

“I think the world has turned upside down, and I think the chat is in fact the new means through which people will make these self -service data, as the catalog was the old way,” Sanjani said.

The Islamic approach focuses on what Sangani calls “knowledge layer” from coordinated data products and comprehensive descriptive data. Although anal had his data catalog and governance capabilities that have evolved over the past decade, it recently got a special start -up numbers to help build Ai Agentic Ai data.

“What numbers did the number station do is that they were mainly built factors at the top of the organized data,” Sanjani said. “What they realized while building these agents is that Building these agents was not a problem of artificial intelligence as much as the problem of graphic data and evaluation. “

The numbers station technology is now an essential part of the new chat capabilities in anal. This integration allows users to inquire about their data through chatting, making data easier and widely inquiring. This technology focuses on ensuring the availability of correct descriptive data, the accuracy of the agents can be evaluated, and agents are given instructions and the correct control.

Determination of competitiveness in the data intelligence market

There is no deficiency in competition in the traditional data catalog market.

Large data platform vendors including data and snowlessness each have their own technologies. Informatica, which is in the process of acquiring it by Salesforce, is also active in space as with Collbra and ATLAN. In the midst of the competition, the analysts company Forster put to place an episode as a leader in its evaluation in Q3 2025 for data governance solutions.

Distinguish through the remainder of the good age and focus on the descriptive data and the evaluation layer instead of building a vertical integrated pile.

“We do not see ourselves as an account seller,” Sanjani pointed out. ))

This approach addresses the Foundation’s concerns about the seller’s lock while solving the accuracy problem that limits the adoption of artificial intelligence in regulatory data scenarios.

He said: “We believe that the data management is no longer something sitting on the side, but this is mainly integrated with the construction of commercial operations, and this is what we see exciting.”

How works as a data catalog that works male artificial intelligence in real world behavior

EUROMONITOR International explains how modern data catalog and data intelligence technology convert commercial operations.

Market Intelligence Company merges the possibilities of data intelligence conversation in an age on its passport platform, which serves more than 2,500 organizations worldwide.

The Euromonitor Data Mix includes a warehouse of the original cloud data of organized data, which is fed by a variety of sources, including operational databases, third -party applications and internal systems through data integration and ETL tools.

Business intelligence and analysis tools are sitting above, allowing analysts to create reports and information panels available in the passport. The company’s data science teams use automatic learning services based on a group of cores to build predictive models and advanced analyzes. EUROMONIRAAAAAAAAAAAAAAAAAAAAAAAAAorlybized from AI by adding natural language visions to their statistical data.

“This ability “Our customers are allowed to quickly reach visions using natural language queries without the need to form complicated filters,” Lamine Lahouasnia, the director of Gen Ai at Euromonitor International, told Venturebeat. “It allows our users to discover data and visions that may be hidden in the past.”

Lahouasnia explained that the previous workflow requires customers to move on multiple pages and complex filters to find specific market data. Users often have to restart their searches when improving standards. This creates bottlenecks that slow customer decisions.

The conversation interface allows customers to ask questions in regular English and receive immediate answers with complete transparency. The system displays the sources of basic data, accounts and thinking behind each response.

Implementation also allows the collection of flexible data. For example, Lahouasnia said that the Euromonitor Passport platform includes pre -calculated regional groups such as the Middle East and Africa. He pointed out that many customers define the regions differently based on the needs of their internal business. The conversation interface allows a dedicated assembly based on customer definitions without asking to extract data and manual processing.

How institutions should implement and publish data intelligence

Euromonitor went despite what Lahouasnia described as a “strict” process when she was looking to choose a seller.

This process and the general trip revealed a number of major lessons and best practices:

Confidence is the basis: Never give up accuracy, especially when your data is a product. Find a solution that can provide clear proportions and quality standards. When users can see how to create an answer and where the data came, they build confidence in the result and are likely to use it in critical decisions.

Focus on people and the process: Data intelligence platform is a cultural transformation. You should invest time and effort in managing change. Setting data heroes in various business units, creating clear governance roles, and providing continuous training. Technology is the tool, but your employees will lead its success.

Governance from the first day: Do not let your data apply to your judgment. Implement a solution that imposes your current safety policies from the beginning. This proactive approach always guarantees data protection and reduces risk.

Strategic partnerships are the key: Technology alone is not enough.
“Our partnership with man was an important component of our success, especially with old data structures that do not always work with configurations outside the box,” said Lahouasnia. “It was incredibly useful to work with a partner who guides us through our data and submit recommendations about the best way a artificial intelligence agency can work with.”