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Qlik unveils GenAI assistant, tools to build trusted AI

The longtime analytics vendor's latest new features include data integration capabilities targeting data quality and a GenAI assistant that includes data lineage capabilities.

Qlik on Tuesday unveiled new data integration capabilities and an AI-powered assistant, both designed to help enterprises develop AI applications using data that can be trusted to inform business decisions.

Qlik Talend Cloud and Qlik Answers were introduced during Qlik Connect, the vendor's user conference in Orlando. Both are in public preview with general availability scheduled for the summer. In addition, Qlik revealed a new collaboration agreement with AWS aimed at enabling joint customers to accelerate their use of AI.

Previously, in September 2023 Qlik launched Staige, an ecosystem that combined the vendor's pre-existing AI and machine learning tools with generative AI capabilities from third-party vendors to create an environment where customers can build and train generative AI models and applications.

In addition, in January Qlik formed an AI council made up of five industry experts to help both Qlik as well as its customers develop responsible AI products. Also that month, the vendor acquired Kyndi to add support for the unstructured data needed to inform and train generative AI models and applications.

Combined, the new capabilities and Qlik's previous AI-related initiatives show that the vendor is taking a pragmatic approach to AI development that serves the needs of its customers, according to Donald Farmer, founder and principal of TreeHive Strategy.

While not as aggressive as vendors such as Databricks and Snowflake that have made multiple acquisitions and unveiled numerous new capabilities to build environments for AI development, by focusing on trusted data, Qlik is nevertheless providing needed capabilities.

"To date, Qlik's moves have been very tactical compared to the big strategic investments of larger competitors like Salesforce, Google and Microsoft," Farmer said. "But their support for AI has been well attuned to the needs of their existing customers by supporting the integration of the Qlik stack, which customers already used with AI platforms they may be exploring."

Based in King of Prussia, Penn., Qlik is a longtime analytics vendor that, in recent years, also developed a data integration platform. Now the vendor is making AI a primary focus, including generative AI.

As a vendor that has narrower focus than some of the larger companies with which it competes, including tech giants AWS, Google and Microsoft, Qlik boasts fewer data and AI infrastructure capabilities, Farmer noted. But what it is doing with the capabilities it does have is astute.

"They are doing a good job by focusing on data trust and flexibility in development," Farmer said.

New capabilities

Qlik Talend Cloud and Qlik Answers are each designed to provide users with trustworthy responses delivered by AI models and applications, including generative AI tools.

Generative AI has been the dominant trend in data management and analytics over the 18 months since OpenAI's launch of ChatGPT altered what could be done when data and generative AI are combined.

Previously, true natural language interactions with data were not possible. Some vendors had developed natural language processing (NLP) tools, but they were limited by small vocabularies. In addition, coding skills and data literacy training were needed to query and analyze data. As a result, despite attempts to make their tools easier to use, only a small number of employees within organizations had the knowledge to use data in their workflows.

Large language models, which not only have vocabularies as big as a dictionary but also are able to infer intent, enable true NLP. That, when integrated with an enterprise's proprietary data, reduces the need to code and go through extensive data literacy training to model, query and interpret data.

Accuracy, however, remains a problem. Qlik Talend Cloud addresses accuracy through data quality.

While the combination of generative AI and data reduce the complexity of data management and analytics, ensuring that the responses generated by AI models and applications are accurate has been a challenge.

Language models need to be trained with an organization's proprietary data to understand that organization's operations and be able to respond to queries related to that organization, such as what year-over-year sales were in each month.

Therefore, the data used to train those models has to be high quality and comprehensive. If the data is poor, the responses will be inaccurate. If the data is incomplete, models might make up answers. If those inaccurate or made-up answers are plausible, they could lead to bad business decisions.

Qlik's moves have been very tactical compared to the big strategic investments of larger competitors like Salesforce, Google and Microsoft. But their support for AI has been well attuned to the needs of their existing customers.
Donald FarmerFounder and principal, TreeHive Strategy

Qlik Talend Cloud is a data integration suite that combines the capabilities Qlik acquired when it purchased Talend in 2023 with the vendor's pre-existing data integration capabilities.

The suite includes a data marketplace to enable discovery and curation of quality datasets and data products using natural language search, data engineering tools with both no-code and pro-code options, and a trust score for AI models and applications based on an assessment of the underlying data.

"Qlik Talend Cloud is the industrialization of all our data integration and data quality capabilities into one platform to speed the development and deployment of data pipelines for analytics and AI applications," said Mike Capone, CEO at Qlik.

That focus on providing trusted data, meanwhile, is appropriate for Qlik, according to Farmer.

The features included in Qlik Talend Cloud don't come as a surprise and aren't materially different than the data integration and data quality tools offered by some other vendors, he noted. But they are nevertheless important to existing Qlik customers as they use their data to build advanced analytics models and applications.

"Qlik Talend Cloud is much as expected," Farmer said. "They have doubled down on trust and governance, which is a good move. But it's not a surprising one and not a significant differentiator. Everyone in data integration is focusing on trust and governance to some extent."

Mike Leone, an analyst at TechTarget's Enterprise Strategy Group, similarly said that most data management and analytics vendors are creating new capabilities and repurposing existing ones to foster AI development.


As a result, Qlik's focus on trust, including the addition of a trust score that includes a dashboard with six attributes demonstrating the trustworthiness of data, helps the vendor serve the needs of its users and stand slightly apart from its competitors.

"Finding areas of differentiation gets challenging," Leone said. "The biggest differentiating factor for Qlik is the areas related to ensuring trust and confidence in AI development and decisioning. Qlik Talend Trust Score for AI, in particular."

Like Qlik Talend Cloud, Qlik Answers similarly aims to result in actionable, trustworthy insights. But it goes about getting those results in a different way.

Qlik Answers is a generative AI assistant similar to those offered by competing vendors such as MicroStrategy and Tableau that enables users to engage with their data using natural language.

The prebuilt tool plugs into an enterprise's curated data sources, including the unstructured data that is estimated to represent well over three-quarters of all data, and can then be deployed by self-service users to ask questions of data that lead to insights and decisions.

In addition to responses, Qlik Answers provides explanations that show how the tool arrived at its response, enabling users to easily check its work and discern whether its output is trustworthy. Meanwhile, the tool comes with security and governance capabilities that, like traditional data governance frameworks, aim to simultaneously enable safe data exploration and protect the organization.

Given that many potential AI users are wary of inaccuracies, its most important feature is explainability, according to Farmer.

"Answers promises full explainability, which we have yet to see proven in the field. But [it] is a good promise to make because many executives in enterprises like Qlik's customer base are wary of the practical and reputational risk of AI investments," he said.

Leone, meanwhile, noted that part of the significance of Qlik Answers is that it marks the first time customers can query and analyze unstructured data such as text, images and audio files using Qlik.

BI has historically focused on deriving insights from structured data, such as financial records and point-of-sale transactions, while unstructured data was inaccessible. Vector search and other capabilities now enable enterprises to give structure to unstructured data so it can be operationalized and used to inform decision-making using tools such as Qlik Answers.

"I like Qlik's focus on unstructured data as it's often overlooked and underutilized," Leone said. "How can organizations expect to get the best answers from GenAI solutions if they're missing out on incorporating all the right knowledge? This will provide customers with a simplified way to incorporate a massively untapped pool of data."

Beyond the new features, Qlik formed a new partnership with AWS under which Qlik's tools will be combined with AWS's cloud and generative AI capabilities. The vendors will collaborate to jointly develop new AI-powered capabilities.

Specifically, the partnership provides joint customers with access services such as Amazon Bedrock, a platform on which users can access a host of foundation models via a single API, AI development tools for secure and responsible AI models, and applications and streamlined compliance across AWS regions to enable Qlik users to expand operations.


While Qlik Talend Cloud and Qlik Answers are scheduled for general availability by the end of summer, next on Qlik's roadmap is to enable customers to model, query and analyze their structured and unstructured data together in one location, according to Capone.

Qlik has always supported structured data. Qlik Answers marks the beginning of its support for unstructured data. The next step for Qlik is to combine the two rather than keep them separate.

"Bringing together structured and unstructured data capabilities into one solution … is the holy grail of analytics," Capone said. "That will be the next thing coming."

Farmer, meanwhile, said Qlik would be wise to continue adding more capabilities that make it easy and secure for customers to develop AI models and applications. In addition, he suggested that the vendor could do more to enable edge computing and enable developers.

While some vendors provide decentralized capabilities to enable more edge computing, Qlik remains more traditional, with IT heavily involved, Farmer noted. Developers, meanwhile, haven't been a target audience for Qlik but are crucial to the expanded use of AI in the enterprise.

"They lost momentum on the developer story, which they perhaps regret now as new AI platforms are perfect for in-house developers tinkering and exploring," Farmer said.

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

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