Qlik unveils agentic AI capabilities, launches lakehouse

Adding AI

Qlik Answers, a GenAI-powered query and response tool, was first made generally available in July 2024. At the time -- like Qlik's longstanding BI platform -- it enabled users to explore structured data to generate insights. Now, Qlik Answers is also able to explore unstructured data, such as the text and images that make up a vast majority of the data generated, and produce better-informed insights.

Mike Capone, Qlik's CEO, noted that while Qlik has had generative AI capabilities within its core analytics platform before, Qlik Answers now connects the vendor's generative AI to its entire platform.

"We really hit the unlock with the Qlik Answers technology," Capone said. "[Now] we can bring together structured data with unstructured data ... We think that's the Holy Grail."

Regarding Qlik's emphasis on supporting unstructured data after decades of supporting only structured data -- like most analytics vendors -- the pace at which unstructured data is being generated compared with structured data was a motivator, he continued.

"We were missing a lot," Capone said. "A lot of the knowledge being created in the universe is showing up in Slack, emails and PDFs. AI will become useless if you only base it on structured data."

Beyond adding support for unstructured data, users can now trigger automated decisions with Qlik Answers.

Discovery Agent, meanwhile, is an AI-powered insight generator in Qlik Cloud Analytics that autonomously scans applications and data sets to surface opportunities and risks, deliver insights with explanations about what is happening and why it matters, and suggest next steps.

"Together, Qlik Answers and Discovery Agent shift Qlik from passive reporting to proactive, embedded intelligence," Catanzano said.

However, while beneficial, Donald Farmer, founder and principal of TreeHive Strategy and a former vice president of innovation and design at Qlik, was critical of Qlik's use of the term agent to describe the new capabilities. In addition, he noted that, unlike vendors such as SAS and Domo that enable users to build agents, Qlik is not providing a development framework for agents.

"What Qlik calls agentic here is basically an enhanced form of augmented intelligence, where the AI makes discoveries in the data for you," Farmer said.

Other new capabilities

In January, Qlik acquired Upsolver to add optimization for Apache Iceberg, the open source table storage format that is often used as the foundation for data lakehouses, and real-time data ingestion capabilities. Now, Qlik is adding Open Lakehouse.

Open Lakehouse -- which enables users to store structured and unstructured data together in one system -- is a fully managed lakehouse built on Iceberg that is now part of Qlik Talend Cloud.

The lakehouse features real-time data ingestion capabilities that can handle the scale of modern workloads, an automated optimizer that compacts and clusters data to speed queries and reduce storage costs, and an open format that makes it compatible with other Iceberg-based platforms such as Snowflake, Apache Spark, Trino and Amazon SageMaker.

Open Lakehouse is a significant addition for existing Qlik users, according to Farmer. However, it is neither innovative nor a development that gives Qlik a competitive advantage, he continued.

"Qlik Open Lakehouse is a catch-up feature, which existing customers will greatly appreciate," Farmer said. "It brings Qlik up to speed with emerging best practices in data analytics architecture."

By adding Open Lakehouse, Qlik now provides capabilities from data ingestion through storage, data integration and analysis in a single platform.

Qlik customers were expressing surprise over the expense of AI development, according to Capone. Acquiring Upsolver to develop a lakehouse built on Iceberg was a response to those customers and is an attempt to help them control spending.

With the addition of an open lakehouse and more GenAI capabilities, Qlik is keeping up with what competitors are offering, according to Catanzano. However, its integration of explainable AI and multi-modal automation into a single experience may help set Qlik apart.

"By focusing not just on AI insights but on actionability and traceability, Qlik is carving out a differentiated position, particularly compared to more generalist platforms like Microsoft Copilot or Google Gemini," Catanzano said.

In addition to agentic AI capabilities and Open Lakehouse, Qlik introduced the following new capabilities:

• Multivariate time series forecasting, a feature in Qlik Predict -- formerly AutoML -- that enables users to model potential scenarios based on time series analysis of factors such as seasonality, economic conditions, pricing and campaign activity.
• Write Table, a tool that lets users update and write back data to systems such as SAP and Salesforce, so it can be synchronized across dashboards and other data products to foster collaboration.
• Table Recipe, a no-code data preparation tool that allows users to clean, convert and format data to create single-table data sets using a spreadsheet-like interface.

Time series analysis is a capability Qlik customers have been asking for and the vendor should have added before now, according to Capone.

Farmer, meanwhile, highlighted Write Table and its potential use in conjunction with agentic AI development. Again, however, he noted that BI vendors already provide write-back capabilities.

"Write Table is a foundation [agentic AI development], but it does sound as if companies like Domo and ThoughtSpot are well ahead in enabling their users to create autonomous agents," he said. "It will be important to see how Qlik pulls together Discovery Agent and Write Table."

Next steps

Since beginning its expansion beyond BI into data integration in 2018, Qlik has used acquisitions to add capabilities.

The acquisitions of Podium Data and Attunity began its development of a data integration platform, which was capped off by the purchase of Talend. Acquisitions have also fueled Qlik's addition of AI development capabilities and a data lakehouse.

More acquisitions are likely as Qlik continues to evolve with industry-specific AI and master data management potential targets, according to Capone.

Qlik is doing a solid job of providing customers with a data platform, according to Farmer. But rather than lead competitors, it is often attempting to catch up to what others are already doing, he continued.

"It increasingly feels as if they are keeping up with new developments and not leading in any space," he said. "It would be good to see some new thinking in AI or application integration, but this is a lot to ask, as more agile companies are moving quickly and Qlik has a substantial technical debt as they integrate their frequent acquisitions."

Catanzano, meanwhile, suggested that Qlik could develop collaboration between agents and add more real-time streaming capabilities. In addition, industry-specific tools and continuing to make its platform easier to use could help users.

"Continuing to simplify UX for non-technical users will be critical for widespread adoption," Catanzano said.

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.