Qlik launches Talend Cloud, aims to ensure data is trusted
The longtime BI vendor's new integration platform aims to deliver trust in the information users work with to inform analytics and AI models and applications.
Qlik has made data integration platform Talend Cloud generally available in an effort to enable customers to inform AI and analytics applications with trusted data.
First unveiled in preview on June 3 during Qlik Connect, the vendor's user conference, Talend Cloud was launched Monday.
The platform is a combination of capabilities from Talend, a data integration vendor that Qlik acquired in 2023, with Qlik's pre-existing data integration capabilities to form a full-featured suite for ensuring high-quality data to inform advanced models, applications and data products.
Because organizations need to ensure data quality to engender trust in the data that informs AI and analytics assets, tools such as Talend Cloud that emphasize trusted data are significant, according to Mike Leone, an analyst at TechTarget's Enterprise Strategy Group.
"Having trusted data is critical to the overall effectiveness and reliability of AI," he said. "Data needs to be of high quality and truly representative of a particular scenario without errors, gaps or biases. It also must be properly governed to maintain compliance and help organizations overcome data privacy and security concerns."
Having trusted data is critical to the overall effectiveness and reliability of AI. Data needs to be of high quality and truly representative of a particular scenario without errors, gaps or biases.
Mike LeoneAnalyst, Enterprise Strategy Group
Based in King of Prussia, Pa., Qlik is a longtime analytics vendor.
In 2018, Qlik began building up a data integration suite to complement its BI tools with the acquisition of Podium Data and followed that with acquisitions of Attunity in 2019 and Blendr.io in 2020 before purchasing Talend to round out its data integration platform.
Now, Qlik Talend Cloud is the vendor's unified integration suite for informing AI and analytics models and applications with trusted data.
New capabilities
Partly because generative AI can make it possible for both non-technical workers and data experts to use natural language interactions with data, interest in generative AI exploded.
That has spurred increased interest in traditional AI and machine learning, as well.
However, for AI -- including GenAI -- and machine learning models and applications to be of value to an enterprise, they need to deliver accurate outputs that engender trust in users. To deliver accurate outputs that leads to trust from AI consumers in AI models and applications used to inform decisions, they need high-quality data.
Qlik Talend Cloud is designed to provide that, according to the vendor.
The platform includes the following:
A suite of data integration and data quality tools designed to enable data engineers and scientists with high-quality data that can be trusted to feed AI-augmented pipelines that inform AI and analytics models and applications.
A trust score to assess the trustworthiness of AI models.
Connectivity to more than 400 data sources -- including major cloud data storage providers such as AWS, Databricks, Google, Microsoft and Snowflake -- through Qlik's connector factory, which now includes AI features to improve visibility into data as it's ingested.
Low-code and pro-code options to cater to different user profiles from business analysts to data scientists.
Tools to turn complex data sets into digestible data products.
Combined, the features that comprise Talend Cloud add up to a significant addition for Qlik customers, according to Leone.
"Between the hundreds of connectors, ability to help with data transformation, integrated AI capabilities and ability to deliver a data trust score for AI, organizations are given the capabilities necessary to deliver a trusted data foundation for analytics and AI," he said.
Kevin Petrie, an analyst at BARC US, similarly said Talend Cloud has the potential to substantially benefit Qlik customers as they develop new models and applications and update existing ones.
By providing features that enable users to set standards for data quality and trust and govern that delivery, Qlik is providing needed capabilities as interest in AI continues to rise.
"We've entered a phase in which enterprises recognize that achieving their analytics and AI innovation goals requires a new level of standardized, integrated and governed data delivery," Petrie said. "The Qlik-Talend portfolio supports this goal, given its breadth of functionality and depth of customer base."
However, even when combined with existing capabilities and made generally available in a unified package, acquired capabilities such as Talend's can sometimes be difficult to navigate in concert with those that preceded them, Petrie cautioned.
"The challenge, of course, is that it can take years to integrate acquired business units and product lines sufficiently to make things easy on enterprise adopters," he said. "I'll be interested to see how enterprise adopters respond to Qlik Talend Cloud and the overall portfolio of the combined companies for data management, governance and consumption."
Looking ahead
In addition to Qlik Talend Cloud, the vendor unveiled Qlik Answers last month.
Qlik Answers is a generative AI assistant similar to those from Qlik competitors such as MicroStrategy and Tableau that removes some of the barriers that have held analytics back from widespread use within organizations by enabling users to engage with data using natural language.
While Talend Cloud is now generally available, Answers, which relies on the foundation of trusted data provided by Talend Cloud, is still in public preview. General availability is promised for sometime this summer.
Beyond Answers, Leone said Qlik would be wise to expand the breadth of its trust score.
Currently, the tool that enables users to easily see whether models and applications can be trusted to deliver accurate outputs lives only with Qlik's data integration suite. With the vendor now developing an environment for AI development called Staige, there is ample opportunity to develop trust scores for other parts of the overall Qlik portfolio.
"While today, trust scores for AI live exclusively on the data integration side of the Qlik business, I'm hoping to see Qlik extend that to more of the AI lifecycle," Leone said, referring to AI application monitoring, MLOps and large language model operations.
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.
