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Alteryx unveils generative AI engine, Analytics Cloud update

The longtime data management vendor developed a new AI engine that incorporates generative AI. It also unveiled new capabilities for the cloud-based version of its platform.

Alteryx on Wednesday introduced a new engine that combines the vendor's existing AI and machine learning capabilities with generative AI and large language models in a move aimed at improving efficiency and productivity.

In addition, the longtime data management and analytics vendor revealed new cloud migration, governance and location intelligence features for its Analytics Cloud, the cloud-based version of Alteryx's platform.

Analytics Cloud, first generally available in February after nearly a year in preview, includes Designer Cloud, a self-service tool set that enables customers to automate data management and analytics workflows; Auto Insights, a decision intelligence tool that automatically surfaces insights that might otherwise never be discovered; and Machine Learning, where users can build AI and ML models.

Analytics Cloud also includes capabilities from data wrangling vendor Trifacta, which Alteryx acquired for $400 million in January 2022.

Alteryx introduced its new AI engine, called Aidin, and the new features in Analytics Cloud during Inspire, the vendor's user conference, held in Las Vegas this week.

The first Aidin capabilities are now generally available, as are the new Analytics Cloud capabilities.

Adding AI

When applied to data management and analytics, the promise of generative AI and large language models (LLMs) is ease of use that enables more people to use the advanced technologies.

Historically, working with data -- whether querying data for analysis, developing AI and ML models, or building data management pipelines -- has required users to know coding languages. Even the advent of natural language processing still required some data literacy, given the limitations of what NLP tools could comprehend.

As a result, analytics use within organizations has been stuck at about a quarter of all employees for more than a decade.

But LLMs from OpenAI and other generative AI vendors have much broader vocabularies than the NLP tools developed by analytics and data management vendors. So instead of forcing users to use precise phrasing to work with data, LLMs enable truer natural language engagement, potentially allowing business users of all skill levels to use data in their workflows.

In addition, as more employees within organizations work with data, the capabilities of tools developed through integrations with generative AI become smarter given the larger sample size from which they have to learn.

When OpenAI released ChatGPT in November, it was a leap in generative AI capabilities. Since then, many platform updates from data management and analytics vendors have included tools that combine the vendors' existing AI capabilities with those of LLMs. In the second week of May alone, Informatica, Tableau and ThoughtSpot unveiled new generative AI capabilities.

Now, it's Alteryx's turn with the introduction of Aidin in a move that could deliver on much of the promise NLP has long held, according to David Menninger, an analyst at Ventana Research.

"Generative AI/LLMs could be the great equalizer for data management vendors," he said. "They can provide auto-generated insights, which may meet the analytics requirements for many within an organization. And perhaps just as importantly, generative AI/LLMs can make all aspects of data management easier to use."

Alteryx's approach delivers on the value of generative AI/LLMs while recognizing the needs of organizations to govern these capabilities properly.
David MenningerAnalyst, Ventana Research

Alteryx's initial Aidin-infused features include Magic Document to automatically surface insights, Workflow Summary to automatically generate summaries of workflows and metadata in natural language, and an OpenAI connector to enable customers to bring generative AI and LLMs into their own workflows.

In addition, Aidin comes with governance capabilities that ensure organizations' data remains secure and that generative AI-fueled information is accurate. Given that ChatGPT has suffered data breaches and has had accuracy and other problems, those governance measures are key, Menninger noted.

"Alteryx's approach delivers on the value of generative AI/LLMs while recognizing the needs of organizations to govern these capabilities properly," he said.

Adam Wilson, senior vice president and general manager of Alteryx Analytics Cloud, said that while the unveiling of Aidin comes after numerous other data management and analytics vendors unveiled their own generative AI-infused tools, Alteryx has been working on the engine for more than a year.

Alteryx has made automation a priority in recent years. Like automation, generative AI has the potential to remove some of the manual burdens previously inherent in data and analytics operations.

Meanwhile, as Alteryx was working on developing Aidin, members of the vendor's community were developing their own integrations between Alteryx and generative AI that helped guide the vendor's roadmap.

"We're seeing some of the Alteryx community build out integrations ... with our OpenAI connector," Wilson said. "A lot of the research in the lab is intersecting with where the community is pushing us."

Analytics Cloud update

While Aidin marks Alteryx's foray into generative AI, the vendor's Analytics Cloud update represents further evolution of its emphasis on the cloud.

As recently as May 2021, Alteryx did not yet offer any cloud-based capabilities. Since then, however, a new management team led by CEO Mark Anderson has made the cloud a priority. As a result, over the course of two years, the vendor developed a full suite of cloud-based data management and analytics tools with Trifacta's cloud-native capabilities serving as the foundation.

Now, one of three new capabilities unveiled on Wednesday is aimed at helping Alteryx's on-premises customers begin migrating their operations to the cloud.

Cloud Execution for Desktop enables users to create data preparation and integration workflows with the desktop version of Alteryx Designer, and then save their work to the Analytics Cloud. They can then run and execute their workflow in the cloud.

Alteryx, which was founded in 1997, currently has about 8,000 customers, according to Wilson. While some have moved their workloads to the cloud, the vast majority still use the vendor's Desktop product.

"Cloud Execution for Desktop is a hybrid approach for users to bridge their data across all systems and help them on their cloud journey," Wilson said.

In addition to Cloud Execution for Desktop, Alteryx unveiled improved governance and added location intelligence capabilities within Analytics Cloud.

The improved governance capabilities are designed to make analytics more scalable, while simultaneously reducing risk and adding greater control with a new authentication feature.

The location intelligence capabilities, meanwhile, add a Desktop tool Alteryx is known for -- the Y and X in the vendor's name refer to geospatial coordinates -- to its cloud platform. But beyond simply re-architecting a Desktop feature for the cloud, the location intelligence capabilities build on the Desktop version by enabling users to work with geospatial data in their cloud data warehouse.

"[Users] will probably appreciate the new location intelligence capabilities, but as a practical matter, the Cloud Execution for Desktop will help with organizations transitioning to the cloud," Menninger said. "Our research shows that half of all organizations are operating their data and analytics infrastructure in a hybrid configuration, and these new capabilities help span the on-premises world and the cloud."

Looking ahead

While features fueled by Aidin are generally available now, Wilson said a significant piece of Alteryx's roadmap is to continue adding AI-powered capabilities.

In particular, the vendor plans to add conversational interfaces that enable customers to take advantage of LLMs to interact with data using free-form language rather than code or highly specific phrasing required by existing NLP tools.

"It's an opportunity to marry the low-code/no-code approach that Alteryx has historically taken with new conversational interfaces to further democratize the work," Wilson said.

Menninger, meanwhile, said Alteryx would be wise to expand its analytics operations capabilities.

Organizations are vulnerable to change as technology improves. If the tools with which they've built their analytics operations aren't able to adapt and grow as their needs change, the tools wind up holding organizations back. And the tools eventually need to be replaced, which can be expensive.

Alteryx, now featuring a cloud-native version of its platform and an AI engine that incorporates generative AI, has the potential to make organizations less vulnerable to change, according to Menninger.

"Alteryx has the opportunity to be more aggressive with its positioning in the AnalyticOps space," he said. "They are one of few vendors that can really support the constantly changing requirements of organizations' analytics processes. Hopefully we will see some of the new generative AI/LLM capabilities applied toward making these processes even more resilient."

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.

Tech News This Week 06-02-2023

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