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Alteryx, Databricks expand complementary partnership

The expanded partnership features new integrations designed to better enable joint customers to combine self-service data preparation and analysis with data science and AI.

Alteryx on Wednesday unveiled an expanded partnership with Databricks aimed at helping Alteryx users combine their domain expertise with the data science and generative AI capabilities of Databricks' tools.

Through a new integration with the Databricks Partner Connect marketplace, existing Databricks customers can now access and use a free trial of the Alteryx Analytics Cloud. This will enable customers to combine Databricks' capabilities with Alteryx data and applications with a few clicks, according to Alteryx.

Alteryx, based in Irvine, Calif., is a data management and analytics vendor whose platform is aimed at enabling business users to work with data.

In December, Alteryx reached an agreement to be acquired by private equity firms for $4.4 billion in a deal that is expected to close during the first half of this year.

Databricks, meanwhile, is a San Francisco-based vendor that helped pioneer the data lakehouse architecture for data management and has historically catered to a customer base of data experts.

Over the past year, Databricks has made generative AI a focus of its product development and acquisition strategies and is working to combine tools that enable generative AI development with its long-standing lakehouse capabilities.

To reflect that emphasis, which includes the June 2023 acquisition of MosaicML for $1.3 billion and the introduction of new vector search capabilities, the vendor is renaming its flagship tool the Data Intelligence Platform.

The partnership makes sense because it brings together two different audiences and provides them with new capabilities.
David MenningerAnalyst, ISG's Ventana Research

Given that Alteryx has a customer base of business users while Databricks provides a suite of AI-driven data infrastructure tools, the two make logical partners with their capabilities complementing one another, according to David Menninger, an analyst at ISG's Ventana Research.

"The partnership makes sense because it brings together two different audiences and provides them with new capabilities," he said.

In addition to Databricks, Alteryx maintains partnerships with Snowflake -- Databricks' closest rival -- as well as tech giants AWS, Google and Microsoft so customers can freely use the cloud platforms of their choice and are not subject to vendor lock-in.

Similarly, Databricks has partnerships with myriad data preparation and analytics vendors to likewise enable users to develop their preferred data stack.

A growing partnership

Databricks and Trifacta, which Alteryx acquired in early 2022 for $400 million, were both born out of some of the same research at the University of California-Berkeley and are longstanding partners. Through its acquisition of Trifacta, Alteryx and Databricks have now been partners for two years.

Previous integrations have enabled Alteryx customers to take advantage of such Databricks capabilities as the basic lakehouse architecture and Unity Catalog as well as Databricks SQL and Databricks Spark.

Now, from a strategic standpoint, the expanded partnership reflects a joint go-to-market effort, according to Adam Wilson, senior vice president and general manager of Alteryx Analytics Cloud. Meanwhile, from a technological standpoint, the alliance targets simplification that enables Databricks users to easily take advantage of Alteryx's capabilities, he continued.

Wilson noted that many large enterprises are adopting Databricks' platform for their data modernization needs, including developing generative AI models and applications, while Alteryx provides tools that bring business users and business use cases to that modern infrastructure.

To better bring those capabilities together, Alteryx and Databricks are now providing preconfigured trial setups for users interested in experimenting with the vendors' platforms in concert with each other.

Rather than go through a sales cycle or a formal evaluation process, Databricks users can create an Alteryx environment on their own and begin using Databricks' tools with sample data or data from Alteryx. By doing so, they can experience the correlative capabilities of Databricks and Alteryx and determine whether they want to move beyond a trial and become customers of both.

"It's a complementary partnership that we see [growing] in terms of joint customers as well as collaboration in the field," Wilson said. "[Trifacta and Databricks] had collaborated over many years before the acquisition by Alteryx. What you're seeing here is a continuation of that partnership and an amplification of it."

One of the main motivators for simplifying access to Alteryx came from customer demand, Wilson added. He noted that Alteryx was having trouble keeping up with interest from potential new customers. The integration with Databricks' marketplace solves that problem.

"I think most evaluations are done before vendors get involved anyway, either through trials or through word-of-mouth," Wilson said. "This leans into that and facilitates it."

In addition to the integration with the Databricks Partner Connect marketplace, the expanded partnership includes a new integration that lets joint Alteryx and Databricks users execute Alteryx Designer workflows with Databricks SQL and SQL Serverless.

As the cloud has become the main environment for data management and analytics, the cost of cloud computing has surprised many organizations. As a result, controlling cloud spending has become a significant initiative with vendors trying to find ways of reducing the cost of their cloud-based services and users attempting to optimize use of their cloud environments.

Serverless computing is one means of controlling costs. Serverless tools automatically scale up or down, using only the compute power needed to run workloads and so saving users from having to pay for downtime.

As a result, by using Databricks SQL and SQL Serverless to run analytics workloads, joint customers can better control their cloud spending leading to substantial savings, according to Alteryx.

Perhaps just as significant as the new access to Alteryx in the Databricks Partner Connect marketplace and potential cost savings of using Alteryx and Databricks together is the way the expanded partnership alters the relationship between the vendors, according to Menninger.

Previous integrations were about Alteryx customers gaining access to Databricks capabilities, he noted. Now, the partnership is more bi-directional.

"This announcement represents a change in the nature of the way the two products work together," Menninger said. "In the past, Alteryx could access and manipulate the data stored in Databricks, but there wasn't much cooperative processing. Now … Databricks can execute the workflows that have been created in Alteryx, providing for a much more seamless integration."

Should customers opt to combine Alteryx with their existing Databricks deployment, one of the main potential benefits includes more effectively moving generative AI projects into production, according to Alteryx.

Currently, just 10% of enterprises report having successfully operationalized a generative AI model or application, according to MIT's CDO Agenda 2024 report, which was sponsored by AWS.

Part of the problem is that organizations aren't valuing domain expertise as they attempt to build generative AI tools.

Alteryx users -- who could potentially be accountants, supply chain managers or medical researchers working with data -- possess that domain expertise. Databricks, meanwhile, has the generative AI expertise.

"Alteryx sits in a unique place in the market, very much focused on the processes behind analytics -- I refer to this aspect as AnalyticsOps," Menninger said. "It's the discipline of creating repeatable and agile processes to support analytics. These workflows can be easily modified as business requirements change."

Next steps

Moving forward, Wilson said Alteryx and Databricks will continue to expand their partnership and develop further integrations.

One area of focus for those integrations is generative AI, with Alteryx able to provide measures that address data quality while Databricks provides the tools that enable developers to build generative AI models and applications.

"If your data quality is bad then your AI is probably worthless, and God forbid that you start automating decisions based on bad data," Wilson said.

Beyond expanding its partnership with Databricks, Alteryx plans to continue developing its own generative AI tools, Wilson continued.

The vendor in May 2023 introduced a new generative AI engine -- including a conversational interface -- called Aidin, which it is working to integrate throughout its platform.

Menninger, meanwhile, said he'd like Alteryx to better integrate with data catalogs to coordinate the many systems with which Alteryx integrates.

He noted that Alteryx is frequently used along with BI platforms such as Microsoft Power BI, Qlik and Tableau to analyze data. In addition, enterprises use it with different data catalogs to organize the products used to analyze data.

With so many tools using data, lineage and quality can suffer.

"It becomes challenging to coordinate all the catalogs and the lineage of various analyses through multiple layers," Menninger said. "It would be good to see some tight integration of the different catalogs extending out to the analyses themselves."

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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