Three insights you might have missed from theCUBE’s coverage of Alteryx Inspire
Amid the current artificial intelligence revolution, data analytics is also booming, driving innovation and transforming industries.
However, questions have emerged around data protection, workflow management, compliance and intellectual property, placing the onus on solutions providers to lay a clear blueprint for addressing these concerns and streamlining data-driven AIOps, machine learning and automation.
“One of the challenges customers have is their data is everywhere (edge, data center, cloud) and comprises objects, tables, files and other data types that use different formats, have different metadata associated with them, and generally are stovepiped,” according to Dave Vellante, co-founder and chief analyst of theCUBE Research in a recent Breaking Analysis segment. “The modern data stack begins to address this problem from an infrastructure standpoint as cloud resources are much more easily deployed and managed.”
At the recent Alteryx Inspire event, theCUBE Research analysts spoke with insiders, experts and industry professionals for cutting-edge data analytics insights. TheCUBE’s exclusive interviews, now available for streaming, touch on Alteryx Inc.’s expanded AI capabilities, active steps to address issues in bias and compliance, and the need for a community-centric approach within the industry — among others. (* Disclosure below.)
Here is a roundup of three things you might have missed during the Alteryx Inspire event:
1. Alteryx is contending with AI’s ethical, operational and IP-related concerns.
In Alteryx’s recent study on generative AI adoption and perception, 89% of respondents believed that standards and regulations managing AI usage (including the use of gen AI) need to be developed in their sector as transformation takes hold. This a growing issue encompassing AI bias and informational accuracy, privacy, security, compliance and intellectual property concerns. Alteryx is aware of these growing pains and is approaching them using the tool it knows best: enterprise data.
“We worry about discrimination coming out of these models. We worry about bias, trust and privacy,” said Trevor Schulze (pictured), chief digital and information officer of Alteryx, during an interview with theCUBE. “There’s so many important topics that we’re going after. I think the good news is companies like Alteryx take this very seriously. It’s actually something that I’ve been a part of working with the development team.”
Part of Alteryx’s proactive approach to dealing with these issues is a critical outlook on the implementation of responsible AI frameworks. By defining clearly where AI should and shouldn’t be used, companies are better positioned to manage risks. Similarly, they must de-prioritize high-risk applications initially in favor of high-value, manageable-risk areas. This strategic approach helps build trust and ensures that AI applications are both safe and effective, according to Schulze.
“Don’t let anyone tell you otherwise, something’s going to go wrong,” he said. “So, you go after the areas that have high value and also have risks that you can maintain and control and manage. [With a] responsible AI framework, figure out where you’re going first and maybe don’t go after those high-risk items right now, maybe that’s a bad idea.”
At the organizational level, the initiative to employ a responsible AI stance stems from the C-suite and permeates from there. According to the study, 30% of the influence driving forward gen AI strategy within organizations derives from the CEO, while the head of IT and chief information officer are at 25% and 22%, respectively.
“I’m so lucky to be in a position as a CIO where I get to see the new technologies before anyone else does,” Schulze said. “I see in real time what my product team is doing, what my product management team is thinking about. The other thing that I get to do, which is one of the best parts of my job, is I am actually out talking to other leading CIOs, CDAOs and CDOs and learning from them what their problems are and how they can use analytics.”
Here’s theCUBE’s complete video interview with Trevor Schulze:
2. Alteryx is facilitating the productization of enterprise AI.
Solutions companies face an existential crossroads: Given the rise of AI use cases across the enterprise, there’s an accompanying mandate to evolve their platforms and applications to deliver on that front.
As evidenced by the Alteryx study, the “hype phase” of AI has given way to sustained belief in its transformative qualities across the enterprise. Sixty-two percent of respondents in the study reported intentions to increase gen AI investment in the future. What real-world outcomes are those investments set to drive?
“Take the healthcare industry as an example,” said Sunil Senan, global head of data, analytics and AI at Infosys Ltd., during an interview with theCUBE. “Now with AI and gen AI, they can power the digital core and transform it into a cognitive core that understands the patients’ journeys better. Our customers are taking a bigger purpose and objectives with consumers and society at large to see how to drive this transformation.”
Being a large consulting outfit gives Infosys insight into enterprise digital transformation. The combination of the current data boom and AI’s maturation is opening up a world of operational possibilities across industries, Senan added.
“Our work with Alteryx is to be able to use that foundation of process mining and understanding how business processes are being run, how to infuse data and AI into that,” he said. “Brand profitability is a great example of where we leverage Alteryx’s innovation to be able to build the brand profitably as a solution on top. Our partnership with Alteryx is helping us curate these industry solutions together and engage in a collaborative way where we can bring these innovations to our common customers.”
Here’s theCUBE’s complete video interview with Sunil Senan:
3. Alteryx expands the AI horizon by driving efficiency and outcome realization.
More than examining gen AI and data-driven analytics in theory, the event explored real use cases and solutions the Alteryx platform is solidifying. Examples range from Infosys’ Topaz as a playbook for ensuring AI-ready enterprise data to Fender Musical Instruments Corp. and its analytics-based approach to productivity in music.
Underpinned by Infosys Cobalt cloud, Topaz allows for advanced analytics, delivers cognitive solutions and facilitates intuitive experiences for companies to revitalize growth. The platform spans over 150 pre-trained models and 10 AI platforms and relies on the Alteryx platform for data wrangling made possible through Auto Insights. Powered by machine learning algorithms, the capability streamlines data workability, allowing companies deeper insights into their business at a skeletal level, according to Gopal Sugavanam, vice president and data analytics practice head at Infosys.
“Alteryx is a very important capability … it is helping democratize data for insights and analytics,” Sugavanam said in an interview with theCUBE. “Alteryx provides an easy way for us to organize, massage the data, what they call ‘wrangle,’ and profile it so that we make it consumable. It’s [the] Auto Insights that Alteryx provides which helps us create those insights from the data we are looking into that help a business user make better decisions.”
The Fender example shows a harmonious blend between the science of AI and the art of making music. Known for its catalog of expertly crafted instruments, Fender is revamping operations with a company-wide transformation helmed by cloud, AI and a customer focus.
“We are big fans of Alteryx … everything came to fruition where we are all going through this transformation together,” said Cliff Kim, vice president of strategy, growth and analytics at Fender, in an interview with theCUBE. “It’s centered around AI, centered around the cloud, centered around all of these pieces that we’re trying to put together, ultimately thinking about the consumer and the customer to move it forward that we’re all passionate about.”
A big chunk of that transformation is automation. Fender is supercharging the task completion experience for a variety of customers using high-value insights made possible by data, according to Kim.
“The new norm is you can use data to make these decisions,” he said. “You can complain … ‘OK, I need more. I want to digest more. I want to have more.’ Because these things are really important to making decisions. Otherwise, we’re going to lean on things that are like N=1, where my own experience is going to change the way that the entire company runs the business.”
Alteryx saves time and allows for greater focus on improving various aspects of the business, according to Paula Hansen, president and chief revenue officer of Alteryx. It significantly reduced data loading time, enabling quicker insights and better customer service for Fender.
“A big launch today with our co-pilot to make analytics easier to use yet again even further,” Hansen said. “That’s being driven by feedback from customers that have convinced us that that’s the wave of the future. We’ve just got to keep lowering the barrier, making it easier, making it possible for data to be democratized. We will always take the feedback and put that into our development strategy.”
Here’s theCUBE’s complete interview with Cliff Kim and Paula Hansen:
Watch theCUBE’s full coverage of Alteryx Inspire here:
(* Disclosure: TheCUBE is a paid media partner for the Alteryx Inspire event. Neither Alteryx, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
Photo: SiliconANGLE
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