Data Analytics

Snowflake user panel focuses on how three orgs are approaching GenAI

There is no shortage of announcements from the vendor community about how they intend to implement generative AI (GenAI) into their product offerings. It has become an almost daily occurrence, but there are fewer indications about strategic plans end-user organizations are formulating when it comes to using the breakthrough technology.

An example of what is and might be possible took place recently at the Toronto stop of Snowflake’s Data Cloud World Tour, during a panel moderated by Shannon Katschilo, the company’s Canada country manager.

She was joined by David Dadoun, head of data and analytics at Bombardier Recreational Products (BRP), Beth Quinton, vice president of data at Air Canada, and Yang Han, co-founder and chief technology officer (CTO) of StackAdapt, an advertising platform for marketers primarily used by brands and agencies.

Following introductions from each panel member, Katschilo turned her attention to Dadoun, saying, “I know it is cliché, but we know we can’t have an AI strategy without a data strategy. Given all the hype, I am interested to learn more about your AI journey at BRP.”

He replied that while “everyone in the room is excited about the benefits that we can all imagine we’re going to get from it, there are certain foundational blocks that you have to have in place before you even attempt that journey. I like to say that the ‘only thing you’re going to do without a data strategy if you embark into AI is make AI dumb, and just make the wrong decisions faster.’ That’s all you’re going to accomplish.”

Asked what impact GenAI and/or Large Language Models (LLMs) are going to have the biggest impact on at BRP, the manufacturer of a host of recreational vehicles including Ski-Doo and Lynx snowmobiles and Sea-Doo watercraft, Dadoun replied “that was the $1 million question.

“Honestly, It’s a little too soon for Gen AI to really define where it’s going to have a significant impact, although I know it will have an impact.  I have to say, we are still investigating. And there are some things I am going to keep to myself, as it stands, but there are places where we’re looking as to how best to leverage it.”

At Air Canada, Quinton said the airline’s executive team “feels we have an obligation to be investing and figuring out our strategy very quickly in the GenAI space.

“Our legal teams, our HR teams, our strategic procurement teams are already in early-phase exploratory discussions about use cases around how we automate some of the mundane tasks that wouldn’t have been possible to do nine months ago. It is now possible because of these LLM plugins.”

StackAdapt, said Han, “helps their customers execute multi channel strategies across the world from mobile, video connected TV, digital out-of-home audio, and other channels. We leverage a lot of AI and automation to ensure we execute customer goals, reach their performance objectives, and uncover customer insights.”

GenAI, he said, has the potential for every organization, regardless of size, to become more efficient by allowing it to conduct “deeper integration” with their customer base.

“No company can thrive in isolation. Data now is the lifeblood – like water for the earth. In order to have  effective solutions you need to have AI. In order to have effective AI you have to have a lot of data and to get data you need deep integration.”

According to a Snowflake fact sheet, GenAI models “break new ground, using advanced deep learning techniques to generate entirely new outputs rather than simply making predictions based on prior experience. These advances rely partly on new approaches to how models are trained, including semi-supervised and unsupervised learning. This shift from prediction to creation opens up exciting possibilities for innovation.”

At the event, Elise Bergeron, the company’s vice president of product marketing, said the Snowflake cloud, “unlocks a core data strategy for our customers, one in which all of your data is available in a single data universe that can be joined and referenced. And not just your data, but the data that matters to you in your ecosystem – from your customers, from your partners from your supply chain.

“And this is really meant to address one of the single biggest customer problems that we hear every day. And that is the data silos. These silos inhibit basic analytics, they inhibit team productivity, and they get in the way of what everyone is trying to solve right now: How do I bring GenAI to light in my enterprise.”


Compilation by Classicfurs Team


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