NEW! Verisk Native Application in Snowflake Marketplace
Learn MoreIn this episode of The Marketing Rapport, host Tim Finnigan engages with Kieran Kennedy, Head of Marketplace at Snowflake. They discuss the importance of data democratization and how Snowflake’s marketplace plays a pivotal role in facilitating seamless data sharing. Kieran emphasizes that data is most valuable when shared and integrated, contrasting it with wine that improves in isolation. He explains Snowflake’s innovative approach to motionless data sharing, which enhances security and governance by eliminating the need to move data.
Looking ahead, Kieran shares exciting developments at Snowflake, including the introduction of Cortex and Arctic, which focus on AI and open-source models. He underscores the company’s commitment to making advanced data solutions accessible and cost-effective, thus empowering businesses to harness the full potential of their data.
The episode concludes with insights into the Snowflake Summit and the significance of the Verisk-Snowflake partnership in driving innovation in data management. Verisk Marketing Solutions recently launched our new Consumer Identity Resolution and Enrichment Application, now available within your Snowflake Marketplace instance. This native app enables streamlined access to our high-quality U.S. consumer and household data through the Snowflake data plane. By harnessing Snowflake’s robust infrastructure and Verisk Marketing Solutions’ data intelligence, you can seamlessly resolve and enrich first-party data with confidence.
Our Data Enrichment Application marks the latest milestone in our ongoing partnership with Snowflake. For the past two years, Snowflake has named Verisk Marketing Solutions a leader in their Modern Marketing Data Stack report. They invited us to build applications within their platform as an early developer, and we launched our first app in the Snowflake Marketplace in 2022.
The Role of the Snowflake Marketplace
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The Snowflake Marketplace is crucial for creating an ecosystem where companies can share data within and outside their organization. This platform facilitates business development and enhances customer insights by integrating unique data sets and applications. The marketplace allows companies to enrich their content with external data, ultimately helping them grow their businesses. This approach revolutionizes how businesses handle and utilize data, making it more accessible and valuable for decision-making and strategic planning.
“So really, my role at Snowflake is in leading the marketplace. It’s really from a business development standpoint. And really, one of the things that we are aspiring to build is the data cloud. And certainly, there’s an aspect of building this data cloud, which is a company sharing data within their organization. But then there’s also the aspect of companies sharing data outside their company and with their customers, with their clients and with their partners.”
Motionless Data Sharing Technology
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Snowflake’s motionless data-sharing technology is a groundbreaking development that eliminates the need to move data, thereby maintaining its security and governance. This innovation allows for seamless data availability across different platforms without the risks associated with traditional data transfer methods. By keeping data stationary and accessible, businesses can ensure data integrity and security while still enabling comprehensive data analysis and collaboration across different entities.
“We revolutionized this idea of having data available where you don’t have to move it around. So then you keep the security, the governance, and its motionless sharing if you will. […] If someone asked me for some data a few years ago, I would email them an Excel spreadsheet. The minute you do that, the spreadsheet gets out of sync, it breaks, and things like that.”
Addressing Data Silos and Integration Challenges
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One of the significant challenges in data management is the presence of data silos, which hinder the effective use of external data. Snowflake addresses this issue by providing a semantic layer that facilitates the seamless integration and movement of data across various platforms, such as AWS and GCP. This capability is essential for gaining new insights, especially in understanding consumer behavior post-COVID, where data from multiple sources is necessary to get a complete picture.
“So you can have it in AWS, you can have it in GCP, but you need that layer that allows you to seamlessly move around. One of the big things that a lot of firms and a lot of companies are struggling with is how to get new insights. If you look at it, people are really, particularly post-COVID, trying to understand consumer behavior. Are people just ordering everything online, or are they going back out to stores, or is it a little bit of both?”
Snowflake’s Focus on AI and Machine Learning
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Snowflake is heavily invested in AI and machine learning, recognizing their fundamental role in modern data strategies. The focus is on bringing computational work to the data to avoid breaks in data linkage that occur during transfer. This approach ensures that data remains intact and secure while enabling advanced analytics. The company believes that a solid data strategy is a prerequisite for an effective AI strategy, emphasizing the need for data to be analytic-ready for creating large language models (LLMs) and other AI applications.
“There’s a lot of buzz around AI and ML. And what does that mean? And how does that manifest itself? Our position is we can play a fundamental role in that. What we fundamentally believe in is bringing work to the data instead of bringing data to work.”
[00:01:42] Kieran Kennedy: “Data doesn’t get better when it’s sitting alone by itself in a cold, dark room, it’s best when it’s distributed and term we use it Snowflake a lot is, when it’s democratized”
[00:05:17] Kieran Kennedy: “If you look at, people are really, particularly post-COVID, trying to understand consumer behavior. Are people just ordering everything online or are they going back out to stores or is it a little bit of both?”
[00:07:45] Kieran Kennedy: “What we fundamentally believe in is bringing work to the data, instead of bringing data to work because once you move the data to address the work, that’s when the breaks in the linkage happen.”
[00:08:11] Kieran Kennedy: “In order for you to have an AI strategy, you have to have a data strategy. It first comes with, you need to have data that is analytic ready. In order for you to create LLMs and things like that.”
[00:09:52] Kieran Kennedy “One of the primary use cases we see with our clean rooms is […] it really starts with hygiene. How do I clean it up? And then you do the identity resolution, and then you go off into segmentation, activation, and measurement.”
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