The most successful generative AI deployments run on modern data ecosystems. And at Snowflake Summit 2024, hosted in San Francisco, experts emphasized that any digital transformation effort requires data — the better the data assets, the stronger the insights for business stakeholders.
Snowflake’s mission has been to give companies an easy-to-use, unified platform, and it’s working: 92 percent of companies report better business value from data investments, according to Forbes. But look deeper, and there are actually “a lot of other products that exist, that surround Snowflake and feed it with information,” said Paul Zajdel, vice president and general manager for data and analytics at CDW.
Picture a constellation of different tech partners and system integrators. “It’s the hub. It’s a single source of truth,” but that output is the result of “many other tools working together,” Zajdel said.
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Redefining a Modern Data Ecosystem
“When we talk about a modern data ecosystem, it's not just the data cloud. It's the data pipelines. It's about how we are integrating the data? How are we serving up the data? How are we storing the data? It’s the computing power,” said Wendi O’Neill, senior director of data and analytics presales at CDW.
A modern data platform can also be defined by a set of capabilities, such as “elasticity, scalability, self-service,” said John Bland, head of cybersecurity strategy at Snowflake. Consolidation and simplification are also key to making data management less burdensome. And finally, interoperability is key so that users can leverage “best of breed applications and tools,” he said.
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How Modern Data Fits with Your IT Infrastructure
Rather than thinking of a modern data ecosystem as one part of a whole, Zajdel described it as being intrinsically connected with an enterprise’s entire IT infrastructure. It supports both cloud and on-premises environments, with seamless data flow between the two. And rather than being siloed, data is integrated and pulled from multiple sources.
Meanwhile, application programming interfaces and pre-build connectors do the work of integrating a company’s data into various enterprise systems, including enterprise resource planning, customer relationship management and other business applications. This lets users work with Snowflake but also access their data from Microsoft, Google, CrowdStrike or Palo Alto Networks platforms to name a few.
How Three Companies Found Data Success
When Fidelity consolidated its data into its Enterprise Analytics Platform, which is engineered using the Snowflake Data Cloud, IT leaders noticed an immediate improvement. Suddenly, all of the data was comprehensively managed. Due to the platform’s high processing power capabilities, it was able to support diverse data sources (structured, semi-structured and unstructured) and various ingestion methods (batch, real-time and streaming). Scalable storage solutions were an added perk.
DHL had a similar success story in 2022 when the logistics courier invested in a major digital transformation. After partnering with Snowflake to get its data in a modern ecosystem, DHL was able to extract more analytics from its average of 4 million queries per day, and it was also able to refine 15 to 25 data analytics use cases pertaining to its operations that were compute-intensive, explained Olga Sholomitskaya, vice president, head of BICOE (Global) at DHL Express.
Aflac had a positive breakthrough after a long period of friction with its data. The company’s analysts had been experiencing hours of delay in running data queries. The insurance firm asked Snowflake to help it build a data lake to contain the market and operational data from all of its systems and platforms.
“We’ve given our global investment teams at Aflac the ability to run models without having to wait for hours. Snowflake has removed our technological bottleneck,” said Ravishankar Radhakrishnan, director and head of global investments IT at Aflac.
In addition to a 50 percent savings on database software and infrastructure, the insurance company gained access to real-time investment analysis and stronger security and compliance to protect its trove of sensitive data.
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Looking at Your Data Holistically
This framework is the future of data management, providing IT leaders with a powerful, integrated solution that enhances efficiency, collaboration and innovation.
“We realize we have to get to value,” said Phil Andriyevsky, principal and head of data analytics in the wealth and access management sector for EY. But getting there requires taking “incremental steps” as IT leaders manage and analyze their data, he said. “We’re looking at the holistic journey.”
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