Snowflake and DataRobot: No “Cooler” Tech Stack
James Lawson
Director, Programmes at Helsing - AI to serve our democracies I Chairman at ASI | Former SpAd
I recently had the opportunity to speak at a number of Data For Breakfast events as part of DataRobot’s strategic partnership with Snowflake. The event series delivers content and best practices on advancements in cloud data analytics and data science. Since I usually skip breakfast – intermittently fasting in a desperate attempt to be healthy – I was glad to find intellectual nourishment was on the menu too, complementing the generous rashes of bacon and three-egg omelets! Understandably, under the current circumstances, the remainder of the live Data For Breakfast events have been postponed (good news below, though), but the opportunity to combine DataRobot and Snowflake remains as strong as ever.
The Value of Snowflake
Snowflake offers a leading cloud-based data management platform. It helps organizations get value out of their data with a single data warehouse, secure governed access across their network, and offers a flexible architecture for different data workloads. Since its general release in mid-2015, Snowflake has enjoyed outstanding success, earning the trust of more than 3,400 customers, with continued rapid growth.
The Value of Snowflake, Coupled with the Leader in Enterprise AI
Most executives recognize that AI is a massive opportunity for their businesses, but implementation is easier said than done. Many organizations struggle with data preparation, building AI models, and managing these assets in production. Executives look to IT departments (and skilled Snowflake users) as potential heroes who can help them address these challenges and instill best practices.
To help overcome these data management-related obstacles, Snowflake and DataRobot have joined forces. The combination of the two platforms is simple to use, highly scalable regardless of business requirements, and can be set up quickly. Both components of this tech stack are cloud native. Both platforms were built for the cloud. Both can be used on your choice of cloud vendor. Both are respective leaders in their fields. Unlimited storage and computing capabilities enable you to feed your AI with the data it needs. Furthermore, Snowflake and DataRobot are seamlessly connected with read and write-back capabilities.
Register for a Virtual Data for Breakfast!
While in-person events may be sidelined, there are still great opportunities to learn more about this leading tech stack. We can’t supply the bacon and eggs any longer, but hope to provide the intellectual nourishment to complement your coffee at home!
Register for the March 31, 2020 virtual Data For Breakfast, or if that does not work well for you, be sure to register for the April 28, 2020 option.
In APAC? We have you covered too - Register for our April 22, 2020 virtual event.
This is a repost of an article I wrote for DataRobot here
Senior Machine Learning Engineer at Integer Technologies
4 年#snowbot