How the Cloud Can Bring the Analytics and Machine Learning Divide to an End
Webinar Speaker: Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics
Date: Tuesday, March 15, 2022
Time: 12:00 p.m. PT, 3:00 p.m. ET
As organizations look to become competitive, they often want to expand the kind of analytics that they perform. For instance, in a recent TDWI survey, 64 percent of respondents stated that demand for machine learning (ML) was growing. By embedding ML in their internal and external applications, organizations can drive more value from their data to predict customer churn, optimize proactive asset maintenance schedules, and more.
Typically, the expansion into machine learning pushes organizations to stand up separate infrastructure that supports the data types and languages that data scientists use. This creates a new silo in the organization and also increases the barrier preventing analysts from participating in ML initiatives. In our surveys, however, we often see that upskilling data analysts to become data scientists is a popular path that organizations are following to build talent.
Join this TDWI Webinar to learn about:
- How to expand analytics endeavors in the cloud without creating new silos
- Building a cohesive foundation to scale ML to get the highest ROI
- The convergence of analytics and ML in cloud data platforms
Julian is a product marketer with experience in both high-growth startups and established enterprise software and infrastructure providers. Prior to Snowflake, Julian was part of Confluent during the fast-growth journey to IPO. He began his career at IBM where as a consultant, he advised large enterprises on their machine learning and analytics strategy. Julian holds an aerospace engineering undergraduate degree from Georgia Tech and an MBA from The University of Chicago. During his free time, Julian enjoys road biking around the San Francisco bay area.
Fern Halper, Ph.D.