Prerequisite: None

Jason Hughes

Director of Product Management

Dremio

Data consumers need data for BI and analytics to make business decisions, but for most organizations, their current data infrastructure isn’t keeping up with demand. Developing analytics and getting them into production takes weeks to months, and data tied to proprietary formats makes it difficult to support different types of analytics, such as BI and data science. Data teams struggle with brittle data pipelines, stale data, slow turnaround, and increasing costs.

A data lakehouse built on an open data architecture enables data users to access data in their data lake directly via SQL queries, simplifies complexity, and makes life easier for data teams. Learn why more organizations are moving their analytics and BI to an open data lakehouse and how you can build a successful lakehouse strategy.