Many organizations build data lakes with the goal of analyzing their data to make data-driven decisions that improve their profitability or fulfil their corporate mission. However, the reality is many data lakes end up being a great place to cheaply store data but don’t achieve their initial goal due to excess complexity and an inability to conduct simple, fast data analytics. Ultimately, such data lakes become data swamps that produce no value.

Attend this webinar to learn 10 tips for architecting a modern data lake that:

  • Acts as both a data lake and a data warehouse 
  • Offers unlimited speed and scale and allows all users to query all the data at any time
  • Stores and transforms raw data for analytical workloads
  • Is available as a simple service with minimal maintenance or complexity
  • Enables data science and data sharing initiatives
  • Joe Goldberg

    Director of Product Marketing, Snowflake

  • Saurin Shah

    Sr. Product Manager, Snowflake