The idea of a data lake is to have a single store of all data in the enterprise ranging from raw data to transformed data, which is used for various tasks including reporting, analysis, visualization, and machine learning. One of the key “V”s of a data lake that never gets old, is Volume. So, how do you build a data lake which not only can store terabytes to petabytes of data but also provides an interactive fast query performance at this scale?
Join this live webinar as we share how Snowflake provides interactive query response on billions of records and learn;
- Physical organization of data in micro-partition architecture
- How to enforce physical organization of data based on my domain expertise.
- How do I run fast queries on top of my data in external data lake like S3, Azure Blob?
- How to make a decision when it comes to Cost vs. Performance