Top Five Delta Lake Tips
Wednesday 10th July, 2019 @ 10.00 AM GMT | 11.00 AM CEST
Making quality data available in a reliable manner is a major determinant of success for data analytics initiatives: from regular dashboards or reports to advanced analytics projects drawing on state of the art machine learning techniques. Data engineers tasked with this responsibility need to take account of a broad set of dependencies and requirements as they design and build their data pipelines.
Delta Lake is an open source storage layer that brings reliability to data lakes. Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing. Delta Lake runs on top of your existing data lake and is fully compatible with Apache Spark APIs.
Join Quentin Ambard, Solution Architect at Databricks, on this webinar to share with you the best practises and tips on Delta Lake key features:
Delta Lake is an open source storage layer that brings reliability to data lakes. Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing. Delta Lake runs on top of your existing data lake and is fully compatible with Apache Spark APIs.
Join Quentin Ambard, Solution Architect at Databricks, on this webinar to share with you the best practises and tips on Delta Lake key features:
- Create a clean Data Lake with Delta: use schema enforcement and expectation to ensure data quality
- Support concurrent queries with ACID transactions: run consistent selects while data is added to the table
- Be GDPR ready: safely delete data and merge tables
- Go back in time, trace your modification and restore previous data
Presenter
Quentin Ambard
Solutions Architect, Databricks
Solutions Architect, Databricks