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Snowflake launches Dynamic Tables
Better seamless Data Engineering in Snowflake
Snowflake just announced the release of Dynamic Tables, a revolutionary feature for simplifying declarative data transformation pipelines[1].
Also just a few days back Snowflake announced pretty interesting new features especially for Data Engineers like reading files with a Java, Scala or Python function or procedure handler and Snowpipe streaming replication support.
Snowflake now provides foundational elements for seamless Data Engineering by providing dynamic tables. They provide a streamlined and efficient approach to transforming data for use, eliminating the need for complicated task sequencing, dependency monitoring, and scheduling[1]. By defining the desired end state of the transformation using dynamic tables, Snowflake is able to manage the intricacies of the pipeline.
When you create a dynamic table, you define the query that will be used to transform data from one or more base or dynamic tables. An automated refresh process is then responsible for regularly…
