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A practical introduction to data engineering on the powerful Snowflake cloud data platform.
Data engineers create the pipelines that ingest raw data, transform it, and funnel it to the analysts and professionals who need it. The Snowflake cloud data platform provides a suite of productivity-focused tools and features that simplify building and maintaining data pipelines. In Snowflake Data Engineering, Snowflake Data Superhero Maja Ferle shows you how to get started.
In Snowflake Data Engineering you will learn how to:
Ingest data into Snowflake from both cloud and local file systems
Transform data using functions, stored procedures, and SQL
Orchestrate data pipelines with streams and tasks, and monitor their execution
Use Snowpark to run Python, Java, and Scala code in your pipelines
Deploy Snowflake objects and code using continuous integration principles
Optimize performance and costs when ingesting data into Snowflake
With this practical guide you’ll build the skills you need to create effective data pipelines on the Snowflake platform. You’ll see how Snowflake makes it easy to work with unstructured data, set up continuous ingestion with Snowpipe, and keep your data safe and secure with best-in-class data governance features. Along the way, you’ll practice the most important data engineering tasks as you work through relevant hands-on examples.
Author Biography
Maja Ferle is a seasoned data architect with more than 30 years of experience in data analytics, data warehousing, business intelligence, data engineering, data modeling, and database administration. She holds the SnowPro Advanced Data Engineer and the SnowPro Advanced Data Analyst certifications. She is also a Snowflake Subject Matter Expert and a Snowflake Data Superhero.
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