A practical introduction to data engineering on the powerful Snowflake cloud data platform.</b>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</i>, Snowflake Data Superhero Maja Ferle</b> shows you how to get started.In Snowflake Data Engineering</i> you will learn how to:Ingest data into Snowflake from both cloud and local file systems</li>Transform data using functions, stored procedures, and SQL</li>Orchestrate data pipelines with streams and tasks, and monitor their execution</li>Use Snowpark to run Python code in your pipelines</li>Deploy Snowflake objects and code using continuous integration principles</li>Optimize performance and costs when ingesting data into Snowflake</li></ul>Snowflake Data Engineering</i> reveals 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. Throughout, author Maja Ferle</b> shares design tips drawn from her years of experience to ensure your pipeline follows the best practices of software engineering, security, and data governance.

Earlier this month I attended the two days International Master Class in Strategic Intelligence executed by Rodenberg Tillman & Associates…