This is a technical, hands-on course that teaches learners how to build modern and continuous data pipelines with Snowflake. It focuses specifically on the most practical Snowflake concepts and tools to get learners up and running quickly with building data pipelines.
Introduction to Modern Data Engineering with Snowflake
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Introduction to Modern Data Engineering with Snowflake
Instructor: Snowflake Northstar
1,960 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.7
(37 reviews)
Intermediate level
Recommended experience
6 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
How to use Snowflake to ingest data at scale, perform data transformations against data, deliver data products, and orchestrate data pipelines
Skills you'll gain
Details to know
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Recently updated!
September 2024
Assessments
5 assignments
Taught in English
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There are 5 modules in this course
Learners understand how the explosion of data in recent years has led to an increased demand for extracting insights from that data, giving rise to data engineering. They'll understand previous data engineering approaches, modern data engineering approaches using Snowflake, and contextualize data engineering with the Ingestion-Transformation-Delivery ("ITD") framework. They also prepare their development environment and build a simple data pipeline with Snowflake.
What's included
6 videos2 readings1 assignment
Learners learn how to ingest data into Snowflake at scale using various, powerful techniques. They specifically load data into Snowflake using the Snowflake Marketplace, the Snowflake web interface (Snowsight), the Snowflake CLI, and the powerful COPY INTO SQL command. Learners also understand how to ingest data from external systems using Snowflake native connectors, and how to optimize data ingestion by fully utilizing a virtual warehouse.
What's included
9 videos3 readings1 assignment
Learners perform data transformations using SQL or Snowpark for Python. Learners also understand that they can use Snowpark to perform data transformations with Java and Scala. They also extend their knowledge of data transformations by learning about, creating, and using user-defined functions (UDFs), stored procedures, streams, and Snowflake Dynamic Tables. They also learn how to perform data transformations using these tools outside of Snowflake, specifically in Visual Studio Code using Snowflake's official extension.
What's included
9 videos1 reading1 assignment
Learners understand what orchestration means, and how to add automation to data pipelines using tasks. They specifically learn about user-managed and serverless tasks, and create tasks to automate calls to stored procedures. They also create and link tasks together to form a task graph, or DAG, and execute individual tasks and entire DAGs.
What's included
5 videos1 reading1 assignment
Learners understand what orchestration means, and how to add automation to data pipelines using tasks. They specifically learn about user-managed and serverless tasks, and create tasks to automate calls to stored procedures. They also create and link tasks together to form a task graph, or DAG, and execute individual tasks and entire DAGs.
What's included
5 videos3 readings1 assignment
Instructor
Instructor ratings
4.9 (14 ratings)Offered by
Recommended if you're interested in Software Development
Amazon Web Services
Coursera Project Network
Universidad Nacional Autónoma de México
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Frequently asked questions
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