After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
课程介绍
Learn how to build modern, continuous data pipelines with Snowflake in this hands-on course. Following the Ingestion-Transformation-Delivery (ITD) framework, you'll ingest data at scale, transform it with SQL and Snowpark, deliver data products, and orchestrate everything into automated pipelines using tasks and DAGs. You'll work the way data engineers do every day, using Snowflake alongside Visual Studio Code, GitHub, and the command line.
先修要求
本课程无先修要求
课程大纲
课程大纲
1
Modern data engineering with Snowflake
Discover how the explosion of data gave rise to data engineering, and how Snowflake reshapes the modern approach. You'll frame your work around the Ingestion-Transformation-Delivery (ITD) framework, prepare your development environment, and build your first simple pipeline in Snowflake.
- The explosion of data and the demand for insights50 经验值
- What we'll cover in this course50 经验值
- Modern data engineering with Snowflake50 经验值
- You've probably done some data engineering in the past50 经验值
- How to successfully complete the course50 经验值
- Preparing your development environment50 经验值
- Build a really simple data pipeline in Snowflake50 经验值
- Chapter 1 review - Question 150 经验值
- Chapter 1 review - Question 250 经验值
- Chapter 1 review - Question 350 经验值
- Chapter 1 review - Question 450 经验值
- Chapter 1 review - Question 550 经验值
2
Batch data ingestion with Snowflake
Ingest data into Snowflake at scale using a range of powerful techniques. You'll load data through the Snowflake Marketplace, the Snowsight web interface, the Snowflake CLI, and the COPY INTO command, pull from external systems with native connectors, and tune virtual warehouses for efficient batch ingestion.
3
Data transformations with Snowflake
Transform raw data into analysis-ready data using SQL and Snowpark for Python. You'll create and apply user-defined functions, stored procedures, streams, and Dynamic Tables, and run transformations from inside Visual Studio Code using Snowflake's official extension.
4
Delivering data products with Snowflake
Turn clean, transformed data into data products that deliver value. You'll share datasets through the Snowflake Marketplace, build and share insights with a Streamlit in Snowflake application, and deploy a Snowflake Native Application using the Snowflake CLI.
5
Orchestrating continuous data pipelines with Snowflake
Bring your pipelines to life with orchestration. You'll automate pipeline steps using user-managed and serverless tasks, link tasks into a task graph (DAG), and execute individual tasks and entire DAGs to run continuous, automated data pipelines.
R
Introduction to Modern Data Engineering with Snowflake
课程完成
