После прохождения этих курсов я уверенно создаю профессиональные визуализации и дашборды.
Shoebur RahmanСпециалист по закупкам, Giz Bangladesh
Описание курса
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.
Предварительные требования
Для этого курса нет предварительных требований
Программа
План курса
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 XP
- What we'll cover in this course50 XP
- Modern data engineering with Snowflake50 XP
- You've probably done some data engineering in the past50 XP
- How to successfully complete the course50 XP
- Preparing your development environment50 XP
- Build a really simple data pipeline in Snowflake50 XP
- Chapter 1 review - Question 150 XP
- Chapter 1 review - Question 250 XP
- Chapter 1 review - Question 350 XP
- Chapter 1 review - Question 450 XP
- Chapter 1 review - Question 550 XP
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
Курс
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