Snowflake for Data Engineers

2h 4m 8s
English
Paid
Snowflake is a next-generation cloud data storage solution that everyone is talking about today. The platform operates 100% in the cloud, providing flexible access to data, scaling on demand, and allowing for the integration of disparate sources, data sharing, and the execution of various analytical tasks. Snowflake is actively used by large companies, and the skill of working with this platform is becoming increasingly in demand among data engineers and analysts. To effectively use Snowflake, one must be able to prepare and integrate data, manage it within the platform, and connect with external tools and services. Therefore, knowledge of Snowflake is relevant not only for analysts but also for data engineers.
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What you will learn

In this hands-on course, you will gain all the basic knowledge needed to start working with Snowflake immediately.

  • We will start with the basics: what Snowflake is, who uses it, and how it fits into the data processing platform architecture.
  • Then you will move on to practice:
    • get acquainted with an e-commerce dataset,
    • set up Snowflake and SnowSQL,
    • create tables, file formats, and load data through internal staging areas by uploading CSV files from your computer.

You will also:

  • create visual reports in Snowflake,
  • connect Power BI to Snowflake for building dashboards,
  • learn how to execute SQL queries via Python,
  • set up and run automated tasks,
  • test a complete ETL pipeline.

Working with AWS and automation

At the end of the course, you will learn how to integrate Snowflake with AWS S3:

  • first, manually import data from external staging areas,
  • then set up automatic loading via Snowpipe.

What's included in the course

  • Source codes
  • Links to useful resources
  • Prepared data for work

Requirements

  • Knowledge of the basics of relational databases
  • AWS account for integration with S3

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# Title Duration
1 Introduction 02:07
2 Snowflake basics 04:17
3 Data Warehousing bascis 04:14
4 How Snowflake fits into data platforms 03:15
5 Snowflake Account setup 04:25
6 Creating your warehouse & UI overview 04:16
7 Our dataset & goals 03:02
8 Setup Snowflake database 10:30
9 Preparing the upload file 08:32
10 Using internal stages with snowsql 12:38
11 Splitting a data table into two tables 06:39
12 Creating a visualization worksheet 07:09
13 Creating of a dashboard 05:24
14 Connect PowerBI to Snowflake 06:04
15 Query data with Python 07:36
16 Create import task 09:19
17 Create table refresh task 03:41
18 Test our pipeline 03:15
19 Working with external stages for AWS S3 10:21
20 Implementing snowpipe with S3 06:20
21 Summary 01:04

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