This workshop is focused on allowing the participants to experience how to process and engineer data efficiently in Snowflake.

Working knowledge of data engineering basics would be a plus.
Applicable to students, working professionals and PMETs.

What you'll learn

Learners will get an understanding of the fundamental concepts, design considerations, and best practices for stakeholders using the Snowflake Cloud Data
Platform. The course will consist of lectures and demos. Below are some of the key take-away participants can have post the session. 

Key Takeaways

• Illustrate the unique and differentiated architecture of the Snowflake Cloud      Data Platform
• Load and transform data
• Evaluate Query Constructs and DDL & DML Operations
• Review Snowflakes broad SQL support for data analysis

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Course Duration

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Course Plan

This is the first step into understanding what Snowflake is and why it is such a powerful tool. We will explore Snowflake from a business perspective and then look at it from a technical perspective. Along the way crafting out a strong use case of using Snowflake as a Data
Warehousing tool.
Introduction to Snowflake
Snowflake Technical Overview
Cloud Services Layer
Storage Layer
Compute Layer

After understanding why we need Snowflake, we now take a look at utilising the languages of DDL and DML for snowflake. We will have a look at how queries can be formed using these languages.
Data Description Language (DDL)
Data Manipulation Language (DML)

Your journey into learning more about Snowflake is not complete without looking at how we can use it for analysis and take a look at the best practices when using it.
SQL Support and Query Best Practices
SQL Analytic Functions

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