Programming in Snowflake Masterclass Hands-On

Cristian Scutaru

IMPORTANT: This course requires an It occasionally deals with advanced notions about security, software and data engineering Check the minimum Requirements for this course, and the "What is NOT Included in This Course" section below, before buying this course.

Who I Am

The only world-class expert from Canada selected for the Snowflake Data Superhero program in 2021.
SnowPro Certification SME (Subject Matter Expert): i.e. many exam questions have been created by me.
Passed four SnowPro certification exams to date (with no retakes): Core, Architect, Data Engineer, Data Analyst.
Specialized in Snowflake for the past few years, I worked for Snowflake Partner companies, and I served dozens of clients in this capacity or as an independent consultant.
Today I continue to work with Snowflake, but I am no longer affiliated with their company in any capacity. I recently left their programs to keep my professional independence.

What You Will Learn

How to access, expand and automate Snowflake through most if not ALL their existing APIs.
How to build useful real-life tools and small apps with Snowflake APIs.
How to ingest CSV and JSON data into Snowflake, through data pipelines and Snowpipe.
How to write medium to complex data analytics queries for Snowflake.
How to optimize queries, compute, storage and overall costs for Snowflake.
How to process and render semi-structured and hierarchical data and metadata in Snowflake.
I tried to cover almost

What Snowflake APIs You Will Learn About

SQL (DDL/DML/DCL) and Snowflake Scripting
Stored Procedures, User-Defined Functions (UDFs), User-Defined Table Functions (UDTFs)
Python Client, Snowpark for Python, Python Worksheets
Streamlit Web Apps, Streamlit for Snowflake, Snowflake Native Apps Framework
Secure Data Sharing and Data Clean Rooms
Sharing with private Data Exchange or public Marketplace
Snowflake

What is NOT Included in This Course

Data Science and Machine Learning APIs.
Most external integrations, such as external functions, or Kafka and Spark connectors.
Integrations with data transfer applications or other third-party partner apps.
Client driver programming in Go, PHP, Java etc.
Snowpark programming in Java or Scala.
Main focus was on SQL and Python, with small extra snippets in JavaScript, C#, Java, Scala.

Real-Life Applications You Will Learn To Build

CDC Data Pipelines with streams and tasks, or dynamic tables
Generic hierarchical data viewer
Hierarchical metadata viewer (for data lineage and object dependencies, role hierarchy, etc.)
Enhanced query profile
Script automation accessing the We’ll use then Streamlit – for many of them - to create simple web apps, local or remote. We may deploy them into Snowflake, as Streamlit Apps. Or even share them with local partner accounts, as Native Apps.
I sold tools similar to these to real-life clients and Snowflake partners.

No other course, book or documentation around - including those from Snowflake. – will offer as much insights, hands-on exercises and knowledge transfer as my course here, guaranteed.

Enroll today, to keep this course forever. And help me continue to update it with new APIs Snowflake comes frequently up with.

Enroll now

Or start a personal plan

And upskill with Udemy

What's inside

Learning objectives

Query anything in snowflake through sql and snowflake scripting
Use most if not all programming apis offered by snowflake
Access and use snowflake as a software or data developer

Build real-life tools and apps with and for snowflake
Process and access hierarchical data and metadata in snowflake data cloud

Query anything in snowflake through sql and snowflake scripting
Use most if not all programming apis offered by snowflake
Access and use snowflake as a software or data developer
Build real-life tools and apps with and for snowflake
Process and access hierarchical data and metadata in snowflake data cloud

Syllabus

Introduction

This course might NOT be right for you if...

Welcome to this Course

Best Ways to Benefit from this Course

SnowPro Snowflake Certifications: Added Material!

Initial Requirements and Project Setup

Warehouses and Cost Estimates

Hands On: Sign-up for a Free Trial Account

Hands On: Use a Very Small Warehouse

Hands On: Run Query with a Very Large Warehouse

Hands On: Just Start a Large Multi-Cluster Warehouse

Review: Overview of the Snowflake Architecture

Hands On: Apply Best Practices for Data and Warehouses

Review: Snowflake Best Practices for Compute and Storage

Check Your Knowledge

Loading and Accessing CSV Data

Hands On: Create Query Context

Hands On: Infer Schema from Staged CSV Files

Hands On: Copy Data into Tables

Hands On: Create External S3 Stage

Review: End-to-End CSV File Uploading

Review: Duplicating Table Data and Zero-Copy Cloning

Loading and Processing JSON Data

Review: File Formats

Hands On: Upload JSON Data

Hands On: Transform JSON Data

Review: JSON Data Transformations

Hands On: Flatten JSON Data

Review: JSON Data Flattening

Hands On: Add Constraints and Materialized Views

Review: Temporary Tables and Materialized Views

Sample Data Extraction and Generation

Hands On: Extract Data Samples with Snowflake

Hands On: Generate Synthetic Data with Snowflake

Hands On: Generate Synthetic Data with Python

Review: Data Sample Extraction and Generation

Review: Sequences and Identity Columns

Hands On: Snowflake Scripting Procedure with Cursor

Stored Procedures and Recursive SQL

Hands On: Prepare Hierarchical Data

Hands On: Query Hierarchical Data with Joins

Hands On: Query Hierarchical Data with Recursive SQL

Review: SQL Queries for Hierarchical Data

Hands On: Create UDFs in SQL

Hands On: Create Stored Procedure in JavaScript

Review: Stored Procedures and Functions

SQL and Snowflake Scripting

Hands On: Use Case Sensitive Identifiers

Hands On: Use Identifier References

Hands On: Access JSON Object Properties

Review: Identifiers and Variables in Snowflake SQL

Hands On: Clone Table Data

Hands On: Snowflake Scripting Procedure with ResultSet

Hands On: Snowflake Scripting Procedure Calling a JavaScript Function

Hands On: Test the Generic Hierarchical Viewer in SQL

Review: Snowflake Scripting

Hands On: Implement Transaction

Hands On: More Transaction Use Cases

Review: Transactions in Snowflake

Hands On: Show Animated Charts (with D3)

Snowflake Data Pipelines

Batch & Stream Data Transfer to Snowflake

Hands On: Manual CDC with MERGE Statement

Hands On: Enable Change Tracking on a Table

Hands On: CDC with Streams and Tasks

Hands On: CDC with Dynamic Table

Review: CDC (Change Data Capture) in Snowflake

Hands On: Continuous Data Loading with Snowpipe on S3

Review: Snowpipe on Amazon S3

Hierarchical Data Visualizations

Hands On: Transform Tabular Data into JSON Format

Review: Hierarchical Data Formats (JSON, XML, and YAML)

Hands On: Show Graphs (with GraphViz)

Hands On: Show Hierarchical Charts (with Plotly)

Streamlit Web Applications

Hands On: Create Your First Streamlit Web App

Hands On: Add Functionality with a Streamlit Tab Control

Review: Introduction to Streamlit

Review: Streamlit Layout Components and Interactive Widgets

Hands On: Cache Streamlit Data

Review: Streamlit Session and Data Caching

Hands On: Deploy and Share a Web App in Streamlit Cloud

Review: Deploying a Web App in Streamlit Cloud

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Programming in Snowflake Masterclass Hands-On with these activities:

Review SQL Fundamentals

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Solidify your understanding of SQL basics before diving into Snowflake-specific SQL extensions. This will make learning Snowflake's query language much easier.

Browse courses on SQL

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Review basic SQL syntax and commands (SELECT, INSERT, UPDATE, DELETE).
Practice writing SQL queries on sample datasets.
Familiarize yourself with relational database concepts.

Read 'Data Architecture: A Primer for the Data Scientist'

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Gain a broader understanding of data architecture principles. This book provides valuable context for understanding how Snowflake fits into a larger data ecosystem.

View Alter Ego on Amazon

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Obtain a copy of 'Data Architecture: A Primer for the Data Scientist'.
Focus on chapters related to data warehousing and data modeling.
Consider how these concepts apply to your Snowflake projects.

Read 'Snowflake Cookbook'

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Supplement your learning with a practical guide to Snowflake. This book provides real-world examples and solutions to common challenges.

View Alter Ego on Amazon

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Obtain a copy of the 'Snowflake Cookbook'.
Read through the chapters relevant to the course topics.
Try out the code examples provided in the book.

Four other activities

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Document Snowflake Best Practices

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Reinforce your understanding of Snowflake best practices by creating a comprehensive document. This will help you internalize the concepts and become a more effective Snowflake developer.

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Research Snowflake best practices for various aspects of the platform.
Organize the information into a clear and concise document.
Include examples and explanations to illustrate the best practices.

Build a Data Pipeline with Snowpipe

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Apply your knowledge by building a complete data pipeline using Snowpipe. This hands-on project will solidify your understanding of data ingestion and automation.

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Set up an AWS S3 bucket or Azure Blob Storage for data staging.
Configure Snowpipe to automatically load data from the stage into Snowflake.
Monitor the pipeline and troubleshoot any issues.

Optimize Snowflake Queries

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Sharpen your query optimization skills by practicing with different datasets and query patterns. This will help you write more efficient and performant Snowflake queries.

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Identify slow-running queries in your Snowflake environment.
Analyze the query execution plan to identify bottlenecks.
Apply optimization techniques such as indexing, partitioning, and query rewriting.

Build a Streamlit App for Data Visualization

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Create a Streamlit application that visualizes data from Snowflake. This project will combine your knowledge of Snowflake, Python, and Streamlit to build a useful and interactive tool.

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Connect your Streamlit app to your Snowflake account.
Write SQL queries to retrieve data from Snowflake.
Use Streamlit's charting libraries to create visualizations.
Add interactive widgets to allow users to explore the data.

Career center

Learners who complete Programming in Snowflake Masterclass Hands-On will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected one books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Programming in Snowflake Masterclass Hands-On.

Alter Ego

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The 'Snowflake Cookbook' provides practical recipes and solutions for common Snowflake tasks. It covers a wide range of topics, including data loading, querying, performance optimization, and security. serves as a valuable reference for both beginners and experienced Snowflake users. It offers step-by-step instructions and code examples to help you quickly solve real-world problems.

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