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Programming in Snowflake Masterclass Hands-On

4.4 Filled star Filled star Filled star Filled star Empty star
Based on 242 ratings
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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

Read more

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

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

Syllabus

Introduction
This course might NOT be right for you if...
Welcome to this Course
Best Ways to Benefit from this Course
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Covers a wide range of Snowflake APIs, including SQL, Python Client, Snowpark, and Streamlit, providing a comprehensive toolkit for building applications and data pipelines
Teaches how to build real-world applications such as CDC data pipelines, hierarchical data viewers, and enhanced query profiles, offering practical skills applicable to industry projects
Explores cost optimization techniques for Snowflake, including query optimization, compute management, and storage strategies, which can lead to significant savings for organizations
Requires familiarity with security, software, and data engineering concepts, suggesting it is designed for individuals with some prior experience in these areas
Focuses primarily on SQL and Python, with limited coverage of other languages like JavaScript, C#, Java, and Scala, which may not suit learners seeking broader language exposure
Excludes data science and machine learning APIs, as well as most external integrations, which may limit its appeal to learners interested in these specific areas of Snowflake functionality

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Reviews summary

In-depth snowflake programming with real-world practice

According to students, this "Programming in Snowflake Masterclass" offers a highly comprehensive and hands-on deep dive into leveraging Snowflake's APIs for real-world applications. Learners frequently praise the instructor's deep expertise and the value of the practical labs and exercises. The course covers a broad range of APIs, including SQL, Python/Snowpark, and Streamlit, providing valuable insights for data professionals and software engineers. While generally very well-received, some reviews indicate that the pace can be challenging for those new to some concepts, and it requires an existing Snowflake account for practice. Overall, it's seen as a unique and valuable resource for mastering Snowflake programming.
Needs a Snowflake account for hands-on practice.
"Make sure you have your Snowflake free trial set up before starting."
"Requires an active Snowflake account which can be a cost factor."
"Had a bit of trouble with the initial setup steps."
Course content is updated to reflect changes.
"Appreciate how the course is updated with new Snowflake features."
"The content feels current and relevant to today's Snowflake."
"Instructor keeps the material fresh."
Building practical tools is very beneficial.
"Building the CDC pipeline project was directly applicable to my work."
"The examples for data lineage and query profile are very useful."
"Liked that the course focuses on practical, buildable tools."
Explores a wide array of Snowflake APIs.
"Covers all the key APIs I needed for my job, especially Snowpark."
"Impressed by the range of topics, from SQL scripting to Streamlit apps."
"Provides a solid overview and practical use of various Snowflake interfaces."
Instructor's deep knowledge is highly valued.
"The instructor clearly knows Snowflake inside and out; his expertise is invaluable."
"Learned so much from the instructor's real-world experience."
"The depth of knowledge shared by the instructor is phenomenal."
Practical labs are very helpful for learning.
"The hands-on exercises solidified my understanding of complex concepts."
"Loved building the real-life applications shown in the demos."
"Practical exercises are a highlight, truly hands-on."
Some learners find the pace or topics complex.
"Some sections move quite fast and assume prior knowledge."
"Found certain advanced topics quite challenging without prior background."
"Might be difficult for complete beginners in Python or data engineering."

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
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
Show steps
  • 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'
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: A Novel on Amazon
Show steps
  • 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'
Supplement your learning with a practical guide to Snowflake. This book provides real-world examples and solutions to common challenges.
View Alter Ego: A Novel on Amazon
Show steps
  • 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
Expand to see all activities and additional details
Show all seven activities
Document Snowflake Best Practices
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.
Show steps
  • 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
Apply your knowledge by building a complete data pipeline using Snowpipe. This hands-on project will solidify your understanding of data ingestion and automation.
Show steps
  • 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
Sharpen your query optimization skills by practicing with different datasets and query patterns. This will help you write more efficient and performant Snowflake queries.
Show steps
  • 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
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.
Show steps
  • 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:
Data Engineer
A Data Engineer designs, builds, and manages data pipelines, transforming raw data into usable formats for analysis. This course, with its hands-on experience in ingesting CSV and JSON data into Snowflake, building CDC data pipelines, and optimizing queries, compute, and storage, directly aligns with the responsibilities of a Data Engineer. The coverage of Snowflake APIs, SQL, and Python makes it a practical resource. A Data Engineer who takes this course will be well-equipped to contribute to data-driven decision-making. Furthermore, this course may allow Data Engineers to master their craft.
See salaries and explore the career path for Data Engineer
Cloud Data Architect
A Cloud Data Architect designs and implements data storage and processing systems in the cloud. This course, by teaching how to access, expand, and automate Snowflake through its APIs, and by covering secure data sharing and data clean rooms, helps build a foundation for this role. The course's focus on optimizing costs for Snowflake is also highly relevant. The practical skills gained in this course are valuable for anyone designing scalable and secure data solutions in the cloud. A Cloud Data Architect would benefit from the focus on automating Snowflake.
See salaries and explore the career path for Cloud Data Architect
ETL Developer
An ETL Developer builds and maintains processes to extract, transform, and load data into data warehouses. This course helps build a foundation for this career through its coverage of data ingestion from CSV and JSON files, data pipelines, and Snowpipe. The hands-on exercises on CDC data pipelines with streams and tasks, and continuous data loading with Snowpipe on S3, are directly applicable to the work of an ETL Developer. An ETL Developer can benefit from the lessons on preparing hierarchical data.
See salaries and explore the career path for ETL Developer
Data Analyst
A Data Analyst interprets data to identify trends and insights that inform business decisions. This course helps build a foundation for this career through its focus on writing medium to complex data analytics queries for Snowflake and processing semi-structured and hierarchical data. The course's emphasis on SQL and Snowflake Scripting allows a Data Analyst to extract, manipulate, and analyze data effectively. The skills gained will enhance a Data Analyst’s ability to provide meaningful reports and recommendations. The course's many hands-on exercises offer Data Analysts an ample opportunity to hone and refine their craft.
See salaries and explore the career path for Data Analyst
Database Developer
A Database Developer designs, develops, and maintains databases and database applications. This course helps build a foundation for this career by teaching SQL, Snowflake Scripting, stored procedures, and user-defined functions. The hands-on exercises on writing medium to complex data analytics queries and implementing transactions provide practical experience in database development. Database Developers may find the discussion of Snowflake APIs helpful in their tasks. The focus on SQL and Python may be especially relevant.
See salaries and explore the career path for Database Developer
Solutions Architect
A Solutions Architect designs and implements technology solutions to meet business needs. This course helps build a foundation for this career by providing a comprehensive overview of Snowflake's capabilities and APIs. A Solutions Architect can use this knowledge to design data solutions that leverage Snowflake's features, such as secure data sharing and data clean rooms. The course’s coverage of building real-life tools and apps with Snowflake APIs makes it a practical resource for designing custom solutions. The course focuses on most if not all programming APIs offered by Snowflake.
See salaries and explore the career path for Solutions Architect
Database Administrator
A Database Administrator manages and maintains database systems, ensuring their performance, security, and availability. This course supports this career through its coverage of Snowflake architecture, best practices for data and warehouses, and query optimization. A Database Administrator will find the hands-on exercises on applying best practices for compute and storage particularly beneficial. The course also covers transaction implementation and security, which are crucial aspects of database administration. The course's many hands-on exercises offer Database Administrators an ample opportunity to hone and refine their craft.
See salaries and explore the career path for Database Administrator
Data Warehouse Architect
A Data Warehouse Architect designs and oversees the implementation of data warehouse solutions. This course may be useful to such a professional by providing in-depth knowledge of Snowflake architecture, data loading techniques, and query optimization. The course's emphasis on best practices for data and warehouses, as well as cost optimization, aligns with the responsibilities of a Data Warehouse Architect. Data Warehouse Architects will be able to leverage the course to make informed decisions about Snowflake implementations. The course focuses on optimizing queries, compute, storage and overall costs for Snowflake.
See salaries and explore the career path for Data Warehouse Architect
Business Intelligence Developer
A Business Intelligence Developer designs and develops BI solutions to provide insights to business users. This course may be useful to this career by covering topics such as data analytics queries, hierarchical data processing, and visualizations with tools like Streamlit, GraphViz, and Plotly. The hands-on exercises in creating Streamlit web applications and deploying them in the cloud offers a practical approach to building BI dashboards and reports. Business Intelligence Developers may benefit from learning ways to show animated and hierarchical charts.
See salaries and explore the career path for Business Intelligence Developer
Analytics Engineer
An Analytics Engineer focuses on transforming raw data into usable datasets for analysis. This course, with its emphasis on data pipelines, semi-structured data processing, and query optimization, may be useful for such a role. The hands-on experience in building CDC data pipelines and using Snowflake Scripting allows the Analytics Engineer to streamline data transformation processes. The course may prepare Analytics Engineers to provide meaningful insights to stakeholders. The course also focuses on cost optimization.
See salaries and explore the career path for Analytics Engineer
Software Engineer
A Software Engineer designs, develops, and tests software applications. This course may be useful to a Software Engineer interested in working with data-intensive applications on the Snowflake platform. The course covers Snowflake APIs, Python, and JavaScript, helping Software Engineers to build custom applications that integrate with Snowflake. The emphasis on building real-life tools and small apps with Snowflake APIs aligns with the responsibilities of a Software Engineer. The course's coverage of Streamlit web apps may be useful to Software Engineers.
See salaries and explore the career path for Software Engineer
Cloud Engineer
A Cloud Engineer manages and maintains cloud infrastructure and services. This course enables professionals to use Snowflake, a popular cloud data platform. The course covers Snowflake APIs, best practices for data and warehouses, and cost optimization. The hands-on exercises on deploying web apps to the cloud may also be relevant. The course can help the Cloud Engineer manage Snowflake resources effectively. The course's coverage secure data sharing and data clean rooms may also be relevant.
See salaries and explore the career path for Cloud Engineer
Data Modeler
A Data Modeler designs and develops data models for databases and data warehouses. This course may be useful for this career by covering data loading, transformation, and hierarchical data processing. The course's hands-on exercises on flattening JSON data and adding constraints may also be valuable. A Data Modeler will gain insights into how data is structured and processed in Snowflake. The coverage of subjects such as file formats may be useful.
See salaries and explore the career path for Data Modeler
Data Science Manager
A Data Science Manager leads a team of data scientists and oversees data science projects. This course may equip a manager to understand the capabilities of Snowflake and how it can be used to support data science initiatives. The course may assist with managing data science projects that rely on Snowflake for data storage and processing. The course’s focus on cost optimization and best practices can inform decisions about resource allocation. The course may allow managers more insight into the work of their subordinates.
See salaries and explore the career path for Data Science Manager
Machine Learning Engineer
A Machine Learning Engineer develops and deploys machine learning models. While this course does not cover machine learning APIs directly, it may be useful to Machine Learning Engineers working with data stored in Snowflake. The course helps build a foundation for skills in data extraction, transformation, and loading, which are essential for preparing data for machine learning models. The course focuses on using SQL and Python to access and manipulate data within Snowflake. The course focuses on automating Snowflake.
See salaries and explore the career path for Machine Learning Engineer

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.
Cover image
Alter Ego
Save
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.
Alter Ego: A Novel
Paperback
$$

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Course image
Rating
4.4 Filled star Filled star Filled star Filled star Empty star
Effort
21.5 total hours
Via
Udemy
Instructor
Cristian Scutaru
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Covers a wide range of Snowflake APIs, including SQL, Python Client, Snowpark, and Streamlit, providing a comprehensive toolkit for building applications and data pipelines
Teaches how to build real-world applications such as CDC data pipelines, hierarchical data viewers, and enhanced query profiles, offering practical skills applicable to industry projects
Explores cost optimization techniques for Snowflake, including query optimization, compute management, and storage strategies, which can lead to significant savings for organizations
Requires familiarity with security, software, and data engineering concepts, suggesting it is designed for individuals with some prior experience in these areas
Focuses primarily on SQL and Python, with limited coverage of other languages like JavaScript, C#, Java, and Scala, which may not suit learners seeking broader language exposure
Excludes data science and machine learning APIs, as well as most external integrations, which may limit its appeal to learners interested in these specific areas of Snowflake functionality
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