Jumpstart Snowflake
Description
This book is your guide to the modern market of data analytics platforms and the benefits of using Snowflake, the data warehouse built for the cloud. As organizations increasingly rely on modern cloud data platforms, the core of any analytics framework-the data warehouse-is more important than ever. This updated 2nd edition ensures you are ready to make the most of the industry's leading data warehouse.
This book will onboard you to Snowflake and present best practices for deploying and using the Snowflake data warehouse. The book also covers modern analytics architecture, integration with leading analytics software such as Matillion ETL, Tableau, and Databricks, and migration scenarios for on-premises legacy data warehouses.
This new edition includes expanded coverage of SnowPark for developing complex data applications, an introduction to managing large datasets with Apache Iceberg tables, and instructions for creating interactive data applications using Streamlit, ensuring readers are equipped with the latest advancements in Snowflake's capabilities.
What You Will Learn
- Master key functionalities of Snowflake
- Set up security and access with cluster
- Bulk load data into Snowflake using the COPY command
- Migrate from a legacy data warehouse to Snowflake
- Integrate the Snowflake data platform with modern business intelligence (BI) and data integration tools
- Manage large datasets with Apache Iceberg Tables
- Implement continuous data loading with Snowpipe and Dynamic Tables
Who This Book Is For
Data professionals, business analysts, IT administrators, and existing or potential Snowflake users
More details
Other editions
Additional editions
Previous edition
Persons
Dmitry Anoshin is a data-centric technologist and recognized expert in building and implementing business/digital intelligence solutions with 14 years of experience working in business intelligence, data warehouse & data integration, BigData, cloud, and ML spaces across North America and Europe. He has a successful track record of implementing analytics projects in numerous industries: retail, finance, marketing, and ecommerce. He continues to lead data engineering initiatives and is currently working on a petabyte-sized data platform built using cloud and big data technologies. This platform is designed to support machine learning experiments, data science models, business intelligence reporting, and data exchange with internal and external partners, while handling privacy compliance and security-critical data sets. He also teaches a cloud computing course at the University of Victoria, mentors high school students, and helps people engineer their data career from scratch at Surfalytics.com.
Dmitry Foshin is a lead data engineer with more than 12 years of IT and Big Data experience. He focuses on delivering business insights through adept data engineering, analytics, and visualization. He excels in leading and executing full-stack big data analytics solutions, from ETL processes to data warehouses, utilizing cloud technologies and modern BI tools. Co-author of the Azure Data Factory Cookbook , Dmitry has launched successful data analytics projects for the leading international corporations.
Donna Strok loves all things data, and for more than 10 years, she has worked in the field with companies such as Expedia Group, JPMorgan Chase, and Amazon. She earned her bachelor degree in Computer Science and her master degree in Computer Information Systems. She resides in beautiful Seattle, WA with her cat Dwayne Johnson, and in her free time enjoys the wanderlust of world travel. She is always on the hunt for exploring unique grocery stores and amazing hole-in the-wall restaurants, where she has had some of her most memorable meals.
Content
Chapter 1: Getting Started with Modern Analytics.- Chapter 2: Getting Started with Snowflake..- Chapter 3: Continuous Data Loading with Snowpipe and Dynamic Tables- Chapter 4: Snowflake Administration and RBAC.- Chapter 5: Secure Data Sharing..- Chapter 6: Getting Started with SnowPark.- Chapter 7: Working with Iceberg Tables.- Chapter 8: Getting Started with Streamlit.- Chapter 9: Designing a Modern Analytics Solution with Snowflake.- Chapter 10: Performance Optimization and Cost Monitoring.- Chapter 11: Snowflake and Generative AI.- Chapter 12: Migrating to Snowflake.