Explore the modern market of data analytics platforms and the benefits of using Snowflake computing, the data warehouse built for the cloud.
With the rise of cloud technologies, organizations prefer to deploy their analytics using cloud providers such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. Cloud vendors are offering modern data platforms for building cloud analytics solutions to collect data and consolidate into single storage solutions that provide insights for business users. The core of any analytics framework is the data warehouse, and previously customers did not have many choices of platform to use.
Snowflake was built specifically for the cloud and it is a true game changer for the analytics market. This book will help onboard you to Snowflake, present best practices to deploy, and use the Snowflake data warehouse. In addition, it covers modern analytics architecture and use cases. It provides use cases of integration with leading analytics software such as Matillion ETL, Tableau, and Databricks. Finally, it covers migration scenarios for on-premise legacy data warehouses.
What You Will Learn
- Know the 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
Who This Book Is For
Those working with data warehouse and business intelligence (BI) technologies, and existing and potential Snowflake users
Mục lục
Chapter 1: Getting Started with Cloud Analytics- Chapter 2: Getting Started with Snowflake.- Chapter 3: Virtual Warehouse.- Chapter 4: Loading Bulk Data into Snowflake.- Chapter 5: Getting Started with Snow SQL.- Chapter 6: Continuous Data Loading with Snowpipe.- Chapter 7: Snowflake Administration.- Chapter 8: Snowflake Security Overview.- Chapter 9: Working with Semi Structured Data.- Chapter 10: Secure Data Sharing.- Chapter 11: Design Modern Analytics Solution with Snowflake.- Chapter 12: Snowflake and Data Science.- Chapter 13: Migration to Snowflake.- Chapter 14: Time Travel.
Giới thiệu về tác giả
Dmitry Anoshin is a data-centric technologist and recognized expert in building and implementing business/digital intelligence solutions. He has a successful track record of implementing analytics projects in numerous industries: retail, finance, marketing, and e Commerce. He possesses an in-depth knowledge of BI, ETL, DWH, and big data technologies and is experienced in data integration processes and proficient use of various data warehousing methodologies. He completed and met deadlines for a number of multinational full BI solution life cycle implementation projects.Dmitry Shirokov is a Data Architect & Cloud Analytics Consultant at Rock Your Data, focused on digital transformation, design analytics solutions, data integration and migration, data governance, and cloud/in-house infrastructure. With over 10 years of experience in data analytics and big data, he has the breadth and depth of experience needed to build mature analytical solutions. Before joining Rock Your Data in early 2018, he worked in different companies in tech consulting and banking sectors. Previously, he held various data-engineering positions focusing on data-driven business transformation.
Donna Strok loves all things data and for over 10 years has worked in the field with companies such as Expedia Group, JPMorgan Chase and most recently Amazon. She earned her Bachelors degree in Computer Science and her Masters 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’s always on the on the hunt for exploring unique grocery stores and amazing hole-in the-wall restaurants, where some of her most memorable meals have been had.
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