Jumpstart Snowflake a step-by-step guide to modern cloud analytics

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, o...

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Bibliographic Details
Main Author: Anoshin, Dmitry
Other Authors: Shirokov, Dmitry, Strok, Donna
Format: eBook
Language:English
Published: Berkeley, CA Apress L.P. 2020
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
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245 0 0 |a Jumpstart Snowflake  |b a step-by-step guide to modern cloud analytics  |c Dmitry Anoshin, Dmitry Shirokov, Donna Strok 
260 |a Berkeley, CA  |b Apress L.P.  |c 2020 
300 |a 270 pages 
505 0 |a Virtual Warehouse Considerations -- Query Design -- Caching Impacts -- Scaling -- Building a Snowflake Virtual Warehouse -- Creating a Virtual Warehouse -- Starting, Resuming, Suspending, and Resizing -- Using a Warehouse -- Setting Up Load Monitoring -- Understanding Load Monitoring -- Best Practices for Load Monitoring -- Summary -- Chapter 4: Loading Bulk Data into Snowflake -- Overview of Bulk Data Loading -- What Is Bulk Data Loading? -- Bulk Load Locations -- Supported File Formats and Encoding -- Compression Handling -- Encryption Options -- Bulk Data Loading Recommendations 
505 0 |a Intro -- Table of Contents -- About the Authors -- Acknowledgments -- Chapter 1: Getting Started with Cloud Analytics -- Time to Innovate -- Key Cloud Computing Concepts -- Meet Snowflake -- Summary -- Chapter 2: Getting Started with Snowflake -- Planning -- Deciding on a Snowflake Edition -- Choosing a Cloud Provider and Region -- Examining Snowflake's Pricing Model -- Other Pricing Considerations -- Examining Types of Snowflake Tools -- Snowflake Web Interface -- SnowSQL -- JDBC and ODBC OS Platform Requirements -- Third-Party Partners -- Creating a Snowflake Account 
505 0 |a Loading Data Continuously -- Snowpipe Auto-Ingest -- Building a Data Pipeline Using the Snowpipe Auto-Ingest Option -- Snowpipe REST API Using AWS Lambda -- Summary -- Chapter 7: Snowflake Administration -- Administering Roles and Users -- Enforcement Model -- Working with Roles and Users -- Administering Resource Consumption -- Virtual Warehouse Usage -- Data Storage Usage -- Data Transfer Usage -- Administering Databases and Warehouses -- Managing Warehouses -- Managing Databases -- Zero-Copy Cloning -- Administering Account Parameters -- Administering Database Objects 
505 0 |a Connecting to Snowflake -- Logging Into the Snowflake Web Interface -- Touring the Web Interface -- Databases Page -- Warehouses Page -- Shares Page -- Worksheets Page -- History Page -- Partner Connect Page -- Help Menu -- User Preferences Menu -- Summary -- Chapter 3: Building a Virtual Warehouse -- Overview of Snowflake Virtual Warehouses -- Warehouse Sizes and Features -- Choosing the Right Size -- Concurrency -- Default Virtual Warehouses in Sessions -- Multicluster Virtual Warehouses -- Overview of Multicluster Virtual Warehouses -- Multicluster Credits and Usage 
505 0 |a File Preparation -- File Sizing -- File Splitting -- CSV File Preparation -- Semistructured Data File Preparation -- File Staging -- Loading -- Querying Staged Files -- Bulk Loading with the Snowflake Web Interface -- Summary -- Chapter 5: Getting Started with SnowSQL -- Installing SnowSQL -- Configuring SnowSQL -- Connection Settings -- Configuration Variables -- Configuration File Example -- Command-Line Example -- Executing Variables in an Active Session -- SnowSQL Commands -- Multiple Connection Names -- Data Loading with SnowSQL -- Summary -- Chapter 6: Continuous Data Loading with Snowpipe 
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700 1 |a Strok, Donna 
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520 |a 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. You will: 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