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Jumpstart Snowflake = a step-by-step...

Anoshin, Dmitry.

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Jumpstart Snowflake/ by Dmitry Anoshin, Dmitry Shirokov, Donna Strok.
Reminder of title:	a step-by-step guide to modern cloud analytics /
Author:	Anoshin, Dmitry.
other author:	Shirokov, Dmitry.
Published:	Berkeley, CA :Apress : : 2020.,
Description:	xiii, 267 p. :ill., digital ;24 cm.
[NT 15003449]:	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 SnowSQL -- 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.
Contained By:	Springer eBooks
Subject:	Data warehousing. -
Online resource:	https://doi.org/10.1007/978-1-4842-5328-1
ISBN:	9781484253281

Jumpstart Snowflake = a step-by-step guide to modern cloud analytics /
Anoshin, Dmitry.

Jumpstart Snowflakea step-by-step guide to modern cloud analytics /[electronic resource] :by Dmitry Anoshin, Dmitry Shirokov, Donna Strok. - Berkeley, CA :Apress :2020. - xiii, 267 p. :ill., digital ;24 cm.

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 SnowSQL -- 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.

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.

ISBN: 9781484253281

Standard No.: 10.1007/978-1-4842-5328-1doiSubjects--Topical Terms:

606996
Data warehousing.

LC Class. No.: QA76.9.D37 / A567 2020

Dewey Class. No.: 005.745

Jumpstart Snowflake = a step-by-step guide to modern cloud analytics /
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245 1 0 $a Jumpstart Snowflake $h [electronic resource] : $b a step-by-step guide to modern cloud analytics / $c by Dmitry Anoshin, Dmitry Shirokov, Donna Strok.
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505 0 $a 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 SnowSQL -- 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.
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.
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700 1 $a Shirokov, Dmitry. $3 3446668
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