Jumpstart Snowflake: A Step-By-Step Guide to Modern Cloud Analytics
Anoshin, Dmitry, Shirokov, Dmitry, Strok, Donna
- 出版商: Apress
- 出版日期: 2019-12-21
- 定價: $1,650
- 售價: 9.0 折 $1,485
- 語言: 英文
- 頁數: 267
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1484253272
- ISBN-13: 9781484253274
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相關分類:
Amazon Web Services、大數據 Big-data、雲端運算
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商品描述
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
商品描述(中文翻譯)
探索現代數據分析平台市場以及使用針對雲端建立的數據倉儲Snowflake的好處。
隨著雲端技術的崛起,組織更傾向於使用Amazon Web Services (AWS)、Microsoft Azure或Google Cloud Platform等雲端供應商來部署他們的分析解決方案。雲端供應商提供了現代數據平台,用於構建雲端分析解決方案,以收集數據並整合到提供業務用戶洞察力的單一存儲解決方案中。任何分析框架的核心是數據倉儲,而以前客戶在選擇平台時選擇不多。
Snowflake專為雲端而建,對於數據分析市場來說是一個真正的遊戲改變者。本書將幫助您上手使用Snowflake,介紹部署和使用Snowflake數據倉儲的最佳實踐。此外,它還涵蓋了現代分析架構和使用案例。它提供了與Matillion ETL、Tableau和Databricks等領先的分析軟件集成的使用案例。最後,它還涵蓋了從本地遺留數據倉儲遷移的情景。
您將學到什麼:
- 了解Snowflake的關鍵功能
- 使用集群設置安全性和訪問權限
- 使用COPY命令將數據批量加載到Snowflake
- 從遺留數據倉儲遷移到Snowflake
- 將Snowflake數據平台與現代商業智能(BI)和數據集成工具集成
本書適合對數據倉儲和商業智能(BI)技術感興趣的人,以及現有和潛在的Snowflake用戶。
作者簡介
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 eCommerce. 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.
作者簡介(中文翻譯)
Dmitry Anoshin 是一位以數據為中心的技術專家,並在建立和實施商業/數位智能解決方案方面享有盛譽。他在多個行業中成功實施了分析項目,包括零售、金融、營銷和電子商務。他對商業智能、ETL、數據倉儲和大數據技術有深入的了解,並且在數據整合流程和各種數據倉儲方法的熟練使用方面具有豐富的經驗。他完成並按時交付了多個跨國完整商業智能解決方案生命週期實施項目。
Dmitry Shirokov 是 Rock Your Data 的數據架構師和雲分析顧問,專注於數位轉型、設計分析解決方案、數據整合和遷移、數據治理以及雲端/內部基礎設施。憑藉超過10年的數據分析和大數據經驗,他具備構建成熟分析解決方案所需的廣度和深度經驗。在2018年初加入Rock Your Data之前,他曾在科技咨詢和銀行業等不同公司工作。此前,他擔任過各種數據工程職位,專注於數據驅動的業務轉型。