Next-Generation Big Data: A Practical Guide to Apache Kudu, Impala, and Spark

Butch Quinto

Next-Generation Big Data: A Practical Guide to Apache Kudu, Impala, and Spark
  • 出版商: Apress
  • 出版日期: 2018-06-13
  • 售價: $2,010
  • 貴賓價: 9.5 折 $1,910
  • 語言: 英文
  • 頁數: 584
  • 裝訂: Paperback
  • ISBN: 1484231465
  • ISBN-13: 9781484231463
  • 相關分類: Spark、大數據 Big-data

    • 海外代購書籍(需單獨結帳)

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商品描述

Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies.

Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data warehousing, data warehouse optimization, real-time and batch data ingestion and processing, real-time data visualization, big data governance, data wrangling, big data cloud deployments, and distributed in-memory big data computing. Finally, the book has an extensive and detailed coverage of big data case studies from Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard.

What You’ll Learn

  • Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow examples, and practical advice
  • Integrate HBase, Solr, Oracle, SQL Server, MySQL, Flume, Kafka, HDFS, and Amazon S3 with Apache Kudu, Impala, and Spark
  • Use StreamSets, Talend, Pentaho, and CDAP for real-time and batch data ingestion and processing
  • Utilize Trifacta, Alteryx, and Datameer for data wrangling and interactive data processing
  • Turbocharge Spark with Alluxio, a distributed in-memory storage platform
  • Deploy big data in the cloud using Cloudera Director
  • Perform real-time data visualization and time series analysis using Zoomdata, Apache Kudu, Impala, and Spark
  • Understand enterprise big data topics such as big data governance, metadata management, data lineage, impact analysis, and policy enforcement, and how to use Cloudera Navigator to perform common data governance tasks
  • Implement big data use cases such as big data warehousing, data warehouse optimization, Internet of Things, real-time data ingestion and analytics, complex event processing, and scalable predictive modeling
  • Study real-world big data case studies from innovative companies, including Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard
Who This Book Is For

BI and big data warehouse professionals interested in gaining practical and real-world insight into next-generation big data processing and analytics using Apache Kudu, Impala, and Spark; and those who want to learn more about other advanced enterprise topics

商品描述(中文翻譯)

利用這本實用且易於遵循的指南，使用下一代大數據技術來現代化傳統企業數據倉庫和商業智能環境。

《下一代大數據》採用全面的方法，涵蓋現代企業大數據的最重要方面。本書不僅涵蓋主要技術堆棧，還包括用於大數據倉庫、數據倉庫優化、實時和批量數據輸入和處理、實時數據可視化、大數據治理、數據整理、大數據雲部署和分佈式內存大數據計算的下一代工具和應用。最後，本書詳細介紹了來自Navistar、Cerner、British Telecom、Shopzilla、Thomson Reuters和Mastercard的大數據案例。

你將學到什麼：
- 使用真實世界的易於遵循的示例和實用建議，安裝Apache Kudu、Impala和Spark，以現代化企業數據倉庫和商業智能環境。
- 將HBase、Solr、Oracle、SQL Server、MySQL、Flume、Kafka、HDFS和Amazon S3與Apache Kudu、Impala和Spark集成。
- 使用StreamSets、Talend、Pentaho和CDAP進行實時和批量數據輸入和處理。
- 使用Trifacta、Alteryx和Datameer進行數據整理和交互式數據處理。
- 使用分佈式內存存儲平台Alluxio加速Spark。
- 使用Cloudera Director在雲中部署大數據。
- 使用Zoomdata、Apache Kudu、Impala和Spark進行實時數據可視化和時間序列分析。
- 了解企業大數據主題，如大數據治理、元數據管理、數據譜系、影響分析和策略執行，以及如何使用Cloudera Navigator執行常見的數據治理任務。
- 實施大數據用例，如大數據倉庫、數據倉庫優化、物聯網、實時數據輸入和分析、複雜事件處理和可擴展的預測建模。
- 研究創新公司的真實大數據案例，包括Navistar、Cerner、British Telecom、Shopzilla、Thomson Reuters和Mastercard。

本書適合對使用Apache Kudu、Impala和Spark進行下一代大數據處理和分析，以及對其他高級企業主題有興趣的商業智能和大數據倉庫專業人士。

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