Data Just Right: Introduction to Large-Scale Data & Analytics (Paperback)

Michael Manoochehri

  • 出版商: Addison Wesley
  • 出版日期: 2013-12-19
  • 售價: $1,320
  • 貴賓價: 9.5$1,254
  • 語言: 英文
  • 頁數: 256
  • 裝訂: Paperback
  • ISBN: 0321898656
  • ISBN-13: 9780321898654
  • 相關分類: NoSQL大數據 Big-data雲端運算
  • 立即出貨 (庫存=1)

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商品描述

Making Big Data Work: Real-World Use Cases and Examples, Practical Code, Detailed Solutions

 

Large-scale data analysis is now vitally important to virtually every business. Mobile and social technologies are generating massive datasets; distributed cloud computing offers the resources to store and analyze them; and professionals have radically new technologies at their command, including NoSQL databases. Until now, however, most books on “Big Data” have been little more than business polemics or product catalogs. Data Just Right is different: It’s a completely practical and indispensable guide for every Big Data decision-maker, implementer, and strategist.

 

Michael Manoochehri, a former Google engineer and data hacker, writes for professionals who need practical solutions that can be implemented with limited resources and time. Drawing on his extensive experience, he helps you focus on building applications, rather than infrastructure, because that’s where you can derive the most value.

 

Manoochehri shows how to address each of today’s key Big Data use cases in a cost-effective way by combining technologies in hybrid solutions. You’ll find expert approaches to managing massive datasets, visualizing data, building data pipelines and dashboards, choosing tools for statistical analysis, and more. Throughout, the author demonstrates techniques using many of today’s leading data analysis tools, including Hadoop, Hive, Shark, R, Apache Pig, Mahout, and Google BigQuery.

 

Coverage includes

  • Mastering the four guiding principles of Big Data success—and avoiding common pitfalls
  • Emphasizing collaboration and avoiding problems with siloed data
  • Hosting and sharing multi-terabyte datasets efficiently and economically
  • “Building for infinity” to support rapid growth
  • Developing a NoSQL Web app with Redis to collect crowd-sourced data
  • Running distributed queries over massive datasets with Hadoop, Hive, and Shark
  • Building a data dashboard with Google BigQuery
  • Exploring large datasets with advanced visualization
  • Implementing efficient pipelines for transforming immense amounts of data
  • Automating complex processing with Apache Pig and the Cascading Java library
  • Applying machine learning to classify, recommend, and predict incoming information
  • Using R to perform statistical analysis on massive datasets
  • Building highly efficient analytics workflows with Python and Pandas
  • Establishing sensible purchasing strategies: when to build, buy, or outsource
  • Previewing emerging trends and convergences in scalable data technologies and the evolving role of the Data Scientist 

商品描述(中文翻譯)

《大數據的運用:實際案例和範例、實用程式碼、詳細解決方案》

大規模數據分析對於幾乎每個企業都至關重要。移動和社交技術正在產生大量的數據集;分散式雲計算提供了存儲和分析這些數據的資源;專業人士擁有全新的技術工具,包括NoSQL數據庫。然而,迄今為止,“大數據”方面的大多數書籍不過是商業辯論或產品目錄。《資料剛剛好》不同:它是一本完全實用且不可或缺的指南,適用於每個大數據決策者、實施者和策略師。

書中的作者Michael Manoochehri是一位前Google工程師和數據黑客,他為需要在有限資源和時間內實施的專業人士提供實用解決方案。他根據自己的豐富經驗,幫助讀者專注於應用程序的構建,而不是基礎設施,因為這是可以獲得最大價值的地方。

Manoochehri展示了如何以成本效益的方式結合技術來應對當今關鍵的大數據使用案例。您將找到專家方法來管理大量數據集、可視化數據、構建數據管道和儀表板、選擇統計分析工具等。在整本書中,作者使用了當今許多領先的數據分析工具,包括Hadoop、Hive、Shark、R、Apache Pig、Mahout和Google BigQuery。

內容包括:

- 掌握大數據成功的四個指導原則,避免常見問題
- 強調協作,避免數據孤立問題
- 高效經濟地托管和共享多TB數據集
- "無限擴展"以支持快速增長
- 使用Redis開發NoSQL Web應用程序以收集眾包數據
- 使用Hadoop、Hive和Shark在大數據集上運行分佈式查詢
- 使用Google BigQuery構建數據儀表板
- 使用高級可視化工具探索大數據集
- 實施高效的數據轉換管道
- 使用Apache Pig和Cascading Java庫自動化複雜處理
- 應用機器學習對傳入信息進行分類、推薦和預測
- 使用R對大數據集進行統計分析
- 使用Python和Pandas構建高效的分析工作流程
- 建立明智的購買策略:何時構建、購買或外包
- 預覽可擴展數據技術和數據科學家角色的新趨勢和融合