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市场调查报告书

Hadoop和BI:第一部分

BI on Hadoop, Part 1

出版商 Ovum (TMT Intelligence, Informa) 商品编码 288848
出版日期 内容信息 英文 17 Pages
商品交期: 最快1-2个工作天内
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Hadoop和BI:第一部分 BI on Hadoop, Part 1
出版日期: 2013年10月10日 内容信息: 英文 17 Pages
简介

直到最近,巨量数据分析用于NoSQL平台的高度计划性风格分析技术和大企业的SQL数据仓储等的数据探勘,不过由于Hadoop和BI工具结合,能成为多数企业分析的主流吗?

本报告提供Hadoop相关调查分析,最新的案例研究,Hadoop和BI结合的机会及限制,BI的角色的Hadoop相关方法等相关考察汇整数据,为您概述为以下内容。

第1章 摘要

  • 发展要素
  • Ovum的见解
  • 主要的讯息
  • 报告系列概要

第2章 现今的BI状况

  • Ovum的商业智能(BI)定义
  • BI和SQL
    • 成熟市场
    • SQL的魅力
    • SQL的限制
  • Hadoop
    • 为何Hadoop成为话题
    • Hadoop的限制
    • 不久将来的变化

第3章 在Hadoop的BI流程加上价值

  • Hadoop无法代替EDW
  • 可是,Hadoop可到达EDW达不到的地方

第4章 Hadoop怎么改变BI

  • 常被询问的问题的回答方法
  • BI工具及技术对这个问题作出回答
  • 在BI使用Hadoop对谁有益

第5章 提案

  • 对企业的提案
    • Hadoop还属于新的技术,技术诀窍是必须的
    • 起于小规模,然后拓展
    • 不追加数据「只是因为」
  • 供应商的提案
    • 指导和教育为关键
    • 在公司内部传播巨量数据的技术诀窍
    • 从外部提高巨量数据相关的专门服务

附录

目录
Product Code: IT014-002804

Until recently, Big Data analytics have typically been associated with advanced programmatic-style analytic techniques on emerging NoSQL platforms, or complex, data mining-oriented runs against large enterprise SQL data warehouses. That triggers an obvious question -- could Hadoop become more accessible with the BI tools that have become a staple of analytics for many enterprises?

Highlights

  • Hadoop will augment, not replace, the traditional enterprise data warehouse.
  • SQL is rapidly becoming a preferred way for BI users to access Hadoop.
  • Data discovery and search tools become increasingly important as more data enters the BI process.

Features Benefits

  • Outlines new use cases for adding Hadoop to the BI stack.
  • Discusses the opportunities and limitations of BI with Hadoop today and going forward.
  • Discusses the types of interaction that different BI roles (casual user, power user, BI developer, BI administrator, etc) will have with Hadoop.

Questions Answers

  • When and why should Hadoop be considered for BI processes?
  • How can Hadoop augment BI implementations?

Table of Contents

Headings

  • SUMMARY
    • Catalyst
    • Ovum view
    • Key messages
    • Overview of report series
  • THE STATE OF BI TODAY
    • Ovum's definition of business intelligence
    • BI and SQL
      • A mature market
      • The appeal of SQL
      • The limitations of SQL
    • Hadoop
      • Why are we having this conversation?
      • Hadoop's limitations
      • Changes are on the horizon
  • HADOOP ADDS BUSINESS VALUE TO BI PROCESSES
    • Hadoop is not replacing EDWs...
    • ...but Hadoop can go where EDWs cannot
      • Keeping it raw
      • Hadoop-augmented BI stack - adding new types of data sources to the BI lifecycle
      • Active archiving
  • HOW DOES HADOOP CHANGE THE BI THOUGHT PROCESS?
    • Bigger ways of answering familiar questions
    • BI tools and techniques to help frame these questions
      • Data discovery and search can be a first analytic step
      • Search will help users find the data they are looking for
      • Graph processing to better understand what is connected to what
    • Who can benefit from BI on Hadoop?
      • Casual end user
      • Power user/data curator
      • Developer
      • Administrator
  • RECOMMENDATIONS
    • Recommendations for enterprises
      • Hadoop is still a young technology - know-how might need to be acquired
      • Start small and scale out
      • Don't add data "just because"
    • Recommendations for vendors
      • Guidance and education will be key
      • Expand Big Data know-how internally
      • Improve Big Data-related professional services externally
      • Don't run away from core BI customers
  • APPENDIX
    • Methodology
    • Further reading
    • Author
    • Ovum Consulting
    • Disclaimer
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