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市場調查報告書

核心的巨量資料技術的收益化:即時分析

Monetizing Core Big Data Technology: Real-time Analytics

出版商 Frost & Sullivan 商品編碼 339884
出版日期 內容資訊 英文 29 Pages
商品交期: 最快1-2個工作天內
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核心的巨量資料技術的收益化:即時分析 Monetizing Core Big Data Technology: Real-time Analytics
出版日期: 2015年09月17日 內容資訊: 英文 29 Pages
簡介

本報告以即時分析為主題,提供與即時分析相關的問題與課題、對應許多課題的共同性業界舉措、引進即時分析的主要供應商與其客戶所採取的優點等相關調查分析。

摘要整理

簡介

即時分析的案例

  • 銀行、金融服務
  • 醫療
  • 行動應用程式、遊戲
  • 旅遊.飯店

資料速度和策略性價值的平衡的看法

  • 即時分析對所有需求來說不一定是必需的,並不總是可能
  • 速度重要,可是策略性價值是必要事項

即時分析

  • Apache Software Foundation (ASF): 開放原始碼的即時分析的促進要素
  • 主要的ASF的創新,加速即時分析的成長

即時分析:系統的課題

接受市場上各種評估的即時分析

實行中的即時分析的案例研究

即時分析解決方案的供應商

結論

圖表清單

目錄
Product Code: 9A37-00-22-00-00

This report asserts that real-time analytics is not “settled science.” It is not a foregone conclusion that every company needs and can afford real-time analytics in all areas of the business. There is also not, at this time, one shining example for all to follow in deploying it; but, instead, several models. Therefore, this report explores these and other issues and challenges surrounding real-time analytics; cooperative industry efforts that are addressing many of the challenges it poses; major providers who are deploying it; and the benefits that are accruing to their customers.

Table of Contents

Executive Summary

Introduction

The Case for Real-time Analytics

  • Banking & Financial Services
  • Healthcare
  • Mobile Apps and Gaming
  • Travel and Hospitality

A Balanced View of Data Speeds and Strategic Value

  • Real-time Analytics Is Not Essential for Every Need-and Not Always Possible
  • Speed is Important, but Strategic Value is Imperative

Real-time Analytics: How It's Made

  • Apache Software Foundation (ASF): Open Source Real-time Analytics Accelerator
  • Key ASF Innovations Accelerating the Growth of Real-time Analytics
    • Micro-batching: Apache Storm Trident and Apache Spark Streaming
    • Stream processing engine that can handle batch processing: Apache Flink
    • Unified stream and batch processing: Apache Apex
    • In-memory data fabric for real-time insights from massive datasets: Apache Ignite
    • Ability to run a large enterprise on a single data cluster: Apache Kafka

Real-time Analytics: Organizational Challenges

Real-time Analytics is Earning Mixed Reviews in the Market

Case Study Snapshots of Real-time Analytics in Action

Providers of Real-time Analytics Solutions

The Last Word

List of Exhibits

  • Exhibit 1: Specific Impacts of Real-time Analytics on Various Verticals
  • Exhibit 2: Impacts of Real-time Analytics on Functions that Impact All Industries
  • Exhibit 3: Apache Software Foundation (ASF) Solutions Supporting Real-time Analytics
  • Exhibit 4: Ignite Speeds Analytic Insights with Parallel Processing of Data and Queries
  • Exhibit 5: Kafka and Hadoop Combine to Deliver “All-speed Analytics”
  • Exhibit 6: Selected Customer Results from Deploying Real-time Analytics
  • Exhibit 7: Major Providers of Real-time Analytics Solutions
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