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表紙:ビッグデータ市場:主要企業・ソリューション・使用例・インフラ・データ統合・IoTサポート・展開モデル・サービス (2021~2026年)
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980892

ビッグデータ市場:主要企業・ソリューション・使用例・インフラ・データ統合・IoTサポート・展開モデル・サービス (2021~2026年)

Big Data Market by Leading Companies, Solutions, Use Cases, Infrastructure, Data Integration, IoT Support, Deployment Model and Services in Industry Verticals 2021 - 2026

出版日: | 発行: Mind Commerce | ページ情報: 英文 314 Pages | 納期: 即日から翌営業日

価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=111.74円
ビッグデータ市場:主要企業・ソリューション・使用例・インフラ・データ統合・IoTサポート・展開モデル・サービス (2021~2026年)
出版日: 2021年01月11日
発行: Mind Commerce
ページ情報: 英文 314 Pages
納期: 即日から翌営業日
  • 全表示
  • 概要
  • 目次
概要

世界の各セグメントにおけるビッグデータの市場規模は、2026年までにSCMが66億米ドル、データ統合・品質ツールが99億米ドル、エンタープライズパフォーマンス分析が278億米ドル、ビジネスインテリジェンスアプリケーションが504億米ドルとなる見込みです。リアルタイムデータは、すべての使用例、セグメント、およびソリューションにとって重要な価値提案となる見込みです。市場をリードする企業は、ビッグデータ技術とIoTインフラストラクチャを急速に統合しています。

当レポートでは、世界のビッグデータ市場について調査し、ビジネスケースの問題/分析、アプリケーションの使用例、ベンダー情勢、バリューチェーン分析、予測による業界の定量的評価など詳細な評価を提供しており、ビッグデータインフラストラクチャとセキュリティフレームワークのコンポーネントについても評価しています。

第1章 エグゼクティブサマリー

第2章 イントロダクション

  • ビッグデータの概要
    • ビッグデータの定義
    • ビッグデータエコシステム
    • ビッグデータの主な特徴
  • 調査の背景
    • 範囲
    • 対象
    • 企業のフォーカス

第3章 ビッグデータの課題と機会

  • ビッグデータインフラストラクチャの保護
    • ビッグデータインフラストラクチャ
    • インフラストラクチャの課題
    • ビッグデータインフラストラクチャの機会
  • 非構造化データとモノのインターネット
    • 新しいプロトコル、プラットフォーム、ストリーミングと解析、ソフトウェアと分析ツール
    • IoTおよび軽量データ交換フォーマットにおけるビッグデータ
    • IoTおよび軽量プロトコルにおけるビッグデータ
    • IoTおよびネットワーク相互運用性プロトコルにおけるビッグデータ
    • IoTデータ処理のスケーラビリティにおけるビッグデータ

第4章 ビッグデータ技術とビジネスケース

  • ビッグデータ技術
    • Hadoop
    • NoSQL
    • MPPデータベース
    • その他の技術
  • 新たな技術、ツール、テクニック
    • ストリーミング分析
    • クラウド技術
    • 検索技術
    • 分析ツールのカスタマイズ
    • キーワード最適化
  • ビッグデータロードマップ
  • 市場の促進要因
    • データ量と多様性
    • 企業および通信事業者によるビッグデータ採用の増加
    • ビッグデータソフトウェアの成熟
    • Web大手によるビッグデータへの継続的な投資
    • ビジネス成長要因
  • 市場の障壁
    • 大きな障壁:プライバシーとセキュリティのギャップ
    • 労働者の再スキル化と組織の抵抗
    • 明確なビッグデータ戦略の欠如
    • スケーラビリティとメンテナンスの技術的課題
    • ビッグデータ開発の専門知識

第5章 主要なビッグデータセクター

  • 産業オートメーションとモノのインターネット
    • マシンツーマシンソリューションにおけるビッグデータ
    • 業界の機会
  • 小売とホスピタリティ
    • 予測と在庫管理
    • 顧客関係管理
    • 購入パターンの決定
    • ホスピタリティの使用例
    • パーソナライズドマーケティング
  • デジタルメディア
    • ソーシャルメディア
    • ソーシャルゲーム分析
    • 他の業界によるソーシャルメディア分析の使用
    • インターネットキーワード検索
  • ユーティリティ
    • 稼働データの分析
    • 将来の応用分野
  • 金融サービス
    • 不正分析、軽減、およびリスクプロファイリング
    • 加盟店負担リワードプログラム
    • 顧客セグメンテーション
    • 顧客保持&パーソナライズド製品の提供
    • 保険企業
  • ヘルスケア
    • 医薬品開発
    • 医療データ分析
    • ケーススタディ:心拍パターンの特定
  • 情報通信技術
    • Telco Analytics:顧客/使用状況のプロファイリングとサービスの最適化
    • ビッグデータ分析ツール
    • 音声分析
    • 新製品とサービス
  • 政府:行政および国土安全保障
    • ビッグデータ研究
    • 統計分析
    • 言語翻訳
    • 公衆向けの新しいアプリケーションの開発
    • 犯罪の追跡
    • 情報収集
    • 不正検出と収益の生成
  • その他のセクター
    • 航空
    • 輸送とロジスティクス:フリート使用の最適化
    • スポーツ統計のリアルタイム処理
    • 教育
    • 製造
    • 抽出と天然資源

第6章 ビッグデータのバリューチェーン

  • ビッグデータバリューチェーンの断片化
  • データの取得とプロビジョニング
  • データウェアハウジングとビジネスインテリジェンス
  • 分析と視覚化
  • アクショニングとビジネスプロセス管理
  • データガバナンス

第7章 ビッグデータ分析

  • ビッグデータ分析の役割と重要性
  • ビッグデータ分析プロセス
  • リアクティブ分析とプロアクティブ分析
  • 技術と実装のアプローチ
    • グリッドコンピューティング
    • データベース内処理
    • インメモリ分析
    • データマイニング
    • 予測分析
    • 自然言語処理
    • テキスト分析
    • ビジュアル分析
    • 相関ルール学習
    • 分類木分析
    • 機械学習
    • ニューラルネットワーク
    • 多層パーセプトロン
    • 放射基底関数
    • 地理空間予測モデリング
    • 回帰分析
    • ソーシャルネットワーク分析

第8章 標準化と規制の問題

  • Cloud Standards Customer Council
  • National Institute of Standards and Technology
  • OASIS
  • Open Data Foundation
  • Open Data Center Alliance
  • Cloud Security Alliance
  • International Telecommunications Union
  • International Organization for Standardization

第9章 業界アプリケーションにおけるビッグデータ

  • 製造業におけるビッグデータアプリケーション
  • 小売りアプリケーション
  • ビッグデータアプリケーション:保険金詐欺の検出
  • ビッグデータアプリケーション:メディアおよびエンターテインメント業界
  • ビッグデータアプリケーション:気象パターン
  • ビッグデータアプリケーション:運輸業界
  • ビッグデータアプリケーション:教育業界
  • ビッグデータアプリケーション: eコマースのパーソナライズ
  • ビッグデータアプリケーション:石油・ガス産業
  • ビッグデータアプリケーション:電気通信業界

第10章 主要なビッグデータ企業とソリューション

  • ベンダー評価マトリクス
  • 主要ビッグデータベンダーの競合情勢
    • 新製品開発
    • 提携、M&A、コラボレーション
  • 1010Data (ACC)
  • Accenture
  • Actian Corporation
  • AdvancedMD
  • Alation
  • Allscripts Healthcare Solutions
  • Alpine Data Labs
  • Alteryx
  • Amazon
  • Anova Data
  • Apache Software Foundation
  • Apple Inc.
  • APTEAN
  • Athena Health Inc.
  • Attunity
  • Booz Allen Hamilton
  • Bosch
  • BGI
  • Big Panda
  • Bina Technologies Inc.
  • Capgemini
  • Cerner Corporation
  • Cisco Systems
  • CLC Bio
  • Cloudera
  • Cogito Ltd.
  • Compuverde
  • CRAY Inc.
  • Computer Science Corporation
  • Crux Informatics
  • Ctrl Shift
  • Cvidya
  • Cybatar
  • DataDirect Network
  • Data Inc.
  • Databricks
  • Dataiku
  • Datameer
  • Data Stax
  • Definiens
  • Dell EMC
  • Deloitte
  • Domo
  • eClinicalWorks
  • Epic Systems Corporation
  • Facebook
  • Fluentd
  • Flytxt
  • Fujitsu
  • Genalice
  • General Electric
  • GenomOncology
  • GoodData Corporation
  • Google
  • Greenplum
  • Grid Gain Systems
  • Groundhog Technologies
  • Guavus
  • Hack/reduce
  • HPCC Systems
  • HP Enterprise
  • Hitachi Data Systems
  • Hortonworks
  • IBM
  • Illumina Inc
  • Imply Corporation
  • Informatica
  • Inter Systems Corporation
  • Intel
  • IVD Industry Connectivity Consortium-IICC
  • Jasper (Cisco)
  • Juniper Networks
  • Knome,Inc.
  • Leica Biosystems (Danaher)
  • Longview
  • MapR
  • Marklogic
  • Mayo Medical Laboratories
  • McKesson Corporation
  • Medical Information Technology Inc.
  • Medio
  • Medopad
  • Microsoft
  • Microstrategy
  • MongoDB
  • MU Sigma
  • N-of-One
  • Netapp
  • NTT Data
  • Open Text (Actuate Corporation)
  • Opera Solutions
  • Oracle
  • Palantir Technologies Inc.
  • Pathway Genomics Corporation
  • Perkin Elmer
  • Pentaho (Hitachi)
  • Platfora
  • Qlik Tech
  • Quality Systems Inc.
  • Quantum
  • Quertle
  • Quest Diagnostics Inc.
  • Rackspace
  • Red Hat
  • Revolution Analytics
  • Roche Diagnostics
  • Rocket Fuel Inc.
  • Salesforce
  • SAP
  • SAS Institute
  • Selventa Inc.
  • Sense Networks
  • Shanghai Data Exchange
  • Sisense
  • Social Cops
  • Software AG/Terracotta
  • Sojern
  • Splice Machine
  • Splunk
  • Sqrrl
  • Sumo Logic
  • Sunquest Information Systems
  • Supermicro
  • Tableau Software
  • Tableau
  • Tata Consultancy Services
  • Teradata
  • ThetaRay
  • Thoughtworks
  • Think Big Analytics
  • TIBCO
  • Tube Mogul
  • Verint Systems
  • VolMetrix
  • VMware
  • Wipro
  • Workday (Platfora)
  • WuXi NextCode Genomics
  • Zoomdata

第11章 ビッグデータ市場全体の分析と予測

  • 世界のビッグデータ市場
  • ビッグデータ市場:ソリューションタイプ別
  • ビッグデータ市場:地域別

第12章 ビッグデータ市場セグメントの分析と予測

  • マネジメントユーティリティ
    • 汎用分析サーバーおよび関連ハードウェア
    • アプリケーションインフラストラクチャとミドルウェア
    • データ統合ツールおよびデータ品質ツール
    • データベース管理システム
    • ストレージ管理
  • 機能セグメント別
    • サプライチェーン管理
    • ワークフォース分析
    • エンタープライズパフォーマンス分析
    • プロフェッショナルサービス
    • ビジネスインテリジェンス
    • ソーシャルメディアとコンテンツ分析
  • 新興技術におけるビッグデータ
    • モノのインターネット
    • スマートシティ
    • ブロックチェーンと暗号通貨
    • 拡張現実と仮想現実
    • サイバーセキュリティ
    • スマートアシスタント
    • コグニティブコンピューティング
    • 顧客関係管理
    • 空間情報
  • 業種別
  • 地域別
    • 北米
    • 南米
    • 西欧
    • 中東欧
    • アジア太平洋
    • 中東およびアフリカ

第13章 付録:ストリーミングIoTデータのビッグデータサポート

目次

Overview:

This report provides an in-depth assessment of the global big data market, including business case issues/analysis, application use cases, vendor landscape, value chain analysis, and a quantitative assessment of the industry with forecasting from 2021 to 2026. This report also evaluates the components of big data infrastructure and security framework.

This report also provides analysis of leading big data solutions with key metrics such as streaming IoT data analytics revenue for leading providers such as Teradata, IBM, Oracle, SAS and Datameter. The report evaluates, compares and contrasts vendors, and provides a vendor ranking matrix. Analysis takes into consideration solutions integrating both structured and unstructured data.

Select Report Findings:

  • Big data in SCM will exceed $6.6B globally by 2026
  • Data Integration and Quality Tools $9.9B globally by 2026
  • Enterprise performance analytics will reach $27.8B globally by 2026
  • Big data in business intelligence applications will reach $50.4B by 2026
  • Combination of AI and IoT (AIoT) will rely upon advanced big data analytics software
  • Real-time data will be a key value proposition for all use cases, segments, and solutions
  • Market leading companies are rapidly integrated big data technologies with IoT infrastructure

Target Audience:

  • IoT companies
  • Network service providers
  • Systems integration companies
  • Big Data and Analytics companies
  • Advertising and media companies
  • Enterprise across all industry verticals
  • Cloud and IoT product and service providers

Big data solutions are relied upon to gain insights from data files/sets so large and complex that it becomes difficult to process using traditional database management tools and data processing applications. Mind Commerce sees key solution areas for big data as commerce, geospatial, finance, healthcare, transportation, and smart grids. Key technology integration includes AI, IoT, cloud and high performance computing.

AI facilitates the efficient and effective supply of information to enterprises for optimized business decision-making. Some of the biggest opportunity areas are commercial applications, search in the big data environment, and mobility control for generation of actionable business intelligence.

In terms of big data integration with cloud-based infrastructure, cloud solutions allow companies that previously required large investments into hardware to store data to do the same through the cloud at a lower cost. Companies save not only money, but physical space where this hardware was previously stored. The trend to migrate to big data technologies is driven by the need for additional information derivable from analysis of all of the electronic data available to a business.

To realize the true potential to transform intelligence information from the huge amount of unstructured data, government agencies cannot leverage traditional data management technologies and DB techniques in terms of processing data. To understand patterns that exist in unstructured data, government agencies apply statistical models to large quantities of unstructured data.

Industry verticals of various types have challenges in capturing, organizing, storing, searching, sharing, transferring, analyzing and using data to improve business. Big data is making a big impact in certain industries such as the healthcare, industrial, and retail sectors. Every large corporation collects and maintains a huge amount of data associated with its customers including their preferences, purchases, habits, travels, and other personal information. In addition to the large volume, much of this data is unstructured, making it hard to manage.

Big data technology will help financial institutions maximize the value of data and gain competitive advantage, minimize costs, convert challenges to opportunities, and minimize risk in real-time. As an example in the transportation industry, real-time applications can match loads to a vehicle's capacity using data analytics. Big data provides shipping and delivery companies with real-time notifications and updates to increase efficiency and accuracy.

Big data technologies provide financial services firms with the capability to capture and analyze data, build predictive models, back-test and simulate scenarios. Through iteration, firms will determine the most important variables and also key predictive models. Financial firms are increasingly migrating their data and analytics to the cloud, leading to reduced cost, better data management, and better customer service. Data and insights can also be transferred far quicker than before, allowing representatives to provide customers with real-time data backed insights.

Healthcare services can be applied more accurately with big data. Decisions based on real-time data and assistance from AI/ML solutions. Private health insurance providers can gain access to previously inaccessible information and databases through big data. Healthcare customer service processes can also be streamlined while providing personalized more personalized medical care to individuals.

Big data analytics allows retail companies to examine and interact with their audience online in new ways. Predictive analytics can analyze a consumer's activity and recommend suggested items to them. Once a consumer has purchased from a company, big data can help retain that customer by better understanding what a person wants. For example, Amazon collects all its customers' data to provide a personalized experience, earning up to 35% of its revenue from its customers' data.

Customer Relationship Management (CRM) is a model of managing relationship and interaction between company and customer. This includes using technology for organizing, automating, and synchronizing all customer-related information like sales, marketing, services, support and more. Big data represents a big business opportunity and it is poised to do more than just improve CRM.

Data analytics is useful for Supply Chain Management (SCM) because it can analyze a variety of variables across a business' operations. SCM service providers use advanced analytics to analyze materials, products in inventory and imports/exports to better understand needs. This helps a business to manage its assets better, saving time and money. Data analytics can predict future risks based on history and a large set of data.

Companies in Report:

  • 1010Data
  • Accenture
  • Actian Corporation
  • AdvancedMD
  • Alation
  • Allscripts Healthcare Solutions
  • Alpine Data Labs
  • Alteryx
  • Amazon
  • Anova Data
  • Apache Software Foundation
  • Apple Inc.
  • APTEAN
  • AthenaHealth Inc.
  • Attunity
  • BGI
  • Big Panda
  • Bina Technologies Inc.
  • Booz Allen Hamilton
  • Bosch
  • Capgemini
  • Cerner Corporation
  • Cisco Systems
  • CLC Bio
  • Cloudera
  • Cogito Ltd.
  • Computer Science Corporation
  • Compuverde
  • CRAY Inc.
  • Crux Informatics
  • Ctrl Shift
  • Cvidya
  • Cybatar
  • Data Inc.
  • Data Stax
  • Databricks
  • DataDirect Network
  • Dataiku
  • Datameer
  • Definiens
  • Dell EMC
  • Deloitte
  • Domo
  • eClinicalWorks
  • Epic Systems Corporation
  • Facebook
  • Fluentd
  • Flytxt
  • Fujitsu
  • Genalice
  • General Electric
  • GenomOncology
  • GoodData Corporation
  • Google
  • Greenplum
  • Grid Gain Systems
  • Groundhog Technologies
  • Guavus
  • Hack/reduce
  • Hitachi Data Systems
  • Hortonworks
  • HP Enterprise
  • HPCC Systems
  • IBM
  • Illumina Inc
  • Imply Corporation
  • Industry Connectivity Consortium
  • Informatica
  • Intel
  • Inter Systems Corporation
  • Jasper (Cisco Jasper)
  • Juniper Networks
  • Knome,Inc.
  • Leica Biosystems (Danaher)
  • Longview
  • MapR
  • Marklogic
  • Mayo Medical Laboratories
  • McKesson Corporation
  • Medical Information Technology Inc.
  • Medio
  • Medopad
  • Microsoft
  • Microstrategy
  • MongoDB (Formerly 10Gen)
  • MU Sigma
  • Netapp
  • N-of-One
  • NTT Data
  • Open Text (Actuate Corporation)
  • Opera Solutions
  • Oracle
  • Palantir Technologies Inc.
  • Pathway Genomics Corporation
  • Pentaho (Hitachi)
  • Perkin Elmer
  • Platfora
  • Qlik Tech
  • Quality Systems Inc.
  • Quantum
  • Quertle
  • Quest Diagnostics Inc.
  • Rackspace
  • Red Hat
  • Revolution Analytics
  • Roche Diagnostics
  • Rocket Fuel Inc.
  • Salesforce
  • SAP
  • SAS Institute
  • Selventa Inc.
  • Sense Networks
  • Shanghai Data Exchange
  • Sisense
  • Social Cops
  • Software AG/Terracotta
  • Sojern
  • Splice Machine
  • Splunk
  • Sqrrl
  • Sumo Logic
  • Sunquest Information Systems
  • Supermicro
  • Tableau
  • Tableau Software
  • Tata Consultancy Services
  • Teradata
  • ThetaRay
  • Think Big Analytics
  • Thoughtworks
  • TIBCO
  • Tube Mogul
  • Verint Systems
  • VMware
  • VolMetrix
  • Wipro
  • Workday (Platfora)
  • WuXi NextCode Genomics
  • Zoomdata

Table of Contents

1.0 Executive Summary

2.0 Introduction

  • 2.1 Big Data Overview
    • 2.1.1 Defining Big Data
    • 2.1.2 Big Data Ecosystem
    • 2.1.3 Key Characteristics of Big Data
      • 2.1.3.1 Volume
      • 2.1.3.2 Variety
      • 2.1.3.3 Velocity
      • 2.1.3.4 Variability
      • 2.1.3.5 Complexity
  • 2.2 Research Background
    • 2.2.1 Scope
    • 2.2.2 Coverage
    • 2.2.3 Company Focus

3.0 Big Data Challenges and Opportunities

  • 3.1 Securing Big Data Infrastructure
    • 3.1.1 Big Data Infrastructure
    • 3.1.2 Infrastructure Challenges
    • 3.1.3 Big Data Infrastructure Opportunities
      • 3.1.3.1 Securing State Data
      • 3.1.3.2 Securing APIs
      • 3.1.3.3 Securing Applications
      • 3.1.3.4 Securing Data for Analysis
      • 3.1.3.5 Securing User Privileges
      • 3.1.3.6 Securing Enterprise Data
  • 3.2 Unstructured Data and the Internet of Things
    • 3.2.1 New Protocols, Platforms, Streaming and Parsing, Software and Analytical Tools
    • 3.2.2 Big Data in IoT and Lightweight Data Interchange Format
    • 3.2.3 Big Data in IoT and Lightweight Protocols
    • 3.2.4 Big Data in IoT and Network Interoperability Protocols
    • 3.2.5 Big Data in IoT Data Processing Scalability

4.0 Big Data Technologies and Business Cases

  • 4.1 Big Data Technology
    • 4.1.1 Hadoop
      • 4.1.1.1 Other Apache Projects
    • 4.1.2 NoSQL
      • 4.1.2.1 Hbase
      • 4.1.2.2 Cassandra
      • 4.1.2.3 Mongo DB
      • 4.1.2.4 Riak
      • 4.1.2.5 CouchDB
    • 4.1.3 MPP Databases
    • 4.1.4 Other Technologies
      • 4.1.4.1 Storm
      • 4.1.4.2 Drill
      • 4.1.4.3 Dremel
      • 4.1.4.4 SAP HANA
      • 4.1.4.5 Gremlin & Giraph
  • 4.2 Emerging Technologies, Tools, and Techniques
    • 4.2.1 Streaming Analytics
    • 4.2.2 Cloud Technology
    • 4.2.3 Search Technologies
    • 4.2.4 Customizes Analytics Tools
    • 4.2.5 Keywords Optimization
  • 4.3 Big Data Roadmap
  • 4.4 Market Drivers
    • 4.4.1 Data Volume and Variety
    • 4.4.2 Increasing Adoption of Big Data by Enterprises and Telecom
    • 4.4.3 Maturation of Big Data Software
    • 4.4.4 Continued Investments in Big Data by Web Giants
    • 4.4.5 Business Drivers
  • 4.5 Market Barriers
    • 4.5.1 The Big Barrier: Privacy and Security Gaps
    • 4.5.2 Workforce Reskilling and Organizational Resistance
    • 4.5.3 Lack of Clear Big Data Strategies
    • 4.5.4 Scalability and Maintenance Technical Challenges
    • 4.5.5 Big Data Development Expertise

5.0 Key Big Data Sectors

  • 5.1 Industrial Automation and Internet of Things
    • 5.1.1 Big Data in Machine to Machine Solutions
    • 5.1.2 Vertical Opportunities
  • 5.2 Retail and Hospitality
    • 5.2.1 Forecasting and Inventory Management
    • 5.2.2 Customer Relationship Management
    • 5.2.3 Determining Buying Patterns
    • 5.2.4 Hospitality Use Cases
    • 5.2.5 Personalized Marketing
  • 5.3 Digital Media
    • 5.3.1 Social Media
    • 5.3.2 Social Gaming Analytics
    • 5.3.3 Usage of Social Media Analytics by Other Verticals
    • 5.3.4 Internet Keyword Search
  • 5.4 Utilities
    • 5.4.1 Analysis of Operational Data
    • 5.4.2 Application Areas for the Future
  • 5.5 Financial Services
    • 5.5.1 Fraud Analysis, Mitigation & Risk Profiling
    • 5.5.2 Merchant-Funded Reward Programs
    • 5.5.3 Customer Segmentation
    • 5.5.4 Customer Retention & Personalized Product Offering
    • 5.5.5 Insurance Companies
  • 5.6 Healthcare
    • 5.6.1 Drug Development
    • 5.6.2 Medical Data Analytics
    • 5.6.3 Case Study: Identifying Heartbeat Patterns
  • 5.7 Information and Communications Technologies
    • 5.7.1 Telco Analytics: Customer/Usage Profiling and Service Optimization
    • 5.7.2 Big Data Analytic Tools
    • 5.7.3 Speech Analytics
    • 5.7.4 New Products and Services
  • 5.8 Government: Administration and Homeland Security
    • 5.8.1 Big Data Research
    • 5.8.2 Statistical Analysis
    • 5.8.3 Language Translation
    • 5.8.4 Developing New Applications for the Public
    • 5.8.5 Tracking Crime
    • 5.8.6 Intelligence Gathering
    • 5.8.7 Fraud Detection and Revenue Generation
  • 5.9 Other Sectors
    • 5.9.1 Aviation
    • 5.9.2 Transportation and Logistics: Optimizing Fleet Usage
    • 5.9.3 Real-Time Processing of Sports Statistics
    • 5.9.4 Education
    • 5.9.5 Manufacturing
    • 5.9.6 Extraction and Natural Resources

6.0 Big Data Value Chain

  • 6.1 Fragmentation in the Big Data Value Chain
  • 6.2 Data Acquisitioning and Provisioning
  • 6.3 Data Warehousing and Business Intelligence
  • 6.4 Analytics and Visualization
  • 6.5 Actioning and Business Process Management
  • 6.6 Data Governance

7.0 Big Data Analytics

  • 7.1 The Role and Importance of Big Data Analytics
  • 7.2 Big Data Analytics Processes
  • 7.3 Reactive vs. Proactive Analytics
  • 7.4 Technology and Implementation Approaches
    • 7.4.1 Grid Computing
    • 7.4.2 In-Database processing
    • 7.4.3 In-Memory Analytics
    • 7.4.4 Data Mining
    • 7.4.5 Predictive Analytics
    • 7.4.6 Natural Language Processing
    • 7.4.7 Text Analytics
    • 7.4.8 Visual Analytics
    • 7.4.9 Association Rule Learning
    • 7.4.10 Classification Tree Analysis
    • 7.4.11 Machine Learning
    • 7.4.12 Neural Networks
    • 7.4.13 Multilayer Perceptron
    • 7.4.14 Radial Basis Functions
      • 7.4.14.1 Support Vector Machines
      • 7.4.14.2 Naïve Bayes
      • 7.4.14.3 K-nearest Neighbors
    • 7.4.15 Geospatial Predictive Modelling
    • 7.4.16 Regression Analysis
    • 7.4.17 Social Network Analysis

8.0 Standardization and Regulatory Issues

  • 8.1 Cloud Standards Customer Council
  • 8.2 National Institute of Standards and Technology
  • 8.3 OASIS
  • 8.4 Open Data Foundation
  • 8.5 Open Data Center Alliance
  • 8.6 Cloud Security Alliance
  • 8.7 International Telecommunications Union
  • 8.8 International Organization for Standardization

9.0 Big Data in Industry Vertical Applications

  • 9.1 Big Data Application in Manufacturing
  • 9.2 Retail Applications
  • 9.3 Big Data Application: Insurance Fraud Detection
  • 9.4 Big Data Application: Media and Entertainment Industry
  • 9.5 Big Data Application: Weather Patterns
  • 9.6 Big Data Application: Transportation Industry
  • 9.7 Big Data Application: Education Industry
  • 9.8 Big Data Application: E-Commerce Personalization
  • 9.9 Big Data Application: Oil and Gas Industry
  • 9.10 Big Data Application: Telecommunication Industry

10.0 Key Big Data Companies and Solutions

  • 10.1 Vendor Assessment Matrix
  • 10.2 Competitive Landscape of Major Big Data Vendors
    • 10.2.1 New Products Developments
    • 10.2.2 Partnership, Merger, Acquisition, and Collaboration
  • 10.3 1010Data (ACC)
  • 10.4 Accenture
  • 10.5 Actian Corporation
  • 10.6 AdvancedMD
  • 10.7 Alation
  • 10.8 Allscripts Healthcare Solutions
  • 10.9 Alpine Data Labs
  • 10.10 Alteryx
  • 10.11 Amazon
  • 10.12 Anova Data
  • 10.13 Apache Software Foundation
  • 10.14 Apple Inc.
  • 10.15 APTEAN
  • 10.16 Athena Health Inc.
  • 10.17 Attunity
  • 10.18 Booz Allen Hamilton
  • 10.19 Bosch
  • 10.20 BGI
  • 10.21 Big Panda
  • 10.22 Bina Technologies Inc.
  • 10.23 Capgemini
  • 10.24 Cerner Corporation
  • 10.25 Cisco Systems
  • 10.26 CLC Bio
  • 10.27 Cloudera
  • 10.28 Cogito Ltd.
  • 10.29 Compuverde
  • 10.30 CRAY Inc.
  • 10.31 Computer Science Corporation
  • 10.32 Crux Informatics
  • 10.33 Ctrl Shift
  • 10.34 Cvidya
  • 10.35 Cybatar
  • 10.36 DataDirect Network
  • 10.37 Data Inc.
  • 10.38 Databricks
  • 10.39 Dataiku
  • 10.40 Datameer
  • 10.41 Data Stax
  • 10.42 Definiens
  • 10.43 Dell EMC
  • 10.44 Deloitte
  • 10.45 Domo
  • 10.46 eClinicalWorks
  • 10.47 Epic Systems Corporation
  • 10.48 Facebook
  • 10.49 Fluentd
  • 10.50 Flytxt
  • 10.51 Fujitsu
  • 10.52 Genalice
  • 10.53 General Electric
  • 10.54 GenomOncology
  • 10.55 GoodData Corporation
  • 10.56 Google
  • 10.57 Greenplum
  • 10.58 Grid Gain Systems
  • 10.59 Groundhog Technologies
  • 10.60 Guavus
  • 10.61 Hack/reduce
  • 10.62 HPCC Systems
  • 10.63 HP Enterprise
  • 10.64 Hitachi Data Systems
  • 10.65 Hortonworks
  • 10.66 IBM
  • 10.67 Illumina Inc
  • 10.68 Imply Corporation
  • 10.69 Informatica
  • 10.70 Inter Systems Corporation
  • 10.71 Intel
  • 10.72 IVD Industry Connectivity Consortium-IICC
  • 10.73 Jasper (Cisco)
  • 10.74 Juniper Networks
  • 10.75 Knome,Inc.
  • 10.76 Leica Biosystems (Danaher)
  • 10.77 Longview
  • 10.78 MapR
  • 10.79 Marklogic
  • 10.80 Mayo Medical Laboratories
  • 10.81 McKesson Corporation
  • 10.82 Medical Information Technology Inc.
  • 10.83 Medio
  • 10.84 Medopad
  • 10.85 Microsoft
  • 10.86 Microstrategy
  • 10.87 MongoDB
  • 10.88 MU Sigma
  • 10.89 N-of-One
  • 10.90 Netapp
  • 10.91 NTT Data
  • 10.92 Open Text (Actuate Corporation)
  • 10.93 Opera Solutions
  • 10.94 Oracle
  • 10.95 Palantir Technologies Inc.
  • 10.96 Pathway Genomics Corporation
  • 10.97 Perkin Elmer
  • 10.98 Pentaho (Hitachi)
  • 10.99 Platfora
  • 10.100 Qlik Tech
  • 10.101 Quality Systems Inc.
  • 10.102 Quantum
  • 10.103 Quertle
  • 10.104 Quest Diagnostics Inc.
  • 10.105 Rackspace
  • 10.106 Red Hat
  • 10.107 Revolution Analytics
  • 10.108 Roche Diagnostics
  • 10.109 Rocket Fuel Inc.
  • 10.110 Salesforce
  • 10.111 SAP
  • 10.112 SAS Institute
  • 10.113 Selventa Inc.
  • 10.114 Sense Networks
  • 10.115 Shanghai Data Exchange
  • 10.116 Sisense
  • 10.117 Social Cops
  • 10.118 Software AG/Terracotta
  • 10.119 Sojern
  • 10.120 Splice Machine
  • 10.121 Splunk
  • 10.122 Sqrrl
  • 10.123 Sumo Logic
  • 10.124 Sunquest Information Systems
  • 10.125 Supermicro
  • 10.126 Tableau Software
  • 10.127 Tableau
  • 10.128 Tata Consultancy Services
  • 10.129 Teradata
  • 10.130 ThetaRay
  • 10.131 Thoughtworks
  • 10.132 Think Big Analytics
  • 10.133 TIBCO
  • 10.134 Tube Mogul
  • 10.135 Verint Systems
  • 10.136 VolMetrix
  • 10.137 VMware
  • 10.138 Wipro
  • 10.139 Workday (Platfora)
  • 10.140 WuXi NextCode Genomics
  • 10.141 Zoomdata

11.0 Overall Big Data Market Analysis and Forecasts 2021 - 2026

  • 11.1 Global Big Data Marketplace
  • 11.2 Big Data Market by Solution Type
  • 11.3 Regional Big Data Market

12.0 Big Data Market Segment Analysis and Forecasts 2021 - 2026

  • 12.1 Big Data Market by Management Utilities 2021 - 2026
    • 12.1.1 Market for General Use Analytics Servers and related Hardware 2021 - 2026
    • 12.1.2 Market for Big Data Application Infrastructure and Middleware 2021 - 2026
    • 12.1.3 Market for Data Integration Tools and Data Quality Tools 2021 - 2026
    • 12.1.4 Big Data Market for Database Management Systems 2021 - 2026
    • 12.1.5 Big Data Market for Storage Management 2021 - 2026
  • 12.2 Big Data Market by Functional Segment 2021 - 2026
    • 12.2.1 Big Data in Supply Chain Management 2021 - 2026
    • 12.2.2 Big Data in Workforce Analytics 2021 - 2026
    • 12.2.3 Big Data in Enterprise Performance Analytics 2021 - 2026
    • 12.2.4 Big Data in Professional Services 2021 - 2026
    • 12.2.5 Big Data in Business Intelligence 2021 - 2026
    • 12.2.6 Big Data in Social Media and Content Analytics 2021 - 2026
  • 12.3 Market for Big Data in Emerging Technologies 2021 - 2026
    • 12.3.1 Big Data in Internet of Things 2021 - 2026
    • 12.3.2 Big Data in Smart Cities 2021 - 2026
    • 12.3.3 Big Data in Blockchain and Cryptocurrency 2021 - 2026
    • 12.3.4 Big Data in Augmented and Virtual Reality 2021 - 2026
    • 12.3.5 Big Data in Cybersecurity 2021 - 2026
    • 12.3.6 Big Data in Smart Assistants 2021 - 2026
    • 12.3.7 Big Data in Cognitive Computing 2021 - 2026
    • 12.3.8 Big Data in Customer Relationship Management 2021 - 2026
    • 12.3.9 Big Data in Spatial Information 2021 - 2026
  • 12.4 Big Data Market by Industry Type 2021 - 2026
  • 12.5 Regional Big Data Markets 2021 - 2026
    • 12.5.1 North America Market for Big Data 2021 - 2026
    • 12.5.2 South American Market for Big Data 2021 - 2026
    • 12.5.3 Western European Market for Big Data 2021 - 2026
    • 12.5.4 Central and Eastern European Market for Big Data 2021 - 2026
    • 12.5.5 Asia Pacific Market for Big Data 2021 - 2026
    • 12.5.6 Middle East and Africa Market for Big Data 2021 - 2026

13.0 Appendix: Big Data Support of Streaming IoT Data

  • 13.1 Big Data Technology Market Outlook for Streaming IoT Data
    • 13.1.1 IoT Data Management is a Ubiquitous Opportunity across Enterprise
    • 13.1.2 IoT Data becomes a Big Data Revenue Opportunity
    • 13.1.3 Real-time Streaming IoT Data Analytics is a Substantial Opportunity
  • 13.2 Global Streaming IoT Data Analytics Revenue 2021 - 2026
    • 13.2.1 Overall Streaming Data Analytics Revenue for IoT 2021 - 2026
    • 13.2.2 Global Streaming IoT Data Analytics Revenue by App, Software, and Services 2021 - 2026
    • 13.2.3 Global Streaming IoT Data Analytics Revenue in Industry Verticals 2021 - 2026
      • 13.2.3.1 Streaming IoT Data Analytics Revenue in Retail
        • 13.2.3.1.1 Streaming IoT Data Analytics Revenue by Retail Segment
        • 13.2.3.1.2 Streaming IoT Data Analytics Retail Revenue by App, Software, and Service
      • 13.2.3.2 Streaming IoT Data Analytics Revenue in Telecom and IT
        • 13.2.3.2.1 Streaming IoT Data Analytics Revenue by Telecom and IT Segment
        • 13.2.3.2.2 Streaming IoT Data Analytics Revenue by Telecom & IT App, Software, and Service
      • 13.2.3.3 Streaming IoT Data Analytics Revenue in Energy and Utility
        • 13.2.3.3.1 Streaming IoT Data Analytics Revenue by Energy and Utility Segment
        • 13.2.3.3.2 Streaming IoT Data Analytics Energy and Utilities Revenue by App, Software, and Service
      • 13.2.3.4 Streaming IoT Data Analytics Revenue in Government
        • 13.2.3.4.1 Streaming IoT Data Analytics Revenue by Government Segment
        • 13.2.3.4.2 Streaming IoT Data Analytics Government Revenue by App, Software, and Service
      • 13.2.3.5 Streaming IoT Data Analytics Revenue in Healthcare and Life Science
        • 13.2.3.5.1 Streaming IoT Data Analytics Revenue by Healthcare Segment
      • 13.2.3.6 Streaming IoT Data Analytics Revenue in Manufacturing
        • 13.2.3.6.1 Streaming IoT Data Analytics Revenue by Manufacturing Segment
        • 13.2.3.6.2 Streaming IoT Data Analytics Manufacturing Revenue by App, Software, and Service
      • 13.2.3.7 Streaming IoT Data Analytics Revenue in Transportation & Logistics
        • 13.2.3.7.1 Streaming IoT Data Analytics Revenue by Transportation & Logistics Segment
        • 13.2.3.7.2 Streaming IoT Data Analytics Transportation & Logistics Revenue by App, Software, and Service
      • 13.2.3.8 Streaming IoT Data Analytics Revenue in Banking and Finance
        • 13.2.3.8.1 Streaming IoT Data Analytics Revenue by Banking and Finance Segment
        • 13.2.3.8.2 Streaming IoT Data Analytics Revenue by Banking and Finance App, Software, and Service
      • 13.2.3.9 Streaming IoT Data Analytics Revenue in Smart Cities
        • 13.2.3.9.1 Streaming IoT Data Analytics Revenue by Smart City Segment
        • 13.2.3.9.2 Streaming IoT Data Analytics Revenue by Smart Cities App, Software, and Service
      • 13.2.3.10 Streaming IoT Data Analytics Revenue in Automotive
        • 13.2.3.10.1 Streaming IoT Data Analytics Revenue by Automobile Industry Segment
        • 13.2.3.10.2 Streaming IoT Data Analytics Revenue by Automotive Industry App, Software, and Service
      • 13.2.3.11 Streaming IoT Data Analytics Revenue in Education
        • 13.2.3.11.1 Streaming IoT Data Analytics Revenue by Education Industry Segment
        • 13.2.3.11.2 Streaming IoT Data Analytics Revenue by Education Industry App, Software, and Service
      • 13.2.3.12 Streaming IoT Data Analytics Revenue in Outsourcing Services
        • 13.2.3.12.1 Streaming IoT Data Analytics Revenue by Outsourcing Segment
        • 13.2.3.12.2 Streaming IoT Data Analytics Revenue by Outsourcing Industry App, Software, and Service
      • 13.2.3.13 Streaming IoT Data Analytics Revenue by Leading Vendor Platform
  • 13.3 Regional Streaming IoT Data Analytics Revenue 2021 - 2026
    • 13.3.1 Streaming IoT Data Analytics Revenue by Region 2021 - 2026
    • 13.3.2 Streaming IoT Data Analytics in Asia Pac Market Revenue 2021 - 2026
    • 13.3.3 Streaming IoT Data Analytics in Europe Market Revenue 2021 - 2026
    • 13.3.4 Streaming IoT Data Analytics in North America Market Revenue 2021 - 2026
    • 13.3.5 Streaming IoT Data Analytics in Latin America Market Revenue 2021 - 2026
    • 13.3.6 Streaming IoT Data Analytics in MEA Market Revenue 2021 - 2026
  • 13.4 Streaming IoT Data Analytics Revenue by Country 2021 - 2026
    • 13.4.1 Streaming IoT Data Analytics Revenue by APAC Countries 2021 - 2026
      • 13.4.1.1 Leading Countries
      • 13.4.1.2 Japan Market Revenue
      • 13.4.1.3 China Market Revenue
      • 13.4.1.4 India Market Revenue
      • 13.4.1.5 Australia Market Revenue
    • 13.4.2 Streaming IoT Data Analytics Revenue by Europe Countries 2021 - 2026
      • 13.4.2.1 Leading Countries
      • 13.4.2.2 Germany Market Revenue
      • 13.4.2.3 UK Market Revenue
      • 13.4.2.4 France Market Revenue
    • 13.4.3 Streaming IoT Data Analytics Revenue by North America Countries 2021 - 2026
      • 13.4.3.1 Leading Countries
      • 13.4.3.2 US Market Revenue
      • 13.4.3.3 Canada Market Revenue
    • 13.4.4 Streaming IoT Data Analytics Revenue by Latin America Countries 2021 - 2026
      • 13.4.4.1 Leading Countries
      • 13.4.4.2 Brazil Market Revenue
      • 13.4.4.3 Mexico Market Revenue
    • 13.4.5 Streaming IoT Data Analytics Revenue by ME&A Countries 2021 - 2026
      • 13.4.5.1 Leading Countries
      • 13.4.5.2 South Africa Market Revenue
      • 13.4.5.3 UAE Market Revenue

Figures

  • Figure 1: Big Data Ecosystem
  • Figure 2: Key Characteristics of Big Data
  • Figure 3: Big Data Use Cases in Industry Verticals
  • Figure 4: Big Data Stack
  • Figure 5: Framework for Big Data in IoT
  • Figure 6: NoSQL vs Legacy DB Performance Comparisons
  • Figure 7: Big Data Technology Roadmap
  • Figure 8: The Big Data Value Chain
  • Figure 9: Big Data Value Flow
  • Figure 10: Big Data Analytics
  • Figure 11: Big Data Vendor Ranking Matrix
  • Figure 12: Global Big Data Market
  • Figure 13: Big Data Market by Solution Type
  • Figure 14: Regional Market for Big Data
  • Figure 15: Big Data Market by Management Utilities
  • Figure 16: Market for Servers and Other Hardware
  • Figure 17: Market for Application Infrastructure and Middleware
  • Figure 18: Big Data Market for Data Integration Tools and Data Quality Tools
  • Figure 19: Market for Database Management Systems
  • Figure 20: Market for Storage Management
  • Figure 21: Big Data Market by Functional Segment
  • Figure 22: Big Data in Supply Chain Management
  • Figure 23: Big Data in Workforce Analytics
  • Figure 24: Big Data in Enterprise Performance Analytics
  • Figure 25: Big Data in Professional Services
  • Figure 26: Big Data in Business Intelligence
  • Figure 27: Big Data in Social Media and Content Analytics
  • Figure 28: Market for Big Data in Emerging Technologies
  • Figure 29: Big Data in Internet of Things
  • Figure 30: Big Data in Smart Cities
  • Figure 31: Big Data in Blockchain and Cryptocurrency
  • Figure 32: Big Data in Augmented and Virtual Reality
  • Figure 33: Big Data in Cybersecurity
  • Figure 34: Big Data in Smart Assistants
  • Figure 35: Big Data in Cognitive Computing
  • Figure 36: Big Data in CRM
  • Figure 37: Big Data in Spatial Information
  • Figure 38: Big Data Market by Industry Type
  • Figure 39: Big Data Applications in Transportation
  • Figure 40: Big Data Applications in Automobiles
  • Figure 41: North America Big Data Market by Solution Type
  • Figure 42: North America Big Data Market by Management Utilities
  • Figure 43: North America Big Data Market by Functional Segments
  • Figure 44: North America Market for Big Data in Emerging Technologies
  • Figure 45: North America Big Data Market by Industry Type
  • Figure 46: South America Big Data Market by Solution Type
  • Figure 47: South America Big Data Market by Management Utilities
  • Figure 48: South America Big Data Market by Functional Segments
  • Figure 49: South America Market for Big Data in Emerging Technologies
  • Figure 50: South America Big Data Market by Industry Type
  • Figure 51: Western Europe Big Data Market by Solution Type
  • Figure 52: Western Europe Big Data Market by Management Utilities
  • Figure 53: Western Europe Big Data Market by Functional Segments
  • Figure 54: Western Europe Market for Big Data in Emerging Technologies
  • Figure 55: Western Europe Big Data Market by Industry Type
  • Figure 56: Central and Eastern Europe Big Data Market by Solution Type
  • Figure 57: Central and Eastern Europe Big Data Market by Management Utilities
  • Figure 58: Central and Eastern Europe Big Data Market by Functional Segments
  • Figure 59: Central and Eastern Europe Market for Big Data in Emerging Tech
  • Figure 60: Central and Eastern Europe Big Data Market by Industry Type
  • Figure 61: APAC Big Data Market by Solution Type
  • Figure 62: APAC Big Data Market by Management Utilities
  • Figure 63: APAC Big Data Market by Functional Segment
  • Figure 64: APAC Market for Big Data in Emerging Technologies
  • Figure 65: APAC Big Data Market by Industry Type
  • Figure 66: MEA Big Data Market by Solution Type
  • Figure 67: MEA Big Data Market by Management Utilities
  • Figure 68: MEA Big Data Market by Functional Segments
  • Figure 69: MEA Market for Big Data in Emerging Technologies
  • Figure 70: MEA Big Data Market by Industry Type
  • Figure 71: Streaming IoT Data Sources Compared
  • Figure 72: Overall Streaming IoT Data Analytics

Tables

  • Table 1: Global Markets for Big Data
  • Table 2: Big Data Markets by the Type of Plan
  • Table 3: Regional Markets for Big Data
  • Table 4: Big Data Market by Management Utilities
  • Table 5: Market for Servers and Other Hardware
  • Table 6: Big Data Market for Application Infrastructure and Middleware
  • Table 7: Market for Data Integration Tools and Data Quality Tools
  • Table 8: Market for Database Management Systems
  • Table 9: Market for Storage Management
  • Table 10: Big Data Market by Functional Segment
  • Table 11: Big Data in Supply Chain Management
  • Table 12: Big Data in Workforce Analytics
  • Table 13: Big Data in Enterprise Performance Analytics
  • Table 14: Big Data in Professional Services
  • Table 15: Big Data in Business Intelligence
  • Table 16: Big Data in Social Media and Content Analytics
  • Table 17: Market for Big Data in Emerging Technologies
  • Table 18: Big Data in Internet of Things
  • Table 19: Big Data in Smart Cities
  • Table 20: Big Data in Blockchain Technology and Cryptocurrency
  • Table 21: Big Data in Augmented and Virtual Reality
  • Table 22: Big Data in Cybersecurity
  • Table 23: Big Data in Smart Assistants
  • Table 24: Big Data in Cognitive Computing
  • Table 25: Big Data in CRM
  • Table 26: Big Data in Spatial Information
  • Table 27: Big Data Market by Industry Type
  • Table 28: Big Data Applications in Transportation Market
  • Table 29: Big Data Applications in Automobiles
  • Table 30: North America Big Data Market by Solution Type
  • Table 31: North America Big Data Market by Management Utilities
  • Table 32: North America Big Data Market by Functional Segments
  • Table 33: North America Market for Big Data in Emerging Technologies
  • Table 34: North America Big Data Market by Industry Type
  • Table 35: South America Big Data Market by Solution Type
  • Table 36: South America Big Data Market by Management Utilities
  • Table 37: South America Big Data Market by Functional Segments
  • Table 38: South America Market for Big Data in Emerging Technologies
  • Table 39: South America Big Data Market by Industry Type
  • Table 40: Western Europe Big Data Market by Solution Type
  • Table 41: Western Europe Big Data Market by Management Utilities
  • Table 42: Western Europe Big Data Market by Functional Segments
  • Table 43: Western Europe Market for Big Data in Emerging Technologies
  • Table 44: Western Europe Big Data Market by Industry Type
  • Table 45: Central and Eastern Europe Big Data Market by Solution Type
  • Table 46: Central and Eastern Europe Big Data Market by Management Utilities
  • Table 47: Central and Eastern Europe Big Data Market by Functional Segments
  • Table 48: Central and Eastern Europe Market for Big Data in Emerging Tech
  • Table 49: Central and Eastern Europe Big Data Market by Industry Type
  • Table 50: APAC Big Data Market by Solution Type
  • Table 51: APAC Big Data Market by Management Utilities
  • Table 52: APAC Big Data Market by Functional Segments
  • Table 53: APAC Market for Big Data in Emerging Technologies
  • Table 54: APAC Big Data Market by Industry Type
  • Table 55: MEA Big Data Market by Solution Type
  • Table 56: MEA Big Data Market by Management Utilities
  • Table 57: MEA Big Data Market by Functional Segments
  • Table 58: MEA Market for Big Data in Emerging Technologies
  • Table 59: MEA Big Data Market by Industry Type
  • Table 60: Global Streaming IoT Data Analytics Revenue by App, Software, and Service
  • Table 61: Global Streaming IoT Data Analytics Revenue in Industry Vertical
  • Table 62: Retail Streaming IoT Data Analytics Revenue by Retail Segment
  • Table 63: Retail Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 64: Telecom & IT Streaming IoT Data Analytics Rev by Segment
  • Table 65: Telecom & IT Streaming IoT Data Analytics Rev by App, Software, and Services
  • Table 66: Energy & Utilities Streaming IoT Data Analytics Rev by Segment
  • Table 67: Energy & Utilities Streaming IoT Data Analytics Rev by App, Software, and Services
  • Table 68: Government Streaming IoT Data Analytics Revenue by Segment
  • Table 69: Government Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 70: Healthcare & Life Science Streaming IoT Data Analytics Revenue by Segment
  • Table 71: Healthcare & Life Science Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 72: Manufacturing Streaming IoT Data Analytics Revenue by Segment
  • Table 73: Manufacturing Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 74: Transportation and Logistics Streaming IoT Data Analytics Revenue by Segment
  • Table 75: Transportation and Logistics Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 76: Banking and Finance Streaming IoT Data Analytics Revenue by Segment
  • Table 77: Banking & Finance Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 78: Smart Cities Streaming IoT Data Analytics Revenue by Segment
  • Table 79: Smart Cities Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 80: Automotive Streaming IoT Data Analytics Revenue by Segment
  • Table 81: Automotive Streaming IoT Data Analytics Revenue by Apps, Software, and Services
  • Table 82: Education Streaming IoT Data Analytics Revenue by Segment
  • Table 83: Education Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 84: Outsourcing Service Streaming IoT Data Analytics Revenue by Segment
  • Table 85: Outsourcing Service Streaming IoT Data Analytics Revenue by App, Software, and Services
  • Table 86: Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 87: Streaming IoT Data Analytics Revenue in Region
  • Table 88: APAC Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 89: APAC Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 90: APAC Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 91: Europe Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 92: Europe Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 93: Europe Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 94: North America Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 95: North America Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 96: North America Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 97: Latin America Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 98: Latin America Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 99: Latin America Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 100: ME&A Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 101: ME&A Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 102: ME&A Streaming IoT Data Analytics Revenue by Leading Vendor Platforms
  • Table 103: Streaming IoT Data Analytics Revenue by APAC Countries
  • Table 104: Japan Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 105: Japan Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 106: China Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 107: China Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 108: India Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 109: India Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 110: Australia Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 111: Australia Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 112: Streaming IoT Data Analytics Revenue by Europe Countries
  • Table 113: Germany Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 114: Germany Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 115: UK Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 116: UK Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 117: France Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 118: France Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 119: Streaming IoT Data Analytics Revenue by North America Countries
  • Table 120: US Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 121: US Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 122: Canada Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 123: Canada Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 124: Streaming IoT Data Analytics Revenue by Latin America Countries
  • Table 125: Brazil Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 126: Brazil Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 127: Mexico Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 128: Mexico Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 129: Streaming IoT Data Analytics Revenue by ME&A Countries
  • Table 130: South Africa Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 131: South Africa Streaming IoT Data Analytics Revenue in Industry Verticals
  • Table 132: UAE Streaming IoT Data Analytics Revenue by Solution and Services
  • Table 133: UAE Streaming IoT Data Analytics Revenue in Industry Verticals
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