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TMCNet:  Carrier B2B Data Revenue Analysis & Forecasts 2018-2023: Big Data, Analytics, Telecom APIs, and Data as a Service (DaaS) - Evaluates the Technologies, Companies, Strategies, and Solutions

[March 11, 2019]

Carrier B2B Data Revenue Analysis & Forecasts 2018-2023: Big Data, Analytics, Telecom APIs, and Data as a Service (DaaS) - Evaluates the Technologies, Companies, Strategies, and Solutions

DUBLIN, March 11, 2019 /PRNewswire/ -- The "Carrier B2B Data Revenue: Big Data, Analytics, Telecom APIs, and Data as a Service (DaaS) 2018-2023" report has been added to ResearchAndMarkets.com's offering.

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This research evaluates telecom data, analytics, APIs, and provides a quantitative and qualitative and assessment of carrier prospects for B2B revenue as a DaaS provider including forecast data and key insights respectively. It 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 2018 to 2023. This research also evaluates the technologies, companies, strategies, and solutions for DaaS.

Telecommunications service providers acquire and maintain substantial structured and unstructured (Big) data. Leading carriers have centralized Subscriber Data Management (SDM) systems, which consolidate and organize data from various sources such as HLR, HSS, and other data repositories. In addition, carriers have access to a plethora of data from various "Big Data" sources such as OSS/BSS, system monitoring and performance management systems including Self Organizing Networks (SON).

Big Data and related Analytics solutions open a vast array of applications and opportunities for telecom carriers to offer services in multiple industry verticals. Solutions for managing unstructured data are evolving beyond systems aligned towards primarily human-generated data (such as social networking, messaging, and browsing habits) towards increasingly greater emphasis upon machine-generated data found across many industry verticals. For example, manufacturing and healthcare are anticipated to create massive amounts of data that may be rendered useful only through advanced analytics and various Artificial Intelligence (AI) technologies. Emerging networks and systems such as IoT and edge computing will generate substantial amounts of unstructured data, which will present both technical challenges and market opportunities for operating companies and their vendors.

Network operators may sell data in a "Data as a Service" (DaaS) model to various market sectors including retail and hospitality, media, utilities, financial services, healthcare and pharmaceutical, telecommunications, government, homeland security, and the emerging industrial Internet vertical. DaaS is defined as any service offered wherein users can access vendor provided databases or host their own databases on vendor managed systems.

It assesses business opportunities for enterprise use of own data, others data, and a combination of both. It also analyzes opportunities for enterprise to monetize their own data through various third-party DaaS offerings. Additionally, it evaluates opportunities for DaaS in major industry verticals as well as the future outlook for emerging data monetization. Forecasts include global and regional projections by Sector, Data Collection, Source, and Structure from 2018 to 2023. This research is also the most comprehensive research covering the telecom API and programmable telecoms ecosystem including players, platforms, tools, solutions, and service offerings.

Select Findings:

  • Total global Telecom API related revenue will reach $319.6B by 2023
  • Telecom API support of IoT remains a high priority cellular operator-only opportunity
  • North America and Western Europe represent the two largest regional markets for DaaS
  • Edge Computing related Telecom API revenue will reach $395M in North America by 2023
  • IoT DaaS is growing nearly three times as fast as non-IoT DaaS, with much of it streaming data
  • Global IoT platform and authentication API revenue reaches $5.3B and $9.2B respectively by 2019
  • Structured data market remains greater than unstructured, but the latter will overtake the former
  • Machine-sourced data is growing twice as fast as non-machine data, largely due to IoT apps and services

Select Report Benefits:

  • Identify key Big Data players and strategies
  • Understand business case for enterprise Big Data
  • DaaS segmentation by Structure, Source, Sector, and Collection
  • Identify leading companies and solutions for Telecom API enabled apps and services
  • Identify leading DaaS companies, strategies, and solutions offering enterprise solutions
  • Understand the market dynamics, players, and outlook for communication enabled apps
  • Understand the market dynamics for the Data as a Service market including leading services

Key Topics Covered:

Data as a Service (DaaS) Market: Enterprise, Industrial, Public and Government DaaS 2018-2023

1. Executive Summary
1.1 Global Data as a Service Market
1.2 Data as a Service Market by Data Type
1.3 Data as a Service Market by Region

2. Data as a Service Technologies
2.1 Cloud Computing and DaaS
2.2 Database Approaches and Solutions
2.3 Data as a Service and the XaaS Ecosystem
2.4 Open Data Center Alliance
2.5 Market Sizing by Horizontal

3. Data as a Service Market
3.1 Market Overview
3.2 Vendor Analysis and Prospects
3.3 Data as a Service Market Drivers and Constraints
3.4 Barriers and Challenges to DaaS Adoption
3.5 Market Share and Geographic Influence
3.6 Vendors

4. Data as a Service Strategies
4.1 General Strategies
4.2 Strategies for Emerging Market Opportunities
4.3 Service Provider Strategies
4.4 Infrastructure Provider Strategies
4.5 Application Developer Strategies

5. Data as a Service Applications
5.1 Business Intelligence
5.2 Development Environments
5.3 Verification and Authorization
5.4 Reporting and Analytics
5.5 Data as a Service in Healthcare
5.6 Data as a Service and Wearable Technology
5.7 Data as a Service in he Government Sector


5.8 Data as a Service for Media and Entertainment
5.9 Data as a Service for Telecoms
5.10 Data as a Service for Insurance
5.11 Data as a Service for Utilities and Energy Sector
5.12 Data as a Service for Pharmaceuticals
5.13 Data as a Service for Financial Services

6. Market Outlook and Future of Data as a Service
6.1 Security Concerns
6.2 Cloud Trends
1.1 General Data Trends
6.3 Enterprise Leverages own Data and Telecom
6.4 Data Federation Emerges for Data as a Service

7. Data as a Service Market Analysis and Forecasts 2018 - 2023
7.1 DaaS Market by Sector: Business, Public, and Government
7.2 DaaS Market by Source: Machine and Non-Machine Data
7.3 DaaS Market by Data Collection: IoT and Non-IoT Data
7.4 DaaS Markets by Hosting Type: Private, Public, and Hybrid
7.5 DaaS Markets by Pricing Model
7.6 DaaS Market by Service
7.7 DaaS Markets by Industry Vertical

8. Regional DaaS Market Analysis and Forecasts 2018 - 2023
8.1 North America Data as a Service Market
8.2 South America Data as a Service Market
8.3 Western Europe Data as a Service Market
8.4 Central & Eastern European Data as a Service Market
8.5 Asia Pacific Data as a Service Market
8.6 Middle East and Africa Data as a Service Market

9. Conclusions and Recommendations

10. Appendix
10.1 Structured vs. Unstructured Data
10.2 Data Architecture and Functionality
10.3 Data Governance
10.4 Master Data Management
10.5 Data Mining

Big Data Market: Business Case, Market Analysis and Forecasts 2018-2023

1 Executive Summary

2 Introduction
2.1 Big Data Overview
2.2 Research Background

3 Big Data Challenges and Opportunities
3.1 Securing Big Data Infrastructure
3.2 Unstructured Data and the Internet of Things

4 Big Data Technology and Business Case
4.1 Big Data Technology
4.2 Emerging Technologies,Tools, and Techniques
4.3 Big Data Roadmap
4.4 Market Drivers
4.5 Market Barriers

5 Key Sectors for Big Data
5.1 Industrial Internet and Machine-to-Machine
5.2 Retail and Hospitality
5.3 Media
5.4 Utilities
5.5 Financial Services
5.6 Healthcare and Pharmaceutical
5.7 Telecommunications
5.8 Government and Homeland Security
5.9 Other Sectors

6 The Big Data Value Chain
6.1 Fragmentation in the Big Data Value
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 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

8 Standardization and Regulatory Initiatives
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 Global Markets and Forecasts for Big Data
9.1 Global Big Data Markets 2018 - 2023
9.2 Regional Markets for Big Data 2018 - 2023
9.3 Leading Countries in Big Data
9.4 Big Data Revenue by Product Segment 2018 - 2023

10 Key Big Data Players
10.1 Vendor Assessment Matrix
10.2 1010Data (Advance Communication Corp.)
10.3 Accenture
10.4 Actian Corporation
10.5 Alteryx
10.6 Amazon
10.7 Anova Data
10.8 Apache Software Foundation
10.9 APTEAN (Formerly CDC Software)
10.10 Booz Allen Hamilton
10.11 Bosch Software Innovations: Bosch IoT Suite
10.12 Capgemini
10.13 Cisco Systems
10.14 Cloudera
10.15 CRAY Inc.
10.16 Computer Science Corporation (CSC)
10.17 DataDirect Network
10.18 Dell EMC
10.19 Deloitte
10.20 Facebook
10.21 Fujitsu
10.22 General Electric (GE)
10.23 GoodData Corporation
10.24 Google
10.25 Guavus
10.26 HP Enterprise
10.27 Hitachi Data Systems
10.28 Hortonworks
10.29 IBM
10.30 Informatica
10.31 Intel
10.32 Jasper (Cisco Jasper)
10.33 Juniper Networks
10.34 Longview
10.35 Marklogic
10.36 Microsoft
10.37 Microstrategy
10.38 MongoDB (Formerly 10Gen)
10.39 MU Sigma
10.40 Netapp
10.41 NTT Data
10.42 Open Text (Actuate Corporation)
10.43 Opera Solutions
10.44 Oracle
10.45 Pentaho (Hitachi)
10.46 Qlik Tech
10.47 Quantum
10.48 Rackspace
10.49 Revolution Analytics
10.50 Salesforce
10.51 SAP
10.52 SAS Institute
10.53 Sisense
10.54 Software AG/Terracotta
10.55 Splunk
10.56 Sqrrl
10.57 Supermicro
10.58 Tableau Software
10.59 Tata Consultancy Services
10.60 Teradata
10.61 Think Big Analytics
10.62 TIBCO
10.63 Verint Systems
10.64 VMware (Part of EMC)
10.65 Wipro
10.66 Workday (Platfora)

11 Appendix: Big Data Support of Streaming IoT Data
11.1 Big Data Technology Market Outlook for Streaming IoT Data
11.2 Global Streaming IoT Data Analytics Revenue
11.3 Regional Streaming IoT Data Analytics Revenue
11.4 Streaming IoT Data Analytics Revenue by Country

Telecom API Market Outlook and Forecasts 2018-2023

1 Executive Summary

2 Introduction
2.1 About the Report
2.2 Programmable Telecom
2.3 State of the Industry

3 Telecom API Overview
3.1 Role and Importance of Telecom APIs
3.2 Business Drivers for CSPs to Leverage APIs
3.3 Telecom API Categories
3.4 Telecom API Business Models
3.5 Segmentation
3.6 Competitive Issues
3.7 Applications that use APIs
3.8 Telecom API Revenue Potential
3.9 Telecom API Usage by Industry Segment
3.10 Telecom API Value Chain
3.11 API Transaction Cost by Type
3.12 Volume of API Transactions

4 API Aggregation
4.1 Role of API Aggregators
4.2 Total Cost of Operation with API Aggregators
4.3 Aggregator API Usage by Category

5 Telecom API Marketplace
5.1 Data as a Service (DaaS)
5.2 API Marketplace Companies
5.3 Telecom API Ecosystem Vendors
5.4 Telecom Application Development

6 Telecom API Enabled App Use Cases
6.1 Monetization of Communications-enabled Apps
6.2 Use Case Issues

7 Communication Service Provider Telecom API Strategies
7.1 Carrier Market Strategy and Positioning
7.2 Select Network Operator API Programs
7.3 Carrier Focus on Internal Telecom API Usage
7.4 Carriers and OTT Service Providers
7.5 Carriers and Value-added Services

8 API Enabled Application Developer Strategies
8.1 Treating Telecom APIs as a Critical Developer Asset
8.2 Judicious Choice of API Releases
8.3 Working alongside Carrier Programs
8.4 Developer Preferences: OTT Service Providers vs Carriers

9 Telecom API Vendor Strategies
9.1 General Strategies
9.2 Specific Strategies

10 Telecom API Market Analysis and Forecasts
10.1 Global Telecom API Market 2018 - 2023
10.2 Regional Telecom API Market 2018 - 2023

11 Technology and Market Drivers for API Market Growth
11.1 Service Oriented Architecture
11.2 Software Defined Networks
11.3 Virtualization
11.4 Internet of Things
11.5 IoT WANs and Telecom APIs

12 Conclusions and Recommendation
12.1 Overall Telecom API Outlook

13 Appendix
13.1 Telecom API Definitions
13.2 More on Telecom APIs and DaaS
13.3 Monetizing IoT APIs

Company Profiles

  • 1010data
  • 3i Data Scraping
  • Accenture PLC
  • Actifio
  • Acxiom Corporation
  • Alibaba Group Holding Limited (China)
  • Alteryx Ltd.
  • Amazon Web Services Inc. (AWS)
  • Amdocs
  • Apaleo Marketplace
  • Apidaze
  • Apifonica
  • Appier.com
  • Aspect Software
  • AtScale Inc.
  • Bandwidth
  • BICS
  • Bloomberg Finance L.P.
  • CA Technologies
  • Cisco Systems Inc.
  • Clickfox
  • CLX Communications
  • Column technologies
  • comScore Inc.
  • Continental vAnalytics
  • Coriolis Technologies
  • Corporate360
  • Crunchbase, Inc.
  • CTERA
  • Datameer
  • Datasift Inc.
  • DataStax Inc
  • Dawex Systems
  • DC Frontiers Pte. Ltd.
  • Dell EMC
  • Demandbase (Whotoo)
  • Denodo Technologies
  • Dow Jones & Company, Inc.
  • Dremio
  • EMC Corporation
  • Equifax, Inc.
  • Ericsson
  • ESRI, Inc.
  • Experian plc
  • Facebook, Inc.
  • Factiva
  • Fico
  • FirstRain, Inc.
  • Fortumo
  • GE Predix
  • getsix group
  • Gigaspaces
  • Google Inc.
  • Guavus Inc.
  • Hewlett Packard Enterprise
  • HG Data Company
  • Hitachi Data Systems
  • Hoover's
  • Hortonworks
  • hSenid Mobile
  • Huawei
  • Hubtel
  • IBM Corporation
  • IHS Inc
  • Infochimps
  • Infogix, Inc.
  • Informatica Corporation
  • Information Builders Inc.
  • Information Resources, Inc
  • Infosys
  • Intel
  • Intercontinental Exchange, Inc.
  • Intuit
  • Iota Foundation
  • Ipedo
  • IQM Corporation
  • K2View
  • KBC global
  • LexisNexis Group
  • LinkedIn Corporation
  • LocationSmart
  • MapR Technologies Inc
  • MariaDB
  • Mashape
  • MasterCard Advisors
  • MessageBird
  • Microsoft Corporation
  • Mighty AI, Inc.
  • Mindtree
  • Mobilewalla
  • Moody's Corporation
  • Morningstar, Inc
  • Mulesoft
  • Nielsen Holdings Plc
  • Nokia Networks
  • Opera Solutions LLC
  • Optum, Inc.
  • Oracle Corporation
  • Pentaho
  • Persistent Systems
  • PlaceIQ, Inc.
  • Protel I/O
  • Qlik Technologies Inc.
  • Qubole
  • Quest Software
  • Rackspace
  • Red Hat
  • Ribbon Communications
  • Salesforce.com
  • SAP SE
  • SAS Institute
  • SiteMinder Exchange
  • SlamData
  • SMARTe Inc.
  • SnapLogic
  • Snapshot (On Demand)
  • Snowflake Computing
  • Splunk
  • Syniverse
  • Talend
  • TeleStax
  • Telnyx
  • Teradata
  • Terbine
  • Terracotta
  • The Dun & Bradstreet Corporation
  • The Weather Company, LLC
  • Thomson Reuters Corp.
  • ThoughtSpot Inc.
  • TIBCO Software Inc
  • Tresata
  • Twilio
  • Twitter, Inc.
  • Tyntec
  • Urban Mapping
  • Verizon Communications, Inc.
  • Vidyo
  • Vonage
  • Wisers Information Limited
  • Wolters Kluwer N.V.
  • workday
  • Xignite
  • ZertoZerto

For more information about this report visit https://www.researchandmarkets.com/research/dg9ft8/carrier_b2b_data?w=5

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