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Communication Service Provider B2B Data Services: Telecom APIs and Data as a Service (DaaS) 2015 - 2020

Communication Service Provider B2B Data Services: Telecom APIs and Data as a Service (DaaS) 2015 - 2020

This product is a collection of several individual publications.

Global Communication Service Providers (CSP) have reached saturation with respect to customer penetration. Furthermore, core voice and messaging services are becoming increasingly marginalized. As fourth generation (4G) cellular via LTE is optimized globally via LTE Advanced (LTE-A), raw data services are next to realize ever shrinking margins. Recognizing this issue, certain leading CSPs offer telecom data Business-to-Business (B2B) services in a Data as a Service (DaaS) basis to various third party companies such as Over-the-Top (OTT) application providers.

Telecom data is provided over Application Programming Interfaces (API) from various CSP databases including number portability, messaging, location, and subscriber databases to name a few. Enterprise customers, OTT players, and others pay CSPs for data in a DaaS business model. This model is expected to expand globally beyond the current large CSPs to smaller CSPs, many of which are located in developing countries.

Additionally, Mind Commerce anticipates the coming of a Telecom API enabled Application Marketplace. This marketplace will be in many ways similar to those of Google and Apple with the key difference that apps rely upon CSP data delivered via APIs in a DaaS B2B business model. Finally, we see CSPs ultimately realizing that they must embrace the app marketplace to offer their own Value-added Service (VAS) apps, which they will initially target for their most important customers: enterprise.

This research evaluates CSP B2B data services opportunities. The report provides an in-depth assessment of the global Telecom Network API market, including business models, business case, best practices, value chain analysis, operator and vendor strategies, vision for the future of telecom data, and forecasts for 2015 to 2020. The report also evaluates the DaaS ecosystem including technologies, companies, and solutions. The report assesses market opportunities and provides a market outlook and forecast for 2015 to 2020. All purchases of Mind Commerce reports includes time with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This needs to be used within three months of purchasing the report.

Target Audience:

App Developers
API Aggregators
Mobile Device Vendors
Mobile Network Carriers
Data services companies
Cloud services companies
Service Bureau Companies
Data infrastructure providers
Wireless Infrastructure Vendors
Network and application integrators
Intermediaries and mediation companies
Major enterprise and businesses of all types

Report Benefits:

Forecast for DaaS through 2020
Understand the DaaS ecosystem
Identify key players and strategies
Understand DaaS technologies and tools
Recognize the importance of data mediation
Understand data management best practices
Understand the importance of managed systems
Identify the relationship between DaaS and cloud
Telecom API marketplace forecasts for 2015 – 2020
Insights from Telecom API use cases and business cases
Understand the Telecom and Enterprise API marketplace
Understand key API technologies and inter-dependencies
Identify advantages of internal Telecom API usage to carriers
Identify the long-term growth drivers for the API marketplace
Understand how the API marketplace relates to the Cloud and DaaS
Understand the untapped potential for carrier Telecom API enabled VAS

General Methodology

Mind Commerce Publishing's research methodology encompasses input from a wide variety of sources.

We rely heavily upon our Subject Matter Experts (SME) in terms of their market knowledge, unique perspective, and vision. We utilize SME industry contacts as well as previous customers and participants in our market surveys and interactive interviews.

In addition, we rely upon our extensive internal database, which contains modeling, qualitative analysis, and quantitative data. We review secondary sources and compare to our primary sources to update previous findings (for prior version reports) and/or compile baseline information for technology and market modeling.

We share preliminary models with industry contacts (select previous clients, experts, and thought leaders) to verify the veracity of initial modeling. Prior to final report production (analysis, findings, and conclusions), we engage in an internal review with internal SMEs as well as cross-expertise, senior staff members to challenge results.

We believe that forecasts should be prepared as part of an integrated process which involves both quantitative as well as qualitative factors. We follow the following 3-step process for forecasting.

Forecasting Methodology

Step 1 - Forecasts Input: The inputs for the present and historical revenues are derived from industry players. Financial and other quantitative data for individual sub-market categories are derived from original research and tested with interviews with major industry constituents.

Step 2 - Forecasting of Future Years: Mind Commerce extends forecasts based on a variety of factors including demand drivers as well as supply side data. Key success factors and assumptions are considered.

Step 3 - Validation of Data: The final step is to validate projections, which is accomplished in consultation with both internal and external industry experts, including both topic and regional experts. Adjustments are made to the forecasts based on factors identified throughout this process.

Data as a Service (DaaS) Market and Forecasts 2015 – 2020
1 Introduction
1.1 Executive Summary
1.2 Topics Covered
1.3 Key Findings
1.4 Target Audience
2 DaaS Technologies
2.1 Cloud
2.2 Database Approaches and Solutions
2.2.1 Relational Database Management System (RDBS)
2.2.2 NoSQL
2.2.3 Hadoop
2.2.4 High Performance Computing Cluster (HPCC)
2.2.5 OpenStack
2.3 DaaS and the XaaS Ecosystem
2.4 Open Data Center Alliance
2.5 Market Sizing by Horizontal
3 DaaS Market
3.1 Market Overview
3.1.1 Data-as-a-Service: A movement
3.1.2 Data Structure
3.1.3 Specialization
3.1.4 Vendors
3.2 Vendor Analysis and Prospects
3.2.1 Large Vendors: BDaaS
3.2.2 Mid-sized Vendors
3.2.3 Small Vendors: DaaS and SaaS
3.2.4 Market Size: BDaaS vs. RDBMS
3.3 Market Drivers and Constraints
3.3.1 Drivers Business Intelligence and DaaS Integration The Cloud Enabler DaaS XaaS Drives DaaS
3.3.2 Constraints Issues Relating to Data-as-a-Service Integration
3.4 Barriers and Challenges to DaaS Adoption
3.4.1 Enterprises Reluctance to Change
3.4.2 Responsibility of Data Security Externalized
3.4.3 Security Concerns are Real
3.4.4 Cyber Attacks
3.4.5 Unclear Agreements
3.4.6 Complexity is a Deterrent
3.4.7 Lack of Cloud Interoperability
3.4.8 Service Provider Resistance to Audits
3.4.9 Viability of Third-party Providers
3.4.10 No Move of Systems and Data is without Cost
3.4.11 Lack of Integration Features in the Public Cloud results in Reduced Functionality
3.5 Market Share and Geographic Influence
3.6 Vendors
3.6.1 1010data
3.6.2 Amazon
3.6.3 Clickfox
3.6.4 Datameer
3.6.5 Google
3.6.6 Hewlett-Packard
3.6.7 IBM
3.6.8 Infosys
3.6.9 Microsoft
3.6.10 Oracle
3.6.11 Rackspace
3.6.12 Salesforce
3.6.13 Splunk
3.6.14 Teradata
3.6.15 Tresata
4 DaaS Strategies
4.1 General Strategies
4.1.1 Tiered Data Focus
4.1.2 Value-based Pricing
4.1.3 Open Development Environment
4.2 Specific Strategies
4.2.1 Service Ecosystem and Platforms
4.2.2 Bringing to Together Multiple Sources for Mash-ups
4.2.3 Developing Value-added Services (VAS) as Proof Points
4.2.4 Open Access to all Entities including Competitors
4.2.5 Prepare for Big Opportunities with the Internet of Things (IoT)
4.3 Service Provider Strategies
4.3.1 Telecom Network Operators
4.3.2 Data Center Providers
4.3.3 Managed Service Providers
4.4 Infrastructure Provider Strategies
4.4.1 Enable New Business Models
4.5 Application Developer Strategies
5 DaaS based Applications
5.1 Business Intelligence
5.2 Development Environments
5.3 Verification and Authorization
5.4 Reporting and Analytics
5.5 DaaS in Healthcare
5.6 DaaS and Wearable technology
5.7 DaaS in the Government Sector
5.8 DaaS for Media and Entertainment
5.9 DaaS for Telecoms
5.10 DaaS for Insurance
5.11 DaaS for Utilities and Energy Sector
5.12 DaaS for Pharmaceuticals
5.13 DaaS for Financial Services
6 Market Outlook and Future of DaaS
6.1 Recent Security Concerns
6.2 Cloud Trends
6.2.1 Hybrid Computing
6.2.2 Multi-Cloud
6.2.3 Cloud Bursting
6.3 General Data Trends
6.4 Enterprise Leverages own Data and Telecom
6.4.1 Web APIs
6.4.2 SOA and Enterprise APIs
6.4.3 Cloud APIs
6.4.4 Telecom APIs
6.5 Data Federation Emerges for DaaS
7 Conclusions
8 Appendix
8.1 Structured vs. Unstructured Data
8.1.1 Structured Database Services in Telecom
8.1.2 Unstructured Database Services in Telecom and Enterprise
8.1.3 Emerging Hybrid (Structured/Unstructured) Database Services
8.2 Data Architecture and Functionality
8.2.1 Data Architecture Data Models and Modelling DaaS Architecture
8.2.2 Data Mart vs. Data Warehouse
8.2.3 Data Gateway
8.2.4 Data Mediation
8.3 Master Data Management (MDM)
8.3.1 Understanding MDM Transactional vs. Non-transactional Data Reference vs. Analytics Data
8.3.2 MDM and DaaS Data Acquisition and Provisioning Data Warehousing and Business Intelligence Analytics and Virtualization Data Governance
8.4 Data Mining
8.4.1 Data Capture Event Detection Capture Methods
8.4.2 Data Mining Tools
Figure 2: Cloud Computing Service Model Stack and Principle Consumers
Figure 3: DaaS across Horizontal and Vertical Segments
Figure 8: Different Data Types and Functions in DaaS
Figure 9: Ecosystem and Platform Model
Figure 10: Ecosystem and Platform Model
Figure 11: DaaS and IoT Mediation for Smartgrid
Figure 12: Internet of Things (IoT) and DaaS
Figure 13: Telecom API Value Chain for DaaS
Figure 14: DaaS, Verification and Authorization
Figure 15: Web APIs
Figure 16: Services Oriented Architecture
Figure 17: Cloud Services, DaaS, and APIs
Figure 18: Telecom APIs
Figure 19: Federated Data vs. Non-Federated Models
Figure 20: Federated Data at Functional Level
Figure 21: Federated Data at City Level
Figure 22: Federated Data at Global Level
Figure 23: Federation Requires Mediation Data
Figure 24: Mediation Data Synchronization
Figure 25: Hybrid Data in Next Generation Applications
Figure 26: Traditional Data Architecture
Figure 27: Data Architecture Modeling
Figure 28: DaaS Data Architecture
Figure 29: Location Data Mediation
Figure 30: Data Mediation in IoT
Figure 31: Data Mediation for Smartgrids
Figure 32: Enterprise Data Types
Figure 33: Data Governance
Figure 34: Data Flow
Figure 35: Processing Streaming Data
Telecom API Marketplace: Strategy, Ecosystem, Players and Forecasts 2015 – 2020
1 Introduction
1.1 Executive Summary
1.2 Topics Covered
1.3 Key Findings
1.4 Target Audience
1.5 Companies Mentioned
2 Telecom Network API Overview
2.1 Defining Network APIs
2.2 Why Carriers are Adopting Telecom Network APIs
2.2.1 Need for New Revenue Sources
2.2.2 B2B Services and Asymmetric Business Models
2.3 Telecom Network API Categories
2.3.1 Web Real-time Communications (WebRTC)
2.3.2 SMS and RCS-E
2.3.3 Presence
2.3.4 MMS
2.3.5 Location
2.3.6 Payments
2.3.7 Voice/Speech
2.3.8 Voice Control
2.3.9 Multimedia Voice Control
2.3.10 M2M
2.3.11 SDM/Identity Management
2.3.12 Subscriber Profile
2.3.13 QoS
2.3.14 ID/SSO
2.3.15 Content Delivery
2.3.16 Hosted UC
2.3.17 Directory
2.3.18 Number Provisioning
2.3.19 USSD
2.3.20 Billing of Non-Digital Goods
2.3.21 Advertising
2.3.22 Collaboration
2.3.23 IVR/Voice Store
2.4 Telecom Network API Business Models
2.4.1 Two-Sided Business Model
2.4.2 Exposing APIs to Developers
2.4.3 Web Mash-ups
2.5 Segmentation
2.5.1 Users by Segment
2.5.2 Workforce Management
2.6 Competitive Issues
2.6.1 Reduced TCO
2.6.2 Open APIs
2.6.3 Configurability
2.7 Percentage of Applications that use APIs
2.8 Telecom API Revenue Potential
2.8.1 Standalone API Revenue vs. Finished Goods Revenue
2.8.2 Telecom API-enabled Mobile VAS Applications
2.8.3 Carrier Focus on Telecom API’s for the Enterprise
2.9 Telecom Network API Usage by Industry Segment
2.10 Telecom Network API Value Chain
2.10.1 Telecom API Value Chain
2.10.2 How the Value Chain Evolve
2.10.3 API Transaction Value Split among Players
2.11 Cost for Different API Transactions
2.12 Volume of API Transactions
3 API Aggregation
3.1 The Role of API Aggregators
3.2 Total Cost Usage for APIs with Aggregators
3.2.1 Start-up Costs
3.2.2 Transaction Costs
3.2.3 Ongoing Maintenance/Support
3.2.4 Professional Services by Intermediaries
3.3 Aggregator API Usage by Category
3.3.1 An LBS Case Study: LOC-AID
3.3.2 Aggregation: Intersection of Two Big Needs
3.3.3 The Case for Other API Categories
3.3.4 Moving Towards New Business Models
4 Enterprise and Telecom API Marketplace
4.1 Data as a Service (DaaS)
4.1.1 Carrier Structured and Unstructured Data
4.1.2 Carrier Data Management in DaaS
4.1.3 Data Federation in the DaaS Ecosystem
4.2 API Market Makers
4.2.1 mashape
4.2.2 Mulesoft
4.3 Need for a New Type of Application Marketplace: CAM
4.3.1 Communications-enabled App Marketplace (CAM)
4.3.2 CAM Market Opportunities and Challenges
5 Telecom API Enabled App Use Cases
5.1 Monetization of Communications-enabled Apps
5.1.1 Direct API Revenue
5.1.2 Data Monetization
5.1.3 Cost Savings
5.1.4 Higher Usage
5.1.5 Churn Reduction
5.2 Use Case Issues
5.2.1 Security
5.2.2 Interoperability
6 Non-Telecom Network APIs and Mash-ups
6.1 Non-Telecom Network APIs
6.1.1 Twitter
6.1.2 Netflix API
6.1.3 Google Maps
6.1.4 Facebook
6.1.5 YouTube
6.1.6 Flickr
6.1.7 eBay
6.1.9 Amazon Web Services
6.1.10 Bing Maps
6.1.11 Yahoo Web Search API
6.2 Mash-ups
6.2.1 BBC News on Mobile
6.2.2 GenSMS emailSMS
6.2.3 Foursquare
6.2.4 Amazon SNS and Nexmo
6.2.6 MappyHealth
6.2.7 Lunchflock
6.2.8 Mobile Time Tracking
6.2.9 Fitsquare
6.2.10 GeoSMS
6.2.11 FONFinder
6.2.12 Pound Docs
6.2.13 140Call
6.2.14 Salesforce SMS
7 Carrier Strategies
7.1 Carrier Market Strategy and Positioning
7.1.1 Increasing API Investments
7.1.2 The Rise of SDM
7.1.3 Telecom API Standardization
7.1.4 Carrier Attitudes towards APIs: U.S vs. Asia Pacific and Western Europe
7.2 Carrier API Programs Worldwide
7.2.1 AT&T Mobility
7.2.2 Verizon Wireless
7.2.3 Vodafone
7.2.4 France Telecom
7.2.5 Telefonica
7.3 Carriers and Internal Telecom API Usage
7.3.1 The Case for Internal Usage
7.3.2 Internal Telecom API Use Cases
7.4 Carriers and OTT Service Providers
7.4.1 Allowing OTT Providers to Manage Applications
7.4.2 Carriers Lack the Innovative Skills to Capitalize on APIs Alone
7.5 Carriers and Value-added Services (VAS)
7.5.1 The Role and Importance of VAS
7.5.2 The Case for Carrier Communication-enabled VAS
7.5.3 Challenges and Opportunities for Carriers in VAS
8 API enabled App Developer Strategies
8.1 A Critical Asset to Developers
8.2 Stimulating the Growth of API Releases
8.3 Working alongside Carrier Programs
8.4 Developer Preferences: Google vs Carriers
9 Telecom API Vendor Strategies
9.1 Positioning as Enablers in the Value Chain
9.2 Moving Away from a Box/Product Supplier Strategy
9.3 Telecom API Companies and Solutions
9.3.1 Alcatel Lucent
9.3.2 UnboundID
9.3.3 Twilio
9.3.4 LOC-AID
9.3.5 Placecast
9.3.6 Samsung
9.3.7 AT&T Mobility
9.3.8 Apigee
9.3.9 2600 Hz
9.3.10 Callfire
9.3.11 Plivo
9.3.12 Tropo (now part of Cisco)
9.3.13 Urban Airship
9.3.14 Voxeo (now Aspect Software)
9.3.15 TeleStax
9.3.16 Intel
9.3.17 Competitive Differentiation
10 Market Analysis and Forecasts
10.1 Telecom Network API Revenue 2015 - 2020
10.2 Telecom Network APIs Revenue by API Category 2015 – 2020
10.2.1 Messaging API Revenues
10.2.2 LBS API Revenues
10.2.3 SDM API Revenues
10.2.4 Payment API Revenues
10.2.5 Internet of Things (IoT) API Revenues
10.2.6 Other API Revenues
10.3 Telecom API Revenue by Region 2015 - 2020
10.3.1 Asia Pacific
10.3.2 Eastern Europe
10.3.3 Latin & Central America
10.3.4 Middle East & Africa
10.3.5 North America
10.3.6 Western Europe
11 Technology and Market Drivers for Future API Market Growth
11.1 Service Oriented Architecture (SOA)
11.2 Software Defined Networks (SDN)
11.3 Virtualization
11.3.1 Network Function Virtualization (NFV)
11.3.2 Virtualization beyond Network Functions
11.4 The Internet of Things (IoT)
11.4.1 IoT Definition
11.4.2 IoT Technologies
11.4.3 IoT Applications
11.4.4 IoT Solutions
11.4.5 IoT, DaaS, and APIs (Telecom and Enterprise)
12 Expert Opinion: TeleStax
13 Expert Opinion: Twilio
14 Expert Opinion:
15 Expert Opinion: Nexmo
16 Appendix
16.1 Research Methodology
16.2 Telecom API Definitions
16.3 More on Telecom APIs and DaaS
16.3.1 Tiered Data Focus
16.3.2 Value-based Pricing
16.3.3 Open Development Environment
16.3.4 Specific Strategies Service Ecosystem and Platforms Bringing to Together Multiple Sources for Mash-ups Developing Value-added Services (VAS) as Proof Points Open Access to all Entities including Competitors Prepare for Big Opportunities with the Internet of Things (IoT)
Figure 1: Wireless Carrier Assets
Figure 2: Telecom API: Standalone vs. Finished Services
Figure 3: RCS and Telecom API Integration
Figure 4: RCS Revenue Forecast
Figure 5: Business vs. Consumer Telecom API Focus
Figure 6: Enterprise Dashboard
Figure 7: Enterprise Dashboard App Example
Figure 8: Telecom Network API Value Chain
Figure 9: Value Split among Aggregators, Carriers and Enterprise for API Transactions: 2012 - 2019
Figure 10: API Transaction Costs (US Cents) 2012 - 2019
Figure 11: Volume of API Transactions for a Tier 1 Carrier (Billions per Month): 2015 - 2020
Figure 12: Cloud Services and APIs
Figure 13: GSMA OneAPI: Benefits to Stakeholders
Figure 14: AT&T Wireless API Catalog
Figure 15: Verizon Wireless API Program
Figure 16: France Telecom (Orange) APIs
Figure 17: Telefonica APIs
Figure 18: Carrier Internal Use of Telecom APIs
Figure 19: UnboundID’s Portfolio of Services
Figure 20: Twilio’s Portfolio of Services
Figure 21: LOC-AID Exchange Server Architecture
Figure 22: Placecast’s ShopAlerts Solution
Figure 23: Apigee Portfolio of Services
Figure 24: Telecom API Revenue (USD Billions) 2015 - 2020
Figure 25: Telecom API Revenue (USD Billions) by API Category 2015 - 2020
Figure 26: Messaging APIs Revenue (USD Billions) 2015 - 2020
Figure 27: LBS APIs Revenue (USD Billions) 2015 - 2020
Figure 28: SDM APIs Revenue (USD Billions) 2015 - 2020
Figure 29: Payment APIs Revenue (USD Billions) 2015 - 2020
Figure 30: IoT API Revenue (USD Billions) 2015 - 2020
Figure 31: APIs Revenue for Other Categories (USD Billions) 2015 - 2020
Figure 32: Telecom API Revenue (USD Billions) by Region 2015 - 2020
Figure 33: Telecom API Revenue (USD Billions) Asia Pacific 2015 - 2020
Figure 34: Telecom API Revenue (USD Billions) Eastern Europe 2015 - 2020
Figure 35: Telecom API Revenue (USD Billions) Latin & Central America 2015 - 2020
Figure 36: Telecom API Revenue (USD Billions) Middle East & Africa 2015 - 2020
Figure 37: Telecom API Revenue (USD Billions) North America 2015 - 2020
Figure 38: Telecom API Revenue (USD Billions) Western Europe 2015 - 2020
Figure 39: Services Oriented Architecture
Figure 40: Growth of Connected Devices
Figure 41: IoT and Telecom API Topology
Figure 42: Telestax App Store Funnel
Figure 43: On-Premise vs. Twilio
Figure 44: and API Ecosystem
Figure 45: Different Data Types and Functions in DaaS
Figure 46: Ecosystem and Platform Model
Figure 47: Telecom API and Internet of Things Mediation
Figure 48: DaaS and IoT Mediation for Smartgrid

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