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1 Mind Commerce Commerce Publishing v3122/ Publisher Sample Phone: (US) or or (Int'l) Hours: Monday - Thursday: 5:30am - 6:30pm EST Fridays: 5:30am - 5:30pm EST MarketResearch.com

2 Sample/Excerpts ONLY Not Full Report The Big Data & Telco Analytics Market: Business Case, Market Analysis & Forecasts

3 Table of Contents 1 Chapter 1: Introduction Executive Summary Topics Covered Key Findings Target Audience Companies Mentioned 12 2 Chapter 2: Big Data Technology & Business Case Defining Big Data Key Characteristics of Big Data Volume Variety Velocity Variability Complexity Big Data Technology Hadoop MapReduce HDFS Other Apache Projects NoSQL Hbase Cassandra Mongo DB Riak 19 Page 2

4 CouchDB MPP Databases Others and Emerging Technologies Storm Drill Dremel SAP HANA Gremlin & Giraph Market Drivers Data Volume & Variety Increasing Adoption of Big Data by Enterprises & Telcos Maturation of Big Data Software Continued Investments in Big Data by Web Giants Market Barriers Privacy & Security: The Big Barrier Workforce Re-skilling & Organizational Resistance Lack of Clear Big Data Strategies Technical Challenges: Scalability & Maintenance 23 3 Chapter 3: Key Investment Sectors for Big Data Industrial Internet & M2M Big Data in M2M Vertical Opportunities Retail & Hospitality Improving Accuracy of Forecasts & Stock Management Determining Buying Patterns Hospitality Use Cases 25 Page 3

5 3.3 Media Social Media Social Gaming Analytics Usage of Social Media Analytics by Other Verticals Utilities Analysis of Operational Data Application Areas for the Future Financial Services Fraud Analysis & Risk Profiling Merchant-Funded Reward Programs Customer Segmentation Insurance Companies Healthcare & Pharmaceutical Drug Development Medical Data Analytics Case Study: Identifying Heartbeat Patterns Telcos Telco Analytics: Customer/Usage Profiling and Service Optimization Speech Analytics Other Use Cases Government & Homeland Security Developing New Applications for the Public Tracking Crime Intelligence Gathering Fraud Detection & Revenue Generation Other Sectors 31 Page 4

6 3.9.1 Aviation: Air Traffic Control Transportation & Logistics: Optimizing Fleet Usage Sports: Real-Time Processing of Statistics 31 4 Chapter 4: The Big Data Value Chain How Fragmented is the Big Data Value Chain? Data Acquisitioning & Provisioning Data Warehousing & Business Intelligence Analytics & Virtualization Actioning & Business Process Management (BPM) Data Governance 34 5 Chapter 5: Big Data in Telco Analytics How Big is the Market for Telco Analytics? Improving Subscriber Experience Generating a Full Spectrum View of the Subscriber Creating Customized Experiences and Targeted Promotions Central Big Data Repository: Key to Customer Satisfaction Reduce Costs and Increase Market Share Building Smarter Networks Understanding the Usage of the Network The Magic of Analytics: Improving Network Quality and Coverage Combining Telco Data with Public Data Sets: Real-Time Event Management Leveraging M2M for Telco Analytics M2M, Deep Packet Inspection & Big Data: Identifying & Fixing Network Defects Churn/Risk Reduction and New Revenue Streams Predictive Analytics 38 Page 5

7 5.4.2 Identifying Fraud & Bandwidth Theft Creating New Revenue Streams Telco Analytics Case Studies T-Mobile USA: Churn Reduction by 50% Vodafone: Using Telco Analytics to Enable Navigation 39 6 Chapter 6: Key Players in the Big Data Market Vendor Assessment Matrix Apache Software Foundation Accenture Amazon APTEAN (Formerly CDC Software) Cisco Systems Cloudera Dell EMC Facebook GoodData Corporation Google Guavus Hitachi Data Systems Hortonworks HP IBM Informatica Intel Jaspersoft 47 Page 6

8 6.21 Microsoft MongoDB (Formerly 10Gen) MU Sigma Netapp Opera Solutions Oracle Pentaho Platfora Qliktech Quantum Rackspace Revolution Analytics Salesforce SAP SAS Institute Sisense Software AG/Terracotta Splunk Sqrrl Supermicro Tableau Software Teradata Think Big Analytics Tidemark Systems VMware (Part of EMC) 54 7 Chapter 7: Market Analysis 55 Page 7

9 7.1 Big Data Revenue: Big Data Revenue by Functional Area: Supply Chain Management Business Intelligence Application Infrastructure & Middleware Data Integration Tools & Data Quality Tools Database Management Systems Big Data Social & Content Analytics Big Data Storage Management Big Data Professional Services Big Data Revenue by Region Asia Pacific Eastern Europe Latin & Central America Middle East & Africa North America Western Europe 71 List of Figures Figure 1: The Big Data Value Chain 32 Figure 2: Telco Analytics Investments Driven by Big Data: ($ M) 35 Figure 3: Big Data Vendor Ranking Matrix Figure 4: Big Data Revenue: ($ M) 55 Figure 5: Big Data Revenue by Functional Area: ($ M) 56 Page 8

10 Figure 6: Big Data Supply Chain Management Revenue: ($ M) 57 Figure 7: Big Data Supply Business Intelligence Revenue: ($ M) 58 Figure 8: Big Data Application Infrastructure & Middleware Revenue: ($ M) 59 Figure 9: Big Data Integration Tools & Data Quality Tools Revenue: ($ M) 60 Figure 10: Big Data Database Management Systems Revenue: ($ M) 61 Figure 11: Big Data Social & Content Analytics Revenue: ($ M) 62 Figure 12: Big Data Storage Management Revenue: ($ M) 63 Figure 13: Big Data Professional Services Revenue: ($ M) 64 Figure 14: Big Data Revenue by Region: ($ M) 65 Figure 15: Asia Pacific Big Data Revenue: ($ M) 66 Figure 16: Eastern Europe Big Data Revenue: ($ M) 67 Figure 17: Latin & Central America Big Data Revenue: ($ M) 68 Figure 18: Middle East & Africa Big Data Revenue: ($ M) 69 Figure 19: North America Big Data Revenue: ($ M) 70 Figure 20: Western Europe Big Data Revenue: ($ M) 71 Page 9

11 1 Chapter 1: Introduction 1.1 Executive Summary Big Data refers to a massive volume of both structured and unstructured data that is so large that it is difficult to process using traditional database and software techniques. While the presence of such datasets is not something new, the past few years have witnessed immense commercial investments in solutions that address the processing and analysis of Big Data. Big Data opens a vast array of applications & opportunities in multiple vertical sectors including not limited to retail & hospitality, media, utilities, financial services, healthcare & pharmaceutical, government & homeland security and the emerging industrial internet vertical. With access to vast amounts of datasets, telcos are also turning out to be major proponents of the Big Data movement. Big Data technologies, and in particular their analytics abilities offer a multitude of benefits to telcos which include improving subscriber experience, building & maintaining smarter networks, reducing churn and even the generation of new revenue streams. Mind commerce, thus expects the Big Data driven telco analytics market to grow at a CAGR of nearly 50% between 2014 and By the end of 2019, the market will eventually account for $5.4 Billion in annual revenue. This report provides an in-depth assessment of the global Big Data and telco analytics markets, including a study of the business case, application use cases, vendor landscape, value chain analysis, case studies and a quantitative assessment of the industry from 2013 till Page 10

12 1.2 Topics Covered The report will address the following key topics: The Business Case for Big Data: An assessment of the business case, growth drivers and barriers for Big Data Big Data Technology: A review of the underlying technologies that resolve big data complexities Big Data Use Cases: A review of investments sectors and specific use cases for the Big Data market The Big Data Value Chain: An analysis of the value chain of Big Data and the major players involved within it Big Data in Telco Analytics: How telcos can utilize Big Data technology to reduce churn, optimize their networks, reduce risks and to create new revenue streams Telco Case Studies: Case Studies on how two major wireless telcos are capitalizing on Big Data in reduce churn and improve revenue Vendor Assessment & Key Player Profiles: An assessment of the vendor landscape and company profiles of leading players within the Big Data market Market Analysis and Forecasts: A global and regional assessment of the market size and forecasts for the Big Data market from 2014 till 2019 Page 11

13 1.3 Key Findings Following are the key findings of the report: Big Data opens a vast array of applications & opportunities in multiple vertical sectors including not limited to retail & hospitality, media, utilities, financial services, healthcare & pharmaceutical, telcos, government & homeland security and the emerging industrial internet vertical Mind Commerce has determined that IBM leads the Big Data market in terms of current investments (from a vendor perspective), with estimated revenue for $1.3 Billion in 2012 for its Big Data services, software and hardware sale Despite challenges such as the lack of clear big data strategies, security concerns and the need for workforce re-skilling, the growth potential of Big Data is unprecedented. Mind Commerce estimates that global spending on Big Data will grow at a CAGR of 48% between 2014 and Big Data revenues will reach $135 Billion by the end of 2019 Big Data technologies, and in particular their analytics abilities offer a multitude of benefits to telcos which include improving subscriber experience, building & maintaining smarter networks, reducing churn and even the generation of new revenue streams The Big Data driven telco analytics market to grow at a CAGR of nearly 50% between 2014 and By the end of 2019, the market will eventually account for $5.4 Billion in annual revenue. Page 12

14 1.4 Target Audience The report targets the following audience. Fixed and Mobile Telcos Application Developers Big Data Technology/Solution (Infrastructure, Software, Service) Vendors Analytics and Data Reporting Companies Government Organizations Financial Institutions Healthcare Service Providers & Institutions Utilities Companies Media Companies Retail & Hospitality Companies Other Vertical Industry Players Investment Firms Page 13

15 1.5 Companies Mentioned The following companies have been mentioned in the report: Accenture Adaptive Adobe Amazon Apache Software Foundation APTEAN (Formerly CDC Software) BoA Bristol Myers Squibb Brooks Brothers Centre for Economics and Business Research CIA Cisco Systems Cloud Security Alliance (CSA) Cloudera Dell EMC Facebook Facebook GoodData Corporation Google Google Guavus Hitachi Data Systems Page 14

16 Hortonworks HP IBM Informatica Intel Jaspersoft JPMC McLaren Microsoft MongoDB (Formerly 10Gen) Morgan Stanley MU Sigma Netapp NSA Opera Solutions Oracle Pentaho Platfora Qliktech Quantum Rackspace Revolution Analytics Salesforce SAP SAS Institute Sisense Page 15

17 Software AG/Terracotta Splunk Sqrrl Supermicro Tableau Software Teradata Think Big Analytics Tidemark Systems T-Mobile TomTom US Xpress VMware (Part of EMC) Vodafone Page 16

18 2 Chapter 4: The Big Data Value Chain In this Chapter we review the value chain of the Big Data market. Data Acquisitioning and Provisioning Data Warehousing and Business Intelligence Analytics & Virtualization Actioning & Business Process Management (BPM) Data Acquisition Data Providers Data Warehousing Providers NoSQL and Content Management Providers Data Analytics Providers Data Virtualization Providers BPM Providers Business Intelligence Tool Providers Data Governance Figure 1: The Big Data Value Chain Source: Mind Commerce 2.1 How Fragmented is the Big Data Value Chain? The Big Data value chain is highly fragmented with many across playing multiple roles across the value chain. While the value chain will vary slightly for each individual investment sector, it can generally be divided into 5 logical segments, namely: Data Acquisitioning & Provisioning Data Warehousing & Business Intelligence Page 17

19 Analytics & Virtualization Actioning & Business Process Management (BPM) Data Governance [ See Full Report for More Information ] 2.2 Telco Analytics Case Studies Vodafone: Using Telco Analytics to Enable Navigation As highlighted previously, M2M services could also provide significant revenue streams from telco analytics where telcos provide monitoring or analysis services of the data content that is used within them. An example of this is analysis of road traffic that is fed back to TomTom from the Vodafone network. The TomTom Traffic service, operating via Vodafone's network, provides real-time traffic reports and information on the best alternative routes to avoid congestion and delays. TomTom also uses Vodafone s network to provide a service called TomTom HD Traffi. HD Traffic generates its traffic information from real-time, anonymous data gathered from millions of [ See Full Report for More Information ] Page 18

20 3 Chapter 6: Key Players in the Big Data Market In this Chapter we present an overview of the big data industry. 3.1 Vendor Assessment Matrix In terms of vendor assessment, Mind Commerce has determined that IBM leads the Big Data market in terms of current investments, with estimated revenue for $1.3 Billion in 2012 for its Big Data services, software and hardware sale. IBM s lead is closely followed by HP and Teradata. See Report for Vendor Ranking Figure 2: Big Data Vendor Ranking Matrix 2013 Source: Mind Commerce Page 19

21 4 Chapter 7: Market Analysis In this Chapter we assess the revenue of the Big Data market and present revenue projections from 2013 till 2019 by revenue category and region Big Data Professional Services Big Data Professional Services revenues will grow at a CAGR of 59% between 2014 and 2019, eventually reaching $56 Billion. $60,000 Professional Services $50,000 $40,000 $30,000 Professional Services $20,000 $10,000 $ Figure 3: Big Data Professional Services Revenue: ($ Million) Source: Mind Commerce [ See Full Report for All Forecast Data ] Page 20

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