View
1.281
Download
7
Category
Tags:
Preview:
DESCRIPTION
For an Executive Summary of this report please contact ediz.ibrahim@visiongain.com (+44 (0)20 7549 9976) or refer to our website http://www.visiongain.com/Report/1175/Top-20-Big-Data-Companies-2014
Citation preview
©noticeThis material is copyright by visiongain. It is against the law to reproduce any of this material without the prior written agreement of vision-gain. You cannot photocopy, fax, download to database or duplicate in any other way any of the material contained in this report. Each pur-chase and single copy is for personal use only.
Top 20 Big Data Companies 2014 Competitive Landscape Analysis
www.visiongain.com
Contents 1. Executive Summary
1.1 Big Data Adoption Rising Amongst Enterprises
1.2 Big Data Proving To Be Beneficial to Organizations Across All Sectors
1.3 Big Data Benefits Outweigh the Security Risks
1.4 Ecosystem Members in the Big Data Market
1.5 Big Data Enterprise Migration Driving Growth
1.6 Aim of the Report
1.7 Structure of the Report
1.8 Report Scope
1.9 Highlights in the report include:
1.10 Who is This Report For?
1.11 Methodology
2. Introduction to the Big Data Market
2.1 The Practice of Big Data
2.2 The Concept behind Big Data
2.3 Defining the Term Big Data
2.4 Categorizing Big Data
2.5 Different Types of Big Data
2.6 Business Case for Big Data Analytics
2.7 Enterprise Application for Big Data Analytics
2.8 Big Data a Catalyst for Innovation & Productivity
2.9 Trust Issues & Security Concerns with Regards to Big Data Outsourcing
2.10 Challenges of Big Data
2.11 Big Data Processing Pipeline
2.11.1 Big Data Processing Pipeline – Major Steps
2.11.2 Big Data Processing Pipeline – Common Challenges
2.12 Big Data Technologies
2.12.1 Apache Hadoop
2.12.2 NoSQL Database
www.visiongain.com
Contents 2.12.3 Additional Big Data Technologies
2.13 Visual Representation of Big Data
3. Global Big Data Market Forecasts 2013-2018
3.1 Significant Enterprise Interest Driving the Big Data Market Forward
4. Competitor Positioning in the Big Data Market
4.1 Leading 20 Company Revenues in the Big Data Market
4.2 Composition of the Big Data Market in 2014
5. Leading 20 Companies in the Big Data Market
5.1 IBM Company Overview
5.1.1 IBM Smart Analytics System
5.2 HP Company Overview
5.3 Teradata Company Overview
5.3.1 Teradata Big Data Analytics Offering – Teradata Unified Data
5.4 Dell Company Overview
5.4.1 Kitenga Analytics Suite
5.5 Oracle Company Overview
5.5.1 Oracle Big Data Analytics Solution
5.6 SAP Company Overview
5.6.1 SAP Big Data Analytics Offering
5.7 EMC Company Overview
5.5.1 EMC Products and Services
5.8 Cisco Systems Company Overview
5.9 PwC Company Overview
5.9.1 PwC Big Data Offering
5.10 Microsoft Company Overview
5.10 Microsoft Big Data Analytics – Offerings and Advantages
www.visiongain.com
Contents 5.11 Accenture Company Overview
5.11.1 Accenture Big Data Offering
5.11.2 Accenture Big Data Services
5.12 Palantir Technologies Company Overview
5.12.1 Palantir Technologies Big Data Focus
5.12.1 Palantir Products
5.12.2 Palantir Customers and Focus
5.12.3 Palantir Big Data Analytics Services
5.13 Fusion-io Company Overview
5.13.1 Fusion-io Customers and Market Standing
5.14 SAS Institute Company Overview
5.14.1 SAS Analytics Portfolio Analysis
5.15 Splunk Company Overview
5.15.1 Splunk Big Data Analytics Offering
5.16 Deloitte Company Overview
5.16.1 Big Data Analytics Offerings
5.17 NetApp Company Overview
5.15.1 NetApp Open Solution for Hadoop
5.18 Hitachi Company Overview
5.18.1 Hitachi Big Data Analytics Offering
5.19 Opera Solutions Company Overview
5.19.1 Opera Solutions Big Data Analytics Offerings
5.20 CSC Company Overview
5.20.1 CSC Big Data Analytics Offerings Analysis
5.21 Additional Players in the Big Data Market Ecosystem
6. SWOT Analysis of the Big Data Market
7. Expert Opinion
www.visiongain.com
Contents 7.1 Deloitte
7.1.1 Deloitte Company Background and Involvement in Big Data
7.1.2 Key Trends & Recent Developments in the Big Data Market
7.1.3 Primary Drivers & Restraints of the Big Data Market
7.1.4 Expected Technological Developments in the Big Data Analytics Market
7.1.5 Leading Players in the Big Data Market
7.1.6 Competitive Landscape Outlook
7.1.7 Regional Growth Focus in the Big Data Market
7.1.8 Challenges & Opportunities in the Big Data Market
7.1.9 Final Thoughts
7.2 Fusion-io
7.2.1 Fusion-io Company Background and Involvement in Big Data
7.2.2 Key Trends & Recent Developments in the Big Data Market
7.2.3 Expected Technological Developments in the Big Data Analytics Market
7.2.4 Leading Players in the Big Data Market
7.2.5 Revenue Growth Estimates
7.2.6 Competitive Landscape Outlook
7.2.7 Regional Growth Focus in the Big Data Market
7.2.8 Challenges & Opportunities in the Big Data Market
7.2.9 Final Thoughts
7.3 IBM
7.3.1 IBM Company Background and Involvement in Big Data
7.3.2 Key Trends & Recent Developments in the Big Data Market
7.3.3 Expected Technological Developments in the Big Data Market
7.3.4 Regional Growth Focus in the Big Data Market
7.3.5 Challenges & Opportunities in the Big Data Market
7.3.6 Primary Drivers & Restraints of the Big Data Market
7.3.7 Business Case for Big Data Analytics
7.3.8 Future of IBM in the Big Data Market
7.4 Splunk
www.visiongain.com
Contents 7.4.1 Splunk Company Background and Involvement in Big Data
7.4.2 Key Trends & Recent Developments in the Big Data Market
7.4.3 Expected Technological Developments in the Big Data Analytics Market
7.4.4 Leading Players in the Big Data Market
7.4.5 Revenue Growth Estimates
7.4.6 Competitive Landscape Outlook
7.4.7 Regional Growth Focus in the Big Data Market
7.4.8 Challenges & Opportunities in the Big Data Market
8. Conclusions
8.1 Enterprise Adaption of Big Data Services
8.2 Choosing the Right Big Data Services
8.3 Increasing Availability of Public Data
8.4 Continued Growth of Big Data Analytics
8.5 Discussion
8.6 Market Share & Outlook for the 20 Leading Big Data Companies
9. Glossary
List of Tables
Table 2.1 Big Data – Defining Factors
Table 2.2 Key Types of Big Data
Table 2.3 Big Data Challenges
Table 2.4 Big Data Processing Pipeline – Major Steps
Table 2.5 Big Data Processing Pipeline – Common Challenges
Table 2.6 Apache Hadoop Modules
Table 2.7 Apache Hadoop Strengths & Limitations
Table 2.8 NoSQL vs SQL Database Summary
www.visiongain.com
Contents Table 2.9 Additional Big Data Technologies
Table 3.1 Global Big Data Market Forecast 2013-2018 ($ bn, AGR %, CAGR%, Cumulative)
Table 4.1 Leading 20 Big Data Companies 2014 (Market Ranking, Revenue, Offerings, Market
Share %)
Table 5.1 IBM Company Overview 2014 (Total Revenue, Revenue from Big Data, % Revenue
From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.2 IBM Big Data Platform - Key Capabilities
Table 5.3 IBM Big Data Platform - Supporting Services
Table 5.4 IBM Smart Analytics System Summary
Table 5.5 HP Company Overview 2014 (Total Revenue, Revenue from Big Data, % Revenue
From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.6 HAVEn Key Summary (Advantages, Description)
Table 5.7 HAVEn - Technical Specifications
Table 5.8 HAVEn Solutions
Table 5.9 Teradata Company Overview 2014 (Total Revenue, Revenue from Big Data, %
Revenue From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.10 Teradata Unified Data Architecture
Table 5.11 Dell Company Overview 2014 (Total Revenue, Revenue from Big Data, % Revenue
From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.12 Kitenga Analytics Suite - Features and Benefits
Table 5.13 Oracle Company Overview 2014 (Total Revenue, Revenue from Big Data, % Revenue
From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.14 SAP Company Overview 2014 (Total Revenue, Revenue from Big Data, % Revenue
From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.15 SAP Big Data Offerings
Table 5.16 EMC Company Overview 2014 (Total Revenue, Revenue from Big Data, % Revenue
From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.17 EMC Big Data Analytics Solutions
Table 5.18 EMC Big Data Analytics Solutions
www.visiongain.com
Contents Table 5.19 Cisco Company Overview 2014 (Total Revenue, Revenue from Big Data, % Revenue
From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.20 Cisco Big Data Offerings
Table 5.21 PwC Company Overview 2014 (Total Revenue, Revenue from Big Data, % Revenue
From Big Data, Global Market Share %, HQ, Ticker, Website)
Table 5.22 PwC Big Data Offering
Table 5.23 Microsoft Company Overview 2014 (Total Revenue, Revenue from Big Data, %
Revenue From Big Data, Global Market Share %, HQ, Ticker, Website)
Table 5.24 Microsoft Big Data Analysis Summary
Table 5.25 Accenture Company Overview 2014 (Total Revenue, Revenue from Big Data, %
Revenue From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.26 Accenture Big Data Services
Table 5.27 Palantir Technologies Company Overview 2014 (Total Revenue, Revenue from Big
Data, % Revenue From Big Data, Global Market Share %, HQ, Contact, Website)
Table 5.28 Palantir Big Data Focus
Table 5.29 Palantir Products
Table 5.30 Palantir Insurance Analytics
Table 5.31 Fusion-io Company Overview 2014 (Total Revenue, Revenue from Big Data, %
Revenue From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.32 SAS Institute Company Overview 2014 (Total Revenue, Revenue from Big Data, %
Revenue From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.33 SAS Analytics Portfolio
Table 5.34 Splunk Company Overview 2014 (Total Revenue, Revenue from Big Data, % Revenue
From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.35 Splunk Big Data Analytics Offerings
Table 5.36 Deloitte Company Overview 2014 (Total Revenue, Revenue from Big DAta, %
Revenue From Big Data, Global Market Share %, HQ, Contact, Website)
Table 5.37 Deloitte's Analytics Services
Table 5.38 NetApp Company Overview 2014 (Total Revenue, Revenue from Big Data, %
Revenue From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
www.visiongain.com
Contents Table 5.39 Hitachi Company Overview 2014 (Total Revenue, Revenue from Big Data, %
Revenue From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.40 Hitachi Big Data Analytics Offering - Features and Benefits
Table 5.41 Opera Solutions Company Overview 2014 (Total Revenue, Revenue from Big Data, %
Revenue From Big Data, Global Market Share %, HQ, Website)
Table 5.42 Operas Solutions Big Data Analytics Solutions and Services
Table 5.43 CSC Company Overview 2014 (Total Revenue, Revenue from Big Data, % Revenue
From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
Table 5.44 CSC Big Data Analytics Offerings
Table 5.45 Additional Players in the Big Data Ecosystem
Table 6.1 SWOT Analysis of the Big Data Market 2013-2018
List of Figures
Figure 2.1 Big Data Processing Pipeline - Major Steps and Common Challenges
Figure 2.2 Big Data Visualisation
Figure 3.1 Global Big Data Market Forecast 2013-2018 ($ bn, AGR%)
Figure 4.1 Leading 20 Big Data Companies Market Share 2014 (%)
Figure 5.1 IBM Big Data Market Share 2014 (%)
Figure 5.2 HP Big Data Market Share 2014 (%)
Figure 5.3 Teradata Big Data Market Share 2014 (%)
Figure 5.4 Dell Big Data Market Share 2014 (%)
Figure 5.5 Oracle Big Data Market Share 2014 (%)
Figure 5.6 SAP Big Data Market Share 2014 (%)
Figure 5.7 EMC Big Data Market Share 2014 (%)
Figure 5.8 Cisco Systems Big Data Market Share 2014 (%)
Figure 5.9 PwC Big Data Market Share 2014 (%)
Figure 5.10 Microsoft Big Data Market Share 2014 (%)
Figure 5.11 Accenture Big Data Market Share 2014 (%)
Figure 5.12 Palantir Big Data Market Share 2014 (%)
Figure 5.13 Fusion-io Big Data Market Share 2014 (%)
www.visiongain.com
Contents Figure 5.14 SAS Institute Big Data Market Share 2014 (%)
Figure 5.15 Splunk Institute Big Data Market Share 2014 (%)
Figure 5.16 Deloitte Big Data Market Share 2014 (%)
Figure 5.17 NetApp Big Data Market Share 2014 (%)
Figure 5.18 Hitachi Big Data Market Share 2014 (%)
Figure 5.19 Opera Solutions Big Data Market Share 2014 (%)
Figure 5.20 CSC Big Data Market Share 2014 (%)
Figure 5.21 Rest of the Companies Big Data Market Share 2014 (%)
Companies Mentioned in This Report
1010data
10gen
Accenture
Accion Labs, Inc.
Actian
Actuate
Acunu
Aerospike
Alacer Technology Solutions
Alteryx
Amazon
Amazon Web Services (AWS)
Apache Software Foundation (ASF)
Apixio
Apple Inc.
ArcSight
Aspera
Atos S.A.
Attivio
Autonomy
www.visiongain.com
Contents Avanade
Basho
BIConcepts IT Consulting GmbH
Big Data Partnership
Blue Coat
BlueKai
Booz Allen Hamilton
BPSolutions
Brightlight Consulting, Inc.
BTRG
Buckley Data Group LLC
Calpont
Capgemini
Centrifuge Systems
CGI
Cisco Systems
ClickFox
Cloudera
Concord
Contexti
Couchbase
Crowdflower
CSC
Daman Consulting
DataCrunchers
Dataguise
Datameer
DataPop
Datasift
dataspora
www.visiongain.com
Contents DataStax
DataXu
DDN
Dell
Deloitte
Digital Reasoning
eBay
EcoSolutions Technology Inc.
EMC
Encore Software Services
Ernst & Young (E&Y)
Ethias
Expan
F5 Networks
Factual
Findability
Fluidinfo
Focus Business Solutions
Ford
Fractal Analytics
Fujitsu Ltd.
Fusion-io
General Sentiment
GlassHouse Systems Inc.
Global Consulting Solutions LLC
Gnip
GoldBot Consulting
GoodData
www.visiongain.com
Contents GTRI
Guavus
Hadapt
Hexaware Technologies Inc
Hitachi
Hortonworks
HP
HPCC Systems
Huawei
Hyperpublic
Hyve Solutions
i2
IBM
Infochimps
Infomotion GmbH
Informatica
Information Control Corporation
In-Q-Tel
Intel
Intelligent Communication (Intelcom)
IQ Associates
iRhythm
iSoftStone Information Technology(Group) Co., Ltd
ISS Inc.
Jaspersoft
Jibes Data Analytic
Juniper Networks
Kaggle
Karmasphere
www.visiongain.com
Contents Kinetic Global Markets
Klarna
Knowesis Technology
Kognitio
KPMG
Lattice Engines
Leap Commerce
Lenovo
Level Seven
Lighthouse
Lilien LLC
Lincube Group AB
Linked-In
Logica
LucidWorks
MapR
MarkLogic
McKenney's
Mercedes
Metamarkets
Microsoft
Microstrategy
Middlecon AB
mLogica
MuSigma
Neo Technology
NES
NetApp
NewsCred
NewVantage
www.visiongain.com
Contents nfrastructure
nPario
OakStream Systems LLC
Offspring Solutions LLC
OpenHeatMap
Opera Solutions
Oracle
Palantir
Palantir Technologies
ParAccel
Paypal
Pentaho
Perficient
Perot Systems
Persistent Systems
Pervasive Software
Philips
Pivotal
Precog
PROTEUS Technologies
PwC
QlikTech
Quantum
Quid
R Square, Inc.
Rackspace
RainStor
ReadyForZero
Recommind
Recorded Future
www.visiongain.com
Contents Red Hat
reHarmony
Reply
RES
RetailNext
Revolution Analytics
Rovio
Salesforce
Samsung
SAP
SAS Institute
SaveWave
SciSpike
Seagate
Sendmail
SGI
Shanghai EC Data Information Technology Co., Ltd.
Sharpe Engineering
Siemens
SiSense
Sociocast
SoftSol
Software AG/Terracotta
Sony
Splunk
Stormpulse
Stream Integration
Sulia
Super Micro
Sybase
www.visiongain.com
Contents Systech Solutions
Systex
Tableau Software
Talend
TamGroup
Tata Consultancy
TCS
Teradata
Teralytics AG
TerraEchos
The Trade Desk
Think Big Analytics
TIBCO Software
Vertica Systems
VMware
Voci Technologies Incorporated
WANdisco
WaveStrong
Wavii
Wikipedia
WiPro
WISE MEN
Wonga
Xerox
Yahoo
ZestFinance
www.visiongain.com
Contents Government Agencies and Other Organizations Mentioned in This
Report
IMEC (Interuniversity Microelectronics Centre)
US CIA (Central Intelligence Agency)
US DoD (Department of Defense)
Page 96 Www.visiongain.com Page 96
Top 20 Big Data Companies 2014: Competitive Landscape Analysis
5.20 CSC Company Overview
Table 5.43 CSC Company Overview 2014 (Total Revenue, Revenue from Big Data, %
Revenue From Big Data, Global Market Share %, HQ, Ticker, Contact, Website)
2014
Total company revenue $bn $24.5bn
Revenue from Big Data $bn $0.17bn
% of revenue from Big Data 0.7%
Global big data market share % 1.0%
Headquarters Virginia, US.
Ticker CSC
IR Contact investorrelations@csc.com
Website www.csc.com
Source: Visiongain 2014
Figure 5.20 CSC Big Data Market Share 2014 (%)
Source: Visiongain 2014
Computer Sciences Corporation (CSC) is an American multinational corporation that provides
information technology (IT) services and professional services. CSC offers services such as:
1.0%
Page 97 Www.visiongain.com Page 97
Top 20 Big Data Companies 2014: Competitive Landscape Analysis
• IT and business process outsourcing like systems analysis, applications development,
network operations, end-user computing and data centre management;
• Emerging services such as cloud computing and cybersecurity protection, Infrastructure as a
Service (IaaS), Software as a Service (SaaS), Business Process as a Service (BPaaS),
Platform as a Service (PaaS), Big Data Managed Services and other emerging technologies
and associated service delivery model; and
• A variety of other IT and professional services, including systems integration, management
consulting, technology consulting and other professional services.
5.20.1 CSC Big Data Analytics Offerings Analysis See Table 5.46 below for a detailed summary of CSC’s big data analytics offerings.
Table 5.44 CSC Big Data Analytics Offerings
Service/Solution Description
CSC Business Intelligence
Transformation
Aims to modernize users BI environment by providing a BI strategy and
renovating users capability to achieve a blend of function, agility and cost
required to support business operations and improve organizational
performance.
CSC Data Integration and
Optimization
Combines ETL tools and proprietary methodology to focus on the complex
portions of data transformation, while modern metadata migration engines
enable the bulk of simpler data migration.
CSC Data Warehouse
Implementation
A well-implemented, integrated data warehouse delivers a single view of
core information across all functional departments and analytical systems.
CSC Enterprise Intelligence
Strategy
EI Strategy has the potential to help capitalize on the volume, variety and
velocity of both internal and external data to gain intelligence and take
effective decisions.
CSC Information Strategy and
Governance
Data strategy, roadmap and high-level business case through consultancy
service that offers prioritized, actionable recommendations to align
information assets to tactical and strategic business objectives.
Page 103 Www.visiongain.com Page 103
Top 20 Big Data Companies 2014: Competitive Landscape Analysis
7. Expert Opinion
7.1 Deloitte The following interview was conducted in December 2013. Visiongain would like to thank Jo
Coutuer, Partner at Deloitte Belgium, Public Sector Technology and Analytics, for his participation
in this interview, and providing us with an expert insight on the big data ecosystem.
7.1.1 Deloitte Company Background and Involvement in Big Data Visiongain: Please give us a little background about your company and your big data
service offerings.
Jo Coutuer: Deloitte is an international professional services company with a strong presence in
technology advisory and implementation. Deloitte focusses on transformational projects. These
are projects that lead to a substantial competitive advantage to our clients or projects that have a
strategic significance to our clients’ organisations. One of our technological advisory and
implementation fields is indeed the field of Big Data and Analytics. But before we dive into those
offerings, it is important to understand that Deloitte’s unique value proposition is its multidisciplinary
approach. Whereas Big Data is often defined as a technological challenge by IT companies,
Deloitte approaches the Big Data and Analytics topics both from the business side as well as from
the technological side. We believe that Big Data and Analytics find their reason of existence in the
way they impact our clients’ business, people, processes, ...their bottom line and shareholder
value.
Deloitte is active in three types of Big Data related activities:
1. Advisory services: we challenge our clients in their existing business models and try to find
the appropriate Big-Data-impacted business models with them. We want to make sure our clients
do not become obsolete. Another way to provide value in this segment is by using Big Data driven
techniques to deliver better insights to our clients. A petrol company asked us to prove they had
the best gas pump network for a specific audience. Instead of proving this with a generic high level
consulting approach, we combined various data sources and calculated hundreds of thousands of
potential client cases and showed the strong points and weak points in the network in a fact based,
analytical manner. The credibility and thus the value of such an advice is much higher than “gut
feeling” advice.
Recommended