Big Data: Strategic Investment Opportunities for IT Heavyweights & Other Investors
Arjunvasan Ambigapathy
Case Topic Description:With big data being a challenge for CIOs and CEOs in manufacturing, retail, healthcare, energy and finance industries, there is increasing demand for data-driven decision-making technologies that enable companies to deliver value to both their customers and for themselves. This demand creates both opportunities and challenges for big IT vendors such as IBM, Oracle, HP, EMC and Microsoft to create value to their customers and investors. The following presentation are the efforts to explain CIOs, CEOs of Big IT vendors and other strategic investors to leverage opportunity in big data market from an technology investment stand-point. This presentation should support big IT vendors not only to enable their customer transform from traditional business intelligence (BI) platforms to operational business intelligence (BI) platforms, but also help them retain existing market share (BI) and gain competitive advantage in the big data market through strategically investing in pure-play big data vendors with innovative solutions.Target Audience: CIOs and CEOs of Big IT Vendors like Oracle, IBM, HP, EMC etc. Additional audience include VCs and other strategic investors in big data markets
Healthcare
Manufacturing
Retail
Financial Services
Energy
Media & Communication
Clinical datasets
fradulant claims
claims data
retail purchase history
adverse drug reactions
medical records
laboratory reports
labor agencies
extensive electronic imaging
multimedia content
regulatory filings
tax filing activities
identified inconsistencies
product information
sales forecasts
sales channels
online interactions
catalogs, stores
blogs
instrumented production machinery
computer-aided design
R&D and product design databases
demand forecast data
Big Data Explosion
0
Reconcile Disparate Data Sources
Data Quality/Accuracy
Lack of Organizational View of Data
Accessing Right Data
Risk of Data Leaks
Data Security
Timeliness of Data
High Data Management Costs Storage
Capacity
CIO
Cha
lleng
e Th
erm
omet
er
We have too much data, but too few resources
Our organization lack right skills to effectively manage data
There is lack of analytical skills to create value from data
We can’t get data into right people in the organization
Top Challenges for CIO’s
An
Unm
et D
eman
d fo
r CIO
s
Volume
Value
Variety Velocity
Big Data Technology in
Demand
Technology for Big Data?: The Need of the Hour
Demand for technology that can process large volume of data
(Terabytes, Records, Transactions, Tables/files)
Demand for technology that can process various types of
data (batch neartime, realtime, streams)
Demand for technology that can quickly process data
(Structured, unstructured, semistructured, etc)
How Enterprises Create Value from Data through Analytics? The Big Data Era!
2006 2008 2010
CIOs focused Towards Data Storage
CIO Technology Adoption Roadmap
CIO will focus towards Big Data Analytics
SQL-based Business Intelligence OLAP Framework
Map Reduce Text Mining
Data Visualization
Storage Solutions
Cloud Computing
Advanced Analytics
Predictive Analytics
Mobile Business Intelligence
In-memory Analytics
Comprehensive Applications: Analytics across Industry Verticals
• Initial data warehouse model and architecture
• Limited use analytical data due to fewer business analysts
• CIO (Chief Information Officer) level of engagement in data management is limited
• Few KPI (Key Performance Indicators) in Revenue Generation were found
• Standardized data models• Database mining, high
performance computing and analytical appliances
• Tech savvy analytical modelers and statisticians were used
• CIO involves in data management strategies
• Significant impact in revenues were monitored and measured regularly
• Clear data management strategy• Business analytics competency
centers are established with data scientists
• Solve complex problems through competency centers
• CIO plays a transformative role in decision taken by the organization
• Frame new business strategy and competitive differentiation based on analytics
Departmental Analytics Enterprise Analytics Big Data Analytics
CIOs used Traditional Business Intelligence tools
Source: Arjunvasan, Cisco Systems
Global Big Data Investment Scenario (2009-12)
The total investment in Big Data technologies have improved from 6
deals in 2009 to 25 deals in 2011
Total funding in Big Data Analytics have improved
from $76.5 Million in 2009 to $700 Million in
2011
Investors are actively investing in technologies
developed by new market players
Top Investors
Top Beneficiaries
N S
E
W
Investor Inclinations Vs. Top Big Data Technology Segments
Hadoop Applications
Big Data Analytics PlatformsBig Data-as-a-service
Non-Hadoop Platforms
Investment Opportunity Analysis for IT Solution Developers & other Investors
Opportunity Strategy Evaluation (OSE) Grid
Hadoop Distributions
Next Generation Data
Warehousing
Big Data Analytic
Platforms & ApplicationsBig Data-as-a-
Service
Non-Hadoop Big Data Platforms
0
5
10
0 5 10
Probability of Success
Level
of
Att
arc
tivess
Big Data Analytics Platforms and Applications
With increasing demand among organizations to generate value from their existing abundant data, investing in Big Data Analytics Platform Developers is poised for success
Hadoop DistributionsVC funding has increased phenomenally in this market sub-segment with 266% increase in funding from beginning of 2008 to 2011. Cloudera, HortonWorks, MapR, Opera Solutions are few major beneficiaries in VC funding with few portfolios in Series D. Companies focus on certification & training programs in big data
Non-Hadoop Big Data Platforms have long-term (2-3 years) success assured, as far as the penetration of this technology is concerned. Companies in this segment have been attracting VC funding and from other investor sources. The recent IPO of Splunk has created huge waves in this market segment.
Non-Hadoop Big Data Platforms
Next Generation Data WarehousingThe importance of next-generation data warehousing solutions is evident from the recent acquisitions of vendors (Vertica by HP in 2011; Greenplum by EMC in 2010 and AsterData by Teradata in 2011). This segment is more matured, unless new innovations emerge in future
Big Data-as-a-ServiceThis market segment is poised to grow tremendously in future, as its implementation saves cost in the form of recruiting ‘data scientists’ and big data infrastructure costs. R&D investment and solving implementation barriers will increase the probability of success for investors
Opportunistic Big Data Technology Segments
NOTEInvestment opportunity analysis was performed based on analysis of each big data technology segments under the following factors:
• Level of Attractiveness: Sunk Cost, Demand from Industry Verticals, Favorable Government/Regulatory Initiatives and Barriers to Market Entry• Probability of Success: Research Efforts, Challenges to Tackle, Criticality of Challenges, Funding
Analyst Insights
Source: Arjunvasan
Big Data Analytics Platforms vendors are strategic partners within the big data industry. They drive industry growth by partnering with vendors from other big data technology segments
With evaluated high probability of success, Hadoop Distributions vendors (such as Cloudera) can make best strategic investment partners in the near term (1-2 years).
IPO
Strategic Investment Options for IT Heavyweights & Venture CapitalistsSe
ries
ASe
ries
BSe
ries
CSe
ries
D
Hadoop Distributions
Non-Hadoop Big Data Platforms
Big Data Analytic Platforms & Applications
Big Data-as-a-Service
Next Generation Data Warehousing
Big Data Market Segments
Revenue from Big Data as a % of Total Revenue0% 25% 50% 75% 100%
Fund
ing
Serie
s (in
Seg
men
ts)
Each
Seg
men
t sho
ws
Big
Dat
a Re
venu
es o
f pur
e-pl
ay v
endo
rs in
big
da
ta s
egm
ent $
0 - $
50 m
illio
n
Big Data-as-a-Service vendors have potential to make big wave in the Enterprise Software market, but funding is needed to improve few technical barriers
Very few seed investments indicate that it is time to start investing in these technologies
Stra
tegi
c In
vest
men
t Opti
ons
Current Funding Status Vs. Financial Performance of Key PortfoliosTop Strategic Investors
NOTE:• Suggestions for strategic investments quoted in the above chart is based on performance of innovative, pure-play big data solution developers, level of funding and revenues. It is vital to ensure the suggested strategic investment fits well with your business model and customer demands
• Big data innovations have been primarily from pure-play companies, which have lured investment in the form of venture funding and through IPO (Initial Public Offering). In addition to connecting with venture capitalists, it is also important to evaluate IP (Intellectual Portfolio) of each segment to make an informed decision
Source: Arjunvasan, Wikibon
2007
2008
2009
2010
2011
2012
Cranes
Data IntegrationBusiness Intelligence
Data Qualty
Enterprise Resource Planning
Data Mining
Database
Infrastructure
Risk
R&D Data Management
Reporting
Storage
Planning Analysis
Content Management
Text Mining
Predictive Analysis
Charts
Data Analysis
Web Analytics
•Predictive Analysis to help companies differentiate, compete and succeed
•BI solutions that address business specific and industry vertical issues
•Independent performance layer that fits enterprise infrastructure
Demands Transform Technologies!
2017
Traditional Business Intelligence
Operational Business IntelligenceTechnology Transformation
Leveraging the Big Data Opportunity
Mergers & Acquisitions
• There is a greater demand for IT organizations to integrate Hadoop into existing database to gain competitive advantage in the industry.
• With mature sales channels and support services, Cloudera and MapR Technologies could be prospective candidates for strategic investment
• Market consolidation is expected by 2017 and will be worth $50 billion
Technology Transition from Business Intelligence to Big Data IntelligenceM&A Strategy for Big IT Vendors
Top Investors
Top Technologies
Big Data market (shows
consolidation trend similar to
Business Intelligence
market (from 2007 to 2008)
For more details:Arjunvasan [email protected]: +91-9962361689