1.
Big Data
Decision Support

2.
Why Big Data
Big Data has the potential to deliver both better data and better understanding, but only for organizations that
invest the necessary resources in business processes, management actions and technology to master the trend
Gartner CEO & Business Leadership Survey 2011
o Growth opportunity - Fastest growing sector in the IT industry
o 50 % CAGR through 2020, a 44x increase – IDC 2011
o Big Data plays a significant economic role to the benefit of private commerce and national
economies - McKinsey Global Institute 2011
o Large technology vendors making significant multi-billon investments
o Big Data is in its infancy, therefore there is a lack of qualified resources and
mature processes
o Enterprises are just now realizing that data could be a valued asset that will
produce new revenue opportunities

3.
Big Data Defined
Big Data means all data, including both transaction and
interaction data, in sets whose size or complexity exceeds the
ability of commonly used technologies to capture, manage, and
process at a reasonable cost and timeframe.

4.
Big Data Drives Big Investments
• CSC
• Purchases $70M Marion Systems Big Data and Analytics Consulting
Company
• IBM
• Purchased Cognos, BI software vendor; Netezza, a data warehouse
vendor
• HP
• Purchased Vertica, a data warehouse software vendor; Autonomy,
Europe's 2nd largest software vendor after SAP helps companies discern
meaning from text-based content
• EMC
• Purchased Greenplum, a data warehouse vendor; Isilon, a large scalable
network storage company
Big Data capabilities acquisitions exceeds $9B over past 2 years

5.
Solving Big Data
• There is a shortage of analytical and managerial talent necessary to make the
most of the big data
– Greater than 190,000 Deep Data Analytical skills analysts and more than 1.5 M managers and
business data analysts - McKinsey Global Institute 2011
• Traditional approaches to managing data are insufficient to deliver the value of
Big Data; introducing substantial business risk
– Rising data volumes obscure visibility into opportunities and threats.
– Data complexity compromises compliance.
– Ceaseless streams of real-time data from multiple channels degrade customer sales and service
• Not deriving Value from Big Data
– 43% of companies surveyed recently are dissatisfied with the tools that filter out irrelevant data
– 46% of companies surveyed say they have made inaccurate decisions as a result of bad or outdated data
“Big Data is a disruptive force and an immediate problem that is already affecting
traditional understanding and business models.” Gartner 2011

6.
Making Big Data Pay
• In industries like: Financial Services; Consumer Industries - Retail, Travel
and Hospitality, Healthcare, Biotech and Pharmaceuticals, Manufacturing,
Telecommunications, new decisions from Big Data
– Attract and retain customers
– Enable targeted cross-sell
– Use to better understand, sell to and service customers, manage brand reputation and
leverage word-of-mouth marketing
– Strengthen Fraud Detection, risk management and compliance
– Electronic Medical Records
– Optimize logistics
– Inventory Management
– GPS and mapping data can streamline supply chain efficiency
– Tune products and services to deliver fast-changing customer demands using social
network analytics

7.
Why Capstone
o Our Experienced Big Data People
o More than 150 years experience in data analytics
o Industry Best Practices (innovative, proprietary processes)
o Assessment and Discovery
o Organizational Change Management
o Sales and Marketing Analytics
o Proven business success
o Grew technology services business with increased profits over last 3.5 years
o Architect and contractor for a storage services business of a Fortune 500 System
Integrator, now generating $20M annually
o Grew technology sales region from $80M to $400M in two years
o Built technology partnerships that lead to $200M in new services revenue

8.
Our Solutions
Capstone provides turn-key immediate resources for Big Data
Integration and Management of Big Data Challenges
SERVICES FUNCTIONS TECHNOLOGY
Decision
Support
Analytics &
Reporting
Business Analytics
Sentiment Analysis
Business Intelligence
Application Development
Business Reporting
Market Analysis
Customer Analysis
Operational Analysis
Cost Benefit Analysis
SAS
Cognos
Alterain
Data
Warehouse
Management
System
Discovery & Assessment
Design & Architecture
DB & DW Development
Migration
Performance Management
Upgrading
Installing
Testing
Training
Database
Data Warehouse
Data Backup &
Recovery
EMC Greenplum
Apache Hadoop
Data Movers
Storage Systems
Backup software &
hardware
Decision
Support
Data
Assembly
Data Governance
Data Integration
Data Profiling
ETL & ELT
Data Quality, Cleansing
Master Data Mgt
Data Staging
OCM
Informatica
Infrastructure
Data Protection
BCDR
Consolidation
Backup
Optimization
Management
Migration &
Replication
Virtualization
Storage Systems
Backup software &
hardware
Data Movers
SANpulse

9.
Business Analytics
• Provide a Structured and Disciplined Approach to Business
Analytics/Data Warehouse Alignment
• Create a design specifically for the customers culture,
current capabilities, analytic requirements, and priorities
• Use a four step process
– Discovery
– GAP Analysis
– Review
– Finalization

10.
Business Analytics
• During Discovery, Interview Stakeholders
– What analytics are required and why
– What analytic tools are used and how
• During Discovery, Review Current Artifacts
– What data is stored currently and why
– How data is stored and retrieved
• Conduct GAP Analysis
• Review Proposed Direction with Stakeholders
• Develop and Deliver Implementation Plan

11.
Self Service BI
• Big Data’s value is limited if the business depends on
delivering it
• Empower business users to access data based on business
terms and semantic metadata
• Accelerate data integration projects through reuse,
automation and collaboration
• Minimize errors and ensure consistency by accurately
translating business requirements into data integration
mappings and quality rules

12.
Big Data Integration Services
• Unleashing the potential of Big Data requires the ability to access and
integrate data of any scale, from any source
• Combining interaction data with transaction data to enable insights not
possible any other way
– 50M Tweets and over 60M Facebook updates daily representing insights into what
they like and don’t like
• Example: using social media data to drive revenue by attracting and
retaining customers
• Social media fans can double as sales people, triggering viral word-of-mouth purchasing among friends and
friends of friends in a broad sphere of influence that makes these customers uniquely valuable
• The opposite is true with poor customer service

13.
Single Source of Truth
• Master Data Management (MDM) and Data Quality
– Enable organizations to achieve better business outcomes by delivering
authoritative, trusted data to business processes, applications and
analytics, regardless of the diversity or scope
– The diversity and complexity of Big Data can worsen the data quality
problems in organizations
• According to CIO magazine report; 46% of surveyed respondents say they have
made an inaccurate business decision based on bad or outdated data.

14.
Big Data Infrastructure Services

15.
Data Protection Solutions
Data Lifecycle
Management
Backup/Recov
ery
Business
Continuity/
Disaster
Recovery
Recovery
Planning and
Management
Big Data Infrastructure Services

16.
IT Strategy &
Business GAP
Solutions
Strategic and Tactical
Systems Planning
Architecture and Design
Review
Organization Efficacy
Business & Executive
Communications
Planning
Business Case
Development
Performance
Benchmarking
Big Data Infrastructure Services

17.
[Name]
[Phone number]
[email]