RCG proposes a Big Data Proof of Concept (PoC) to demonstrate the business value of analyzing a client's data using Big Data technologies. The PoC involves: 1) Defining a business problem and objectives in a workshop with client. 2) The client collecting and anonymizing relevant data. 3) RCG loading the data into their Big Data lab and analyzing it using Big Data technologies. 4) RCG producing results, insights, and recommendations for applying Big Data and taking business actions. The PoC requires no investment from the client and provides an opportunity to explore Big Data analytics without committing resources.

1. Ideas. Realized. ®
RCG Global Services
Business Intelligence
Big Data Proof of Concept
July 2014
© 2014 RCG. All Rights Reserved. Proprietary and Confidential.

2. Big Data Architecture Goes Beyond BI
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 2
What ‘Traditional’ BI Misses . . .
“More than 80% of all data in an enterprise is unstructured
information. Unfortunately, attempts to leverage this resource
often fail because many businesses lack the technology to utilize
content that resides outside the scope of structured databases.”
Is What Big Data Is Designed to Deliver
“The practices and technology that close the gap between [all
types of] data available and the ability to turn that data into
business insight.”
[http://www.aiim.org/Research-and-Publications/Research/White-Papers/Data-is-Unstructured-Information]

3. The Big Data Landscape Is Complex
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 3

4. Big Data Challenges
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 Understanding and architecting
solutions incorporating Big Data
technologies (Hadoop, NewSQL,
NoSQL, in-memory, and so forth)
 Navigating Hadoop, its ‘projects’/
components, and packaged Hadoop
options in the market
 Knowing which Big Data solution best
meets your needs
 Planning, sizing, installing, and using a
Big Data server complex
 Incorporating Big Data into existing data
management and governance processes
 Delivering analytic results from Big
Data volumes and variety of data types,
particularly real-time data stream
analysis, ad hoc queries and searches,
and inferential analytics

5. Examples of RCG’s Big Data Experience
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 5
IT Cost Reduction
Savings of $3 million and
processing time reduction
from 4.5 hours to 1.5 hours
realized by using Big Data
technologies rather than
traditional ETL and MPP
database options
RCG’s Big Data Lab
Demonstrates Big Data
technologies and produces
Advanced Analytics Insights
with client dataClick Stream Analysis
Real time click stream
analysis and correlation
to in-store purchase history
SKU Analysis
Analyze sales, inventories,
and delivery logistics by sku
by day over years of history
using Big Data technology
and architecture
recommendations
Business Operations
Analysis
Near real-time analysis of
business operations to manage
inventories, adjust pricing, and
manage promotions
ROIC Analysis for Store
Renovations
Advanced Analytics doubled
ROIC, increased store
profitability, and reduced capital
allocated for store renovations by
$150M

6. RCG’s Big Data Offerings for Business
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 6
Demonstrates the business value of Big Data using your data
in RCG’s Big Data Lab with Big Data technologies and analytics
Requires no investment in Big Data hardware, software, or
skills in IT or business units
Big Data Proof
of Concept
Identifies how Advanced Analytics can support your business
goals and with technologies that fit in your IT environment
Provides a Roadmap of projects to deliver business value and
add the capabilities needed for successful advanced analytics
Advanced
Analytics
Roadmap
Provides business insights using inferential / predictive, real-
time data stream, text, and other advanced analytics
Applies Advanced Analytics techniques to develop business
insights by RCG Data Scientists and identifies business actions
Advanced
Analytics and
Insight

7. RCG’s Big Data Offerings for IT
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 7
Identifies the savings IT can achieve using Big Data and open
source technologies in place of further investment in high-
cost ETL products and massively parallel processing platforms
IT Cost
Reduction with
Big Data
Identifies the Big Data technologies best suited to your
environment and needs of the business and develops the
architecture that fits Big Data into your IT infrastructure
Big Data and
Advanced
Analytics
Architecture
Sizes, configures, and sets up the cluster of Big Data storage
required to support the needs of the business, installs the Big
Data software, and trains the IT staff who will monitor,
maintain, and use the Big Data installation
Big Data
Technology
Installation

8. 8
Big Data Proof of Concept (PoC)
The RCG Big Data Proof of Concept
demonstrates the business value of Big Data
using your data in RCG’s Big Data Lab with Big
Data technologies and analytics. This requires
no investment in Big Data hardware, software,
or skills in your IT or business units.

9. Big Data Proof of Concept Overview
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 9
Get statistically
significant
business insights
Apply insights to solve
the problem or
act on the opportunity
Start with a real
business problem
or opportunity
RCG’s Data
Scientists apply
Advanced Analytics
1 3
4
5
Take real
business data to
RCG’s Big Data Lab
2

10. Big Data PoC Objectives
The primary objective for RCG’s Big Data PoC is to demonstrate
the business value of Big Data analytics and business insights
using client data in RCG’s Big Data Lab.
This provides clients with:
‒ Access to RCG’s skills, experience, and facilities to jump start the
learning curve and application of Big Data analytics
‒ The ability to apply a Big Data technology of interest
‒ A low-cost, easy way to demonstrate the value of Big Data analytics
and business insights to enhance business results
The Big Data PoC requires no investment in hardware,
software, or skills in a client’s IT or business departments
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 10

11. RCG’s Big Data Lab
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 11
Our Big Data Lab has the capacity
and capability to help you make
sense of this to solve problems and
take advantage of opportunities
We can help you select
a Big Data option that
makes sense
for your company
12 nodes of Hadoop or NoSQL configuration
½ terabyte of memory
144 terabytes of storage
‘R’ and SAS statistical analysis technologies
Apache Hadoop project software
NoSQL and NewSQL options

12. Big Data PoC Approach
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Activities:
Collect data related to
the business problem,
such as customer data,
purchase history, emails,
demographics, product
data, product sales
history, and so forth
Mask sensitive data such
as names, credit card or
financial specifics, health
information, and so
forth
Client Activities:
Participate in problem
definition workshop
Approve problem
definition and its
objectives
Activities:
Conduct brief (1-2
hours) problem
statement workshop
with Business Executives
Identify an objective,
such as sales lift through
better product
recommendations or
improving healthcare
outcomes through
personalized treatments
Client Activities:
Activities:
Transmit data to RCG
(depending on the
volume of data, this can
be done over high
speed communications
or through physical
media)
Load data into RCG’s
Big Data Lab
Client Activities:
Provide collected
data for analysis
Activities:
Client Activities:
Activities:
Develop results and
insights
Make recommendations
for business actions and
for applying Big Data
Client Activities:
Review results and
insights
Review business action
recommendations
Review Big Data
recommendations
Work Products:Work Products: Work Products: Work Products: Deliverables:
File(s) of data to be
used for the PoC
Problem Statement Big Data clusters set
up in clients
technology of choice
Client data loaded
into the Big Data
cluster
Results and insights
Recommendations for
business actions
Recommendations for
implementing Big Data
Identify a
Business
Problem Area
Collect Data
Related to the
Problem Area
Load Data
into RCG’s Big
Data Lab
Apply Big
Data
Analytics
Produce
Results and
Insights
Collect data related to
the problem definition
Ensure data complies
with privacy and
regulatory policies
Review data insights
and provide
feedback
Data insights, with
their statistical
significance
Perform initial analysis
based on client
requirements
Develop and refine
statistical models to
focus on new insights
Review with client and
iterate as needed
Present current model
and define
automation/validation
process if needed

13. Big Data PoC Approach
 RCG Activities
‒ Conduct brief (1-2 hours) problem statement workshop with Business
Executives to identify:
• An objective for the PoC, such as sales lift through better product
recommendations or improving healthcare outcomes through personalized
treatments
• The data related to the business problem to analyze
• The technical environment to be set up for the PoC in RCG’s Big Data Lab
 Client Responsibility
‒ Participate in facilitated problem definition workshop
‒ Approve PoC Problem Statement
 Work Products
‒ Problem Statement
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 13
Identify a
Business
Problem Area
Collect Data
Related to the
Problem Area
Load Data
into RCG’s Big
Data Lab
Apply Big
Data
Analytics
Produce
Results and
Insights

14. Big Data PoC Approach
 RCG Activities
‒ None
 Client Responsibility
‒ Collect the data related to the business problem to analyze
‒ Mask sensitive data such as names, credit card or financial
specifics, health information, and so forth
 Work Products
‒ Collected files of data to analyze
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 14
Identify a
Business
Problem Area
Collect Data
Related to the
Problem Area
Load Data
into RCG’s Big
Data Lab
Apply Big
Data
Analytics
Produce
Results and
Insights

15. Big Data PoC Approach
 RCG Activities
‒ Set up the technical environment for the PoC
‒ Load the CLIENT’s data for analysis
 Client Responsibility
‒ None
 Work Products
‒ Collected files of data loaded into the specified technical
environment in RCG’s Big Data Lab
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 15
Identify a
Business
Problem Area
Collect Data
Related to the
Problem Area
Load Data
into RCG’s Big
Data Lab
Apply Big
Data
Analytics
Produce
Results and
Insights

16. Big Data PoC Approach
 RCG Activities
‒ Perform initial analysis based on client requirements
‒ Review insights with client
‒ Develop and refine statistical models to further focus on new insights
‒ Review with client and iterate as needed
‒ Present current model and define automation/validation process if
needed
 Client Responsibility
‒ Provide feedback on interim analysis results
 Work Products
‒ Data analysis, actionable statistical model(s) based on insights
discovered
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 16
Identify a
Business
Problem Area
Collect Data
Related to the
Problem Area
Load Data
into RCG’s Big
Data Lab
Apply Big
Data
Analytics
Produce
Results and
Insights

17. Big Data PoC Approach
 RCG Activities
‒ Develop results and insights
‒ Make recommendations for business actions and for applying Big Data
 Client Responsibility
‒ Review results and insights
‒ Review business action recommendations
‒ Review Big Data recommendations
 Deliverables
‒ Results and insights
‒ Recommendations for business actions
‒ Recommendations for implementing Big Data and Advanced Analytics
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 17
Identify a
Business
Problem Area
Collect Data
Related to the
Problem Area
Load Data
into RCG’s Big
Data Lab
Apply Big
Data
Analytics
Produce
Results and
Insights

18. Roles and Responsibilities
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 18
RCG Solution Architect
• Overall responsibility for RCG’s delivery of
the PoC
• Develops, with CLIENT, the problem
definition that the PoC will investigate
• Presents the PoC results and recommended
business actions
RCG Technical Specialist
• Implements the Big Data and Advanced
Analytics software in RCG’s Big Data Lab for
the PoC
• Loads the data collected by the CLIENT into
RCG’s Big Data Lab
RCG Data Scientist
• Provides Data Science experience and
knowledge to the project
• Develops Advanced Analytics models and
discovers data insights
• Determines the statistical significance of
these data insights and works to improve it
CLIENT's Project Manager
• Primary contact for RCG,
working to create and review
project schedule, milestones and
deliverables
• Participate in problem definition
workshop
CLIENT's Business Participants
• Provide CLIENT's business
expertise
• Participate in problem definition
workshop
• Identify information related to
the PoC’s problem definition
CLIENT's IT SMEs
• Provide CLIENT's ITs expertise
• Participate in problem definition
workshop
• Collect CLIENT’s data related to
the PoC’s problem definition

19. Big Data PoC Timeline and Fees
© 2014 RCG. All Rights Reserved. Proprietary and Confidential. 19
Project Timeline
 Estimated Duration: 3 to 5 weeks
 Estimated Total Fees: $35 - 55K, plus expenses (this does not include
fees for RCG assistance to collect and prepare data, if it is required)
 Typical Resources: Big Data Solution Architect, Data Scientist, Big Data
Technical Specialist
Activity Week 1 Week 2 Week 3 Week 4 Week 5
Identify a Business Problem Area
Collect Data Related to the Problem Area
Load Data into RCG’s Big Data Lab
Apply Big Data Analytics
Produce Results and Insights

20. Our Brand Promise
Our reputation is built upon the premise that
we are a company that listens.
We bring a creative view to your
business initiative.
We are collaborative and accountable as
we jointly create your solution.
We continuously innovate from concept to result and
help you affect business change.
There will be no surprises.
Ideas. Realized.®