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 2014 RCG. All Rights Reserved. Proprietary and Confidential. 4 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 RCGs 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 RCGs 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. RCGs 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 RCGs 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. RCGs 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 RCGs 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 RCGs Data Scientists apply Advanced Analytics 1 3 4 5 Take real business data to RCGs Big Data Lab 2 10. Big Data PoC Objectives The primary objective for RCGs Big Data PoC is to demonstrate the business value of Big Data analytics and business insights using client data in RCGs Big Data Lab. This provides clients with: Access to RCGs 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 clients IT or business departments 2014 RCG. All Rights Reserved. Proprietary and Confidential. 10 11. RCGs 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 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 2014 RCG. All Rights Reserved. Proprietary and Confidential. 12 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 RCGs 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 RCGs 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 RCGs 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 RCGs 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 RCGs 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 CLIENTs data for analysis Client Responsibility None Work Products Collected files of data loaded into the specified technical environment in RCGs 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 RCGs 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 RCGs 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 RCGs 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 RCGs 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 RCGs Big Data Lab for the PoC Loads the data collected by the CLIENT into RCGs 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 PoCs problem definition CLIENT's IT SMEs Provide CLIENT's ITs expertise Participate in problem definition workshop Collect CLIENTs data related to the PoCs 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 RCGs 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.