Big datacamp june14_alex_liu
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This document discusses how big data analytics can provide insights from large amounts of structured and unstructured data. It provides examples of how big data has helped organizations reduce customer churn, improve customer acquisition, speed up loan approvals, and detect fraud. The document also outlines IBM's big data platform and analytics process for extracting value from large, diverse data sources.
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Big datacamp june14_alex_liu
- 1. © 2014 IBM Corporation From Big Data to Big Insights Dr. Alex Liu – Big Data Scientist June 14, 2014 BDCamp-06-14-2014-1
- 2. © 2014 IBM Corporation Big Data is hot Cost effectively manage all available data unstructured, structured, streaming ERP CRM RFID Website Network Switches Social Media Billing
- 3. © 2014 IBM Corporation Know Everything about your Customer Analyze all sources of data to know your customers as individuals Instant Awareness of Fraud and Risk Analyze all available data, detect fraud and manage risk in real-time Innovate New Products at Speed and Scale Capture all sources of feedback and analyze vast data to drive innovation Exploit Instrumented Assets Predict and prevent maintenance, develop new products & services Big data has great potential, and can impacts every aspects … Creates customized offers up to 125x faster with better results Reduced processing time in half Loads hurricane data in seconds and performs risk analysis in near real-time for greater reliability Identified fraud which previously went undetected Capabilities Outcomes
- 4. © 2014 IBM Corporation Many organizations are already enjoying the power of using big data for big insights leading to great results • Big Data Strategy • Business Analytics Rapid and data-driven decisions consistent across the organization Business Value Use Over Time Top performers are more likely to use big data analytic approach*5.4x Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. Copyright © Massachusetts Institute of Technology 2010. *within business processes
- 5. © 2014 IBM Corporation Business-Centric Big Data Analytics Enables You to Start With a Critical Business Pain and Unleash the Power of Big Data “Big data” isn’t just a technology— it’s a business strategy for capitalizing on information resources Getting started is crucial Success at each entry point is accelerated by products within the Big Data platform Build the foundation for future requirements by expanding further into the big data platform
- 6. © 2014 IBM Corporation Big Data Analytics is a process 4Es – Equation – Estimation – Evaluation - Explanation
- 7. © 2014 IBM Corporation CASE I: Predicting Customer Churn with Big Data Analytics 20% Reduction in Churn 7x Improvement in XML Processing Time Customers Most Likely To Leave (and Why) Dropped Calls Calling Patterns (Big Data) Rate Plans Integrate/Cleanse/ Deduplicate Data Warehouse Predictive Modeling Why do people leave and how can you intervene before it’s too late? Ongoing insightMaster Data Management Key Capabilities • Customer Analytics • Predictive Analytics • Data integration with Common Metadata • Master Data Mgmt • Big Data • Warehouse Scalability • Compression and Archiving
- 8. © 2014 IBM Corporation8 CASE II: Big Data Audience Insight Analytics enables rich audience analysis and a better customer acquisition Capture, integrate and analyze data Combine data sets to measure content consumption and create audience profiles Make insights operational to drive business decisions Structured Unstructured Hadoop System Stream Computin g Data Warehous e Accelerators Information Integration & Governance IBM Big Data Platform Location Gender Occupation Influence Interests analytics Programming Distribution Marketing Ad Sales
- 9. © 2014 IBM Corporation CASE III: Improving Decision-making for Loan Origination Approval Denial Fast Track Collaboration Existing Customer Details Real-Time Data Gathering External Policies Automated Scoring/Pricing Credit Monitoring Credit Monitoring How can you maximize approval rate while minimizing risk? 6 Days to 5 seconds new loan processing Key Capabilities • Content Analytics • Advanced Case Management • Master Data Mgmt • Business Rules • Integrated Collaboration Master Data Management
- 10. © 2014 IBM Corporation CASE IV: Fraud Modeling with Big Data Big Insights Data Business Vocabulary Name, Address, Medical condition Party Contact point & Preferences Claim Communication Fraud type Assessment & Condition Standard Text & Comms Risk factor score Claim fraud assessment Task Atomic Warehouse Data industry shared database Scan all paperwork(quotations, repair invoices, previous claims by insured or by another insured based on chasis, vehicle registration to ascertain history and condition of vehicle involved in accident Claim Fraud type Claim fraud Claim fraud condition Claim fraud investigation Professional fraud exclusion clause
- 11. © 2014 IBM Corporation Thank you