BUSINESS INTELLIGENCE & ADVANCED ANALYTICS DISCOVER | PLAN | EXECUTE JANUARY 14, 2016

Channel

Organizations Diverse Data Needs

CIO Technology Priorities

Business Intelligence Defined Business Intelligence (BI) provides historical, current and predictive views of business operations and supports business decisions ranging from operational to strategic. Common functions of business intelligence technologies are reporting, online analytical processing (OLAP), analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics.

Big Data Supports and Enables BI

Big Data Defined (4 V’s) Velocity Veracity

Volume Velocity Veracity

Velocity Veracity

Variety Velocity Veracity

Velocity Veracity

Improve efficiency of operations Provide easy access to reports Deliver right data at the right time Comply with regulatory Enable better and faster decisions information repository that enables the decision makers in IT & business users and executives The right information delivered to the right people at the right time creates real value by:  Increase User Adoption & Productivity  Increase ROI  Increase confidence in decision making & compliance  Improve time to decision making  Improve human capital management  Drive accountability  Accuracy of Information THE HIGH-PERFORMANCE ENTERPRISE Right Information, Right People, Right Time

Big Data circa 1960

Why Big Data?

Governed Information Value Optimization

Why Big Data?

IoT - Fueling the Push to Big Data

Big Data - Lowers Cost

Practical Examples Fraud Detection Compliance Algorithmic Trading Smart Drugs Resource Scheduling Early Detection Churn Prevention IoT Self Driving Cars Consumer Analytics Demand Planning Omni Channel

ExamplesCharacteristicsTypical toolsAnalytical methods Small Data (megabytes) Inventory levels Hundreds – thousands of records Personal computer, Excel, SPSS, R, other basic statistics software Simple statistics Large Data (gigabytes- terabytes) Customer databasesMillions of records, mostly structured data Server workstation computer, Relational database systems, data warehouses Advanced statistics, business intelligence, data mining, Big Data (terabytes – petabytes) Customer interactions (social media, mobile), multimedia (video, images, free text), location-based data, RFIM Sales records, Customers database (small and medium companies) Cloud, data centers, Distributed databases, NoSQL, Hadoop MapReduce, Distributed File Systems, Machine Learning, Predictive Analytics ExamplesCharacteristicsTypical toolsAnalytical methods One Size Does Not Fit All

Business Intelligence Maturity & Value

Business Intelligence Best Practices Data Governance: Formation, Education & Communication Measure Quality to Manage/Enforce Quality – Master Data Management Information Value Optimization Move from Hindsight to Insight to Foresight Use existing technology investment more efficiently – Enterprise Data Warehouse 2.0 Organization: Shared Services – Shared Vision (ROI) Aligned People, Process & Technology – Right Skills Support Diverse Business Needs & Systems Best Practices: Make Good Investments Great (TCO) Repurpose planned investments to achieve organizational excellence

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