III JORNADAS DE DATA MINING

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1 III JORNADAS DE DATA MINING EN EL MARCO DE LA MAESTRÍA EN DATA MINING DE LA UNIVERSIDAD AUSTRAL PRESENTACIÓN TECNOLÓGICA IBM Alan Schcolnik, Cognos Technical Sales Team Leader, IBM Software Group. IAE - Pilar, 12 y 13 de agosto de 2008

2 Accelerate information on demand with dynamic warehousing & Performance Management Solutions Alan Schcolnik IBM Corporation Cognos Tech Sales - Team Leader Mexico & SSA

3 Leveraging Information to Create Business Value Insightful, Relevant Information When and Where it s Needed Information On Demand Optimize Each Transaction Call Centers, Field Ops Help Solve Crimes by Delivering Suspect List to Detectives Arriving at the Crime Scene OLAP & Data Mining Merchandising, Inventory, Operations Optimizing Police Force Deployments Query & Reporting Financials, Sales Crime Rate Reports 3

4 Dynamic Warehousing A New Approach to Leveraging Information Information On Demand to Optimize Real-Time Processes Dynamic Warehousing Dynamic Warehousing Requires: OLAP & Data Mining to Understand Why and Recommend Future Action 1. Real-time access in context Traditional Data 2. Analytics as part of a business process Warehousing Query & Reporting 3. Unstructured information extracted knowledge to Understand 4. Extended infrastructure tightly integrated What Happened 4

5 Information On Demand Unlocking the Business Value of Information Customer & Product Profitability Financial Risk Insight Workforce Optimization Business Optimization Dynamic Supply Chain Offerings Multi-Channel Marketing Industry Models, Blueprints & Frameworks IBM Cognos 8 BI IBM Cognos Now! IBM Cognos 8 Planning Flexible Architecture for Leveraging Existing Investments IBM InfoSphere Warehouse IBM InfoSphere MDM Server IBM Information Server Other Information Sources DB2, IMS, Informix IBM Content Manager, IBM FileNet 5

6 Dynamic warehousing Extending beyond the warehouse to enable information on demand Search and text analytics Information integration Process management Enterprise data modeling Dynamic Warehouse Industry perspective Master data management 6

7 More Examples of Dynamic Warehousing in Action Enabling Information On Demand for Business Advantage Traditional warehousing Insurance fraud analysis and reporting Reporting on customer issues Historical sales analysis and reporting Dynamic warehousing Identifying potentially fraudulent claims prior to approval and payment Transforms healthcare Identifying possible related issues, churn risk and crosssell opportunities while engaged with the customer Transforms customer service Discovering relevant customer information to identify cross sell opportunities and improve negotiating position at the point of sale Transforms sales effectiveness 7

8 Why is it a challenge for organizations to leverage information effectively? Information distributed in silos across the organization Volume and variety of information increasing Velocity of business driving real-time requirements Not accurate Not complete Not trusted Not timely Increased need to aggregate and analyze information dynamically 8

9 Creates challenges for traditional warehousing Not just for traditional query and reporting purposes anymore Warehouses must now: Address expanding needs for analytics and information on demand Leverage ALL types of information, including unstructured Serve increasing numbers and types of applications and users, with varying service level demands Increasingly mixed workload environments and the constantly changing needs of different business constituents require more dynamic warehousing capabilities 9

10 IBM provides more than just a warehouse DB2 Warehouse provides extended capabilities and value Embeddable analytics (Inline and as a Service) Multidimensional analysis Data mining and visualization Beyond traditional structured data Generate and leverage knowledge from unstructured information Traditional IBM DB2 Warehouse warehouse Data Volumes Unstructured Structured OLTP As a direct effect of the mixed workload, with continuous DW loading and the increase in automated transactions from the Dedicated Benefits of a transactional functional analytics in OLTP, the transactional DBM Ss have an edge that challenges the DW DBM Ss (such as Teradata) data server foundation Deep compression warehousing Optimized for real-time access, Gartner Data DBMS Reduced Warehouse storage Magic costs Quadrant, 2006 Shared-nothing architecture High availability and reliability Better disk utilization Advanced data partitioning Scalable, secure and auditable Query speed improvement Workload management 10

11 IBM DB2 Warehouse software A complete, integrated platform Embedded analytics Modeling and design Data mining and visualization Data partitioning Performance optimization Workload control In-line analytics Deep compression Data movement and transformation Administration and control Database management IBM DB2 Warehouse 11

12 Introducing IBM Balanced Warehouse TM A fast track to warehousing Balanced Configuration Unit (BCU) Preconfigured, pretested allocation of software, storage and hardware to support a specified combination of function and scale SIMPLE FLEXIBLE OPTIMIZED Balanced Warehouse Simplicity Predefined configurations for reduced complexity One number to contact for complete solution support Flexibility for growth Add BCUs to address increasing demands Multiple on-ramps for different needs Reliable, nonproprietary hardware for reusability Optimized performance Preconfigured and certified for guaranteed performance Based on best practices for reduced risk Better than an appliance 12

13 Embedded mining with integrated tools Seamless integration of analytics capabilities Drag-and-drop interface Seamlessly add specific analytics and mining operations into a data flow and specify the attributes in the pane below Filter required data directly in the warehouse Get the subset of products that you are interested in performing market basket analysis on. Integrated data movement and transformation capabilities allow you to do to this in line within mining processes. 13

14 Deliver inline visualization and analytics Embedded analytics capabilities 14

15 Introducing IBM OmniFind Analytics Edition Rich analysis interface for combining structured and unstructured data Combines search, text analytics and data visualization Unstructured analytics framework Analysis tools Original Data Structured Data Call Taker: James Date: Aug. 30, 2002 Duration: 10 min. CustomerID: ADC00123 Category Extracted metadata [Call Taker] James [Date] 2002/08/30 [Duration] 10 min. [CustomerID] ADC00123 Item Search, visualization and interactive mining D: Complained about rejected claim for antibiotics; form req d more information Linguistic analysis [type] complaint [issue] denied claim [service] prescription [resolution] add l info Unstructured data Mining engine 15

16 Data Mining Enhancing Business Insight with Predictive Analytics Data Warehouse Selected Data Extracted Information Select Transform Mine Assimilate Assimilated Information Statistician & Data Mining Workbench Business Analyst DB2 Warehouse Easy Mining algorithms Associations Which item affinities ( rules ) are in my data? [Beer => Diapers] single transaction Sequences Which sequential patterns are in my data? [Love] => [Marriage] => [Baby Products] sequential transactions Clustering Which interesting groups are in my data? customer profiles, store profiles Classification How to predict categorical values in my data? will the patient be cured, harmed, or unaffected by this treatment? Prediction How to predict numerical values in my data? how likely a customer will respond to the promotion how much will each customer spend this year? Score data directly in DB2, scalable and real time 16

17 Performance Management Vision Finance Sales Operations Marketing How are we doing? Scorecards and Dashboards Why? Reporting & Analytics Customer Service IT/Systems Human Resources What should we be doing? Planning, Forecasting and Budgeting 17

18 Industry data models Leverage industry best practices for faster time to market Over 400 Customers! Banking (Banking Data Warehouse) Financial Markets (Financial Markets Data Warehouse) Health Plan (Health Plan Data Warehouse) New Offering! Profitability Risk management Claims Relationship marketing Risk management Asset and liability management Asset and liability management Compliance Medical management Provider and network Sales, marketing and membership Compliance Financials Insurance (Insurance Information Warehouse) Retail (Retail Data Warehouse) Telco (Telecommunications Data Warehouse) Customer centricity Claims Intermediary performance Compliance Risk management Enhanced Capabilities! Customer centricity Merchandising management Store operations and product management Supply chain management Compliance Churn management Relationship management and segmentation Sales and marketing Service quality and product lifecycle Usage profile 18

19 What is the value of information? Information availability is key to addressing business challenges Business challenge Optimize business processes Impact of information availability Ability to make better decisions, faster Improve customer service Increase employee productivity A more holistic and accurate picture of customers and their needs Less time wasted searching for answers Reduce risks and address regulatory compliance More than 60% of CEOs need to do a better job leveraging information Greater transparency provides ability to avoid risks and detect potential threats 70% of employee time spent searching for relevant information 19

20 Information on Demand is needed Where can business insights provide the most value? Who is using business intelligence tools today? Who can get most value out of business insights? IT Power (Analysts) Business (Managers) Casual (Front Line) Extended IT Power (Analysts) Business (Managers) Casual (Front Line) Extended 20

21 Business Advantage through Information on Demand Faster access to information improves business performance Challenge Integrate disparate data sources to support more accurate store and product performance analysis Speed responsiveness to changing business conditions and better understand store and product performance information Key to success An integrated end-to-end retail warehousing solution with pre-existing industry models and embedded analytics that could generate insight into all aspects of the core business Company profile A leading specialty retailer of children s clothing Business benefits Drastically reduced model development time and decreased query time from days to just seconds, helping speed responsiveness to variable business conditions Ability to address customer needs and behavior analyses, fraud detection, and store location and merchandising optimization through a single platform 21

22 Business Advantage through Information on Demand Visibility into relevant information improves customer service and sales Challenge Consolidate claims transactions from several thousand providers with structured and unstructured data distributed across multiple systems into a single data warehouse instance Develop a centralized view of medical provider information including unstructured data to improve terms negotiation leverage Key to success In-context delivery of knowledge from structured and unstructured information distributed across the organization and beyond Company profile An independent, not-for-profit health benefits company serving more than five million people Business benefits Single view into all revenue for a provider across multiple programs, identification of provider requests for new facilities and access to existing contracts during negotiations Categorization and understanding of customer service issues and access to provider demographic and service offerings for improved support 22

23 IBM is the leading provider of data warehousing Industry leaders use DB2 for warehousing 11 of the top 12 banks 7 of the top 8 auto manufacturers 5 of the top 6 insurance companies 4 of the top 6 general merchandisers 4 of the top 5 specialty retailers 3 of the top 4 food and drug stores IBM is ranked as a leader in Gartner s Magic Quadrant for Data Warehouse Database Management Systems

24 IBM enables dynamic warehousing Delivering greater value from information More dynamic and balanced approach to warehousing is key Broad set of capabilities beyond the warehouse required IBM provides the most comprehensive platform to address these needs 24

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