Zhangxi Lin

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ISQS 6339, Data Management Business
IntelligenceIntroduction

• Zhangxi Lin
• Texas Tech University

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• \\TechShare\coba\d\isqs3358

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Outline

• Definitions of BI
• Categorizations of BI
• BI Trend
• BI tools

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Online Video

• Business intelligence and data warehousing 613
• What is business intelligence? 1036

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What is Business Intelligence

• A Simple Definition The applications and
  technologies transforming Business Data into
  Action
• Business intelligence (BI) is a business
  management term
• refers to applications and technologies which are
  used to gather, provide access to, and analyze
  data and information about their company
  operations.
• Business intelligence systems can help companies
  gain more comprehensive knowledge of the factors
  affecting their business, and help companies to
  make better business decisions.
• YouTube
• What is BI? B, 2
• Microsoft Business Intelligence Surface Demo 634

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Data, information, and knowledge

• Data a collection of raw value elements or
  facts used for calculating, reasoning, or
  measuring.
• Information the result of collecting and
  organizing data in a way that establishes
  relationship between data items, which thereby
  provides context and meaning
• Knowledge the concept of understanding
  information based on recognized patterns in a way
  that provides insight to information.

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The process of BI

• Data -gt information -gt knowledge -gt actionable
  plans
• Data -gt information the process of determining
  what data is to be collected and managed and in
  what context
• Information -gt knowledge The process involving
  the analytical components, such as data
  warehousing, online analytical processing, data
  quality, data profiling, business rule analysis,
  and data mining
• Knowledge -gt actionable plans The most important
  aspect in a BI process

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Actionable Knowledge

• An information asset retains its value on if the
  converted knowledge is actionable.
• Need some methods for extracting value from
  knowledge
• This is not a technical issue but an
  organizational one need empowered individuals
  in the organization to take the action
• There is an issue of Return on Investment (ROI)

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BI Problems

• Structured
• Detecting Credit card fraud
• Setting Loan parameters
• Market segmentation/Mass customization
• Deciding Marketing mix
• Customer Churn
• Reducing employee turnover
• Improving Quality/Efficiency
• Unstructured
• Data exploration
• Utilization of resources (stored knowledge) to
  maximum effectiveness

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BI Applications

• Customer Analytics
• Customer profiling
• Targeted marketing
• Personalization
• Collaborative filtering
• Customer satisfaction
• Customer lifetime value
• Customer loyalty
• Sales Channel Analytics
• Marketing
• Sales performance and pipeline

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BI Applications (2)

• Supply Chain Analytics
• Supplier and vendor management
• Shipping
• Inventory control
• Distribution analysis
• Behavior Analysis
• Purchasing trends
• Web activity
• Fraud and abuse detection
• Customer attrition
• Social network analysis

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Why is BI getting hot?

• Demands from processing explosive information
• MIS/ERP
• Internet
• Gartner Says Business Intelligence Software
  Market to Reach 3 Billion in 2009 Gartner's CIO
  Survey ranked BI as number one technology
  priority for 2006London, UK, 7 February 2006 -
  New license revenue in the worldwide business
  intelligence (BI) software market is poised for
  constant growth through 2009, when the market is
  projected to reach 3 billion in 2009, according
  to the latest forecasts by Gartner Inc. In 2006,
  the market is estimated to reach 2.5 billion, a
  six percent increase from 2005.

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Explosion of digitally born data

• 55 in personal PCs
• 16 in corporate data warehouses
• Internet only 21 TB
• Email 500x more than Internet / year

• Sources
• http//www2.sims.berkeley.edu/research/projects/
  how-much-info-2003/execsum.htm,
• The Expanding Digital Universe, IDC white
  paper, March 2007

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BI Job Description - BI Analyst (1)

• Description Looking for professionals in
  Microsoft Business Intelligence and Data
  Warehousing who have a proven track record of
  success within industry. The position requires a
  broad range of skills and the ability to step in
  to different roles depending on the size and
  scope of an engagement both internally and at
  client sites. The qualified candidate would have
  proven experience developing successful
  Microsoft-based Business Intelligence and Data
  Warehouse solutions.
• Requirements 10 years of experience
  developing Business Intelligence solutions with
  Microsoft database, ETL and OLAP technologies
  (SQL Server, SSIS, Analysis Services)
  Demonstrated understanding of multi-dimensional
  database design and architecture. Ability to
  develop business requirements and translate them
  into a data warehouse dimensional model.
  Demonstrated ability to develop front-end
  reporting and analytical solutions that meet the
  business needs. Microsoft SQL Server data
  modeling and development (10 years) Microsoft
  SQL Server Analysis Services design and
  development (5 years) Microsoft SQL Server
  Integration Services (2 years) Microsoft SQL
  Server Reporting Services design and
  development Understanding of Data Warehouse
  Methodologies, preferably using Kimball
  Methodology Demonstrated leadership aptitude
  and ability to work effectively within a team
  environment

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BI Analyst (2)

• Microsoft SQL Server (BI) Business Intelligence
• SetFocus is seeking professionals with Analyst
  and/or Data Warehousing backgrounds for Business
  Intelligence consulting positions across the
  country. Apply Today www.setfocus.com/Apply/defau
  ltbi.aspx
• Successful candidates have had backgrounds as
• Business Intelligence Analyst, Database
  Developer, SQL Programmer, Financial Analyst,
  Business Analyst, System Analyst, Software
  Developer, Dir. of IT, VP of IT and / or
  experience with Cognos, Siebel, SAP, Business
  Objects, SAS, PeopleSoft, Oracle, Microstrategy,
  Information Builders, ProClarity, CA, or Actuate.
  

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The Evolution of Business Intelligence

• 1st Generation Traditional analytics (query and
  reporting)
• 2nd Generation Traditional generation (OLAP,
  data warehousing)
• 2.5nd Generation New traditional generation
• 3rd Generation - Advanced analytics
• Rules, predictive analytics and realtime data
  mining
• Stream analytics

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Business Intelligence Classifications
Stream Analytics Real-time, continuous,
sequential analysis (ranging from basic to
advanced analytics) In lieu of stream
analytics, embedded analytics, although
architecturally different, could potentially play
the same role
3rd-Generation BI
Advanced Analytics/Optimization Rules Predictive
Analytics Real-time and traditional Data Mining
New Traditional Analytics 2.5-Gen Analytics
(In-Memory OLAP, Search-Based)
Traditional Analytics 1st Generation Analytics
(Query Reporting) 2nd Generation Analytics
(OLAP, Data Warehousing)
Source Bill OConnell IBM, Aug 2007
Legacy BI
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Business Intelligence Use Cases
Example Target Solutions Fraud Detection / Risk
CRM Analytic Supply Chain Optimization RFID
/ Spatial Data Other High-Volume
Focus on what is happening RIGHT NOW
Stream Analytics Real-time, continuous,
sequential analysis (ranging from basic to
advanced analytics) In lieu of stream
analytics, embedded analytics, although
architecturally different, could potentially play
the same role
Focus on what will happen Analytic applications
that apply statistical relationships in the form
of RULES
Advanced Analytics/Optimization Rules Predictive
Analytics Real-time and traditional Data Mining
New Traditional Analytics 2.5-Gen Analytics
(In-Memory OLAP, Search-Based)
Data mining to determine why something happened
by unearthing relationships that the end-user may
not have known existed.
Focus on what did happen Turning data into
information is limited by the relationships which
the end-user already knows to look for.
Traditional Analytics 1st Generation Analytics
(Query Reporting) 2nd Generation Analytics
(OLAP, Data Warehousing)
Source Bill OConnell IBM, Aug 2007
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3rd Generation Business Intelligence

• Raises Traditional Warehousing to new levels ?
  Dynamic Warehousing
• Injects analytical insight into the day to day
  process of an organization when activity is
  occurring in real time
• Broad, real time, leverage of insight to achieve
  business optimization
• Moves beyond what happened to why and what
  should happen next.
• Requires the marriage of analytical insight with
  real time business processing.
• 3rd Gen BI by nature requires a Data Warehouse
  Platform and MDM system to consume analytical
  insight, not just source data for BI.

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3rd Generation BI Attributes from data
management perspective

• Near-real time (streaming, change data control,
  memory resident, etc.)
• Off-line capable
• In-context
• Actionable through predictive/prescriptive stats,
  optimization and business rules
• Search User Interface (UI) as the front end of BI
• Structured unstructured
• Visual
• For the masses
• Horizontal platform with verticalized solutions
• Can be delivered via a hosted model