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HandsOn-Business Analytics™
Published: 5 September 2007
This course starts by defining the promise of business intelligence and the gap that exists between what is promised and what is often implemented.

This course is available at the TDWI World Conference in Orlando. For more information, and to register, visit www.tdwi.org/orlando2007.

M6
Administration & Technology / Data Integration

Prerequisite: Understanding of relational database and data warehouse terms and concepts


Michael L. Gonzales, CBIP

Principal, Claraview, Inc.

You Will Learn

  • The best practices for blending data mining, dashboards, scorecards, advanced visualization, and spatial data technology into your BI environments
  • The core components to effective spatial analysis, data mining, dashboards/scorecards, and visualization applications
  • Through extensive lab exercises, you will gain hands-on experience with leading BI tools, including:
    • Microsoft Data Mining
    • Microsoft Scorecard
    • ESRI Business Analyst
    • PolyVista
    • Tableau
  • How and when to effectively apply advanced BI technology in order to enhance your information content and analytical landscape

Geared To

  • Anyone involved in the sponsorship, management, design, and construction of BI solutions for an enterprise

Business intelligence (BI) is well beyond the domain of traditional topics such as ETL and OLAP. Today, BI drives the information organization with technologies and techniques that allow the enterprise to glean actionable insight from volumes of disparate data, with near real-time refresh cycles.

This course starts by defining the promise of business intelligence and the gap that exists between what is promised and what is often implemented. The lecture portion of the course then sets out to identify the technologies and techniques necessary to fill the gap, including data mining, dashboards/scorecards, advanced visualization, and spatial analysis.

Hands-on exercises complement all lecture content. Throughout the course, participants experience leading products representing tangible evidence and applicability, to enhance the informational content of any BI effort. Specific technologies include:

  • Data Mining: Microsoft Data Mining lab
  • Dashboards: Hyperion Intelligent Dashboard
  • Scorecards: Microsoft
  • Visualization: Tableau and PolyVista labs
  • Spatial Analysis: ESRI Business Analyst lab

 

HandsOn-Business Analytics is designed to provide participants with a non-biased view of leading BI tools.

Enrollment is limited to 30 attendees.

 

Course Outline

1. The Promise of BI
  • Data challenges
  • The BI organization
  • Actionable insight
2. The BI Gap
  • Traditional disparate data stores
  • A pie chart is not enough
3. Filling the BI Gap
  • Foundations for business intelligence
  • Leading RDBMS vendors
  • The BI fabric
  • Information versus simple data
  • Filling the BI gap

4. Dashboards and Scorecards

  • Overview and terms
  • Dashboards and scorecards
  • Comparing technologies
  • Not mutually exclusive
  • Effective dashboards and scorecards
  • Representative market competitors

5. Scorecard Lab: The objective of the lab exercises is to cover the process for formally defining and implementing scorecards. (total lab time: 45 minutes)

  • Lab Exercises Using Microsoft SQL 2005 Scorecard – Experience the entire process of defining scorecard metrics and implementing them through Microsoft SQL 2005 Scorecard
6. Visualization and Spatial Analysis
  • Overview and terms
  • We think visually
  • Visualize quantitative information
  • Broad landscape of application
  • Trends
  • Great body of evidence
  • Advanced histograms
  • Three-dimensional intersections
7. Visualization Lab: The objective of the lab exercises is to demonstrate advanced visualization technology and how it impacts the insight gleaned from complex data (total Lab time: 1.0 hour)
  • Lab Exercise #1 Using Tableau – Import traditional financial data into the Tableau software and perform several visual queries against the data set
  • Lab Exercise #2 Using PolyVista – Examine complex, multidimensional OLAP data in a single, advanced visualization
8. Location BI
  • Overview and terms
  • Complete and comprehensive BI
  • Impaired intelligence
  • Location intelligence
  • Information enhancement
  • Blending space with BI
9. Location BI Lab: The objective of the lab exercises is to demonstrate the enhancement of traditional warehouse data and reports with spatial data and analysis (total lab time: 1.0 hour)
  • Lab Exercise #1 – Import, geocode, and map traditional structured data
  • Lab Exercise #2 – Experience the use of Business Analyst for advanced business intelligence applications
10. Data Mining
  • Overview and terms
  • What is data mining
  • Data mining scenarios
  • Case study: market basket analysis and text mining
  • Complete the analytic landscape
  • The BI organization and data mining
11. Data Mining Labs: The objective of the lab exercises is to use data mining techniques to explore data sets and establish mining models in traditional ETL flow for data quality (total lab time: 45 minutes)
  • Lab Exercises Using Microsoft SQL 2005 Data Mining Functions – Gain insight for running decision trees and cluster algorithms to enhance your BI solutions