Hands-On BI - Presented by Michael Gonzales

Prerequisite: An understanding of relational database and data warehousing terms and concepts

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 insight from volumes of data. This course examines three foremost technologies that impact BI: spatial data, data mining, metadata, portals, and real-time analytics. Participants will be given the opportunity to gain hands-on experience with the tangible value each technology brings to any warehouse effort.

Through lecture and hands-on exercises, participants experience leading product applicability to enhance the informational content of any data warehouse effort, such as IBM’s OLAP Miner, Teradata Warehouse Miner, ESRI’s Spatial Business Analyst, Ascential’s MetaStage, Arcplan, and Sagent’s Enterprise Information Integrator.

Hands-On Business Intelligence is designed to provide participants with a non-biased view of leading BI tools.

You will learn:

• The best practices for blending data mining, portal, and spatial data technology into your BI solution
• The core components to effective spatial analysis, data mining, and portal applications
• Through extensive lab exercises, you will gain hands-on experience with leading BI tools, including:
• IBM OLAP Miner, Teradata Warehouse Miner
• ESRI Spatial Business Analyst
• Arcplan Portal
• Ascential MetaStage
• Sagent EII
• How and when to effectively apply advanced BI technology in order to enhance your information content and analytical landscape

Intended Audience

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

Course Outline

1. Overview
2. Spatial Data
• Spatial Data Concepts
• Terms
• Definitions
• GIS Functions
• Spatial Data & The BI Organization
• ESRI Spatial Analysis LAB
3. Data Mining
• Introduction
• Terms
• Definitions
• Data Mining Opportunities
• The Mining Process
• Individual Techniques
• Clustering
• Association
• Classification
• Prediction
• Data Mining Application
• Data Mining Lab: MS Analytics and IBM OLAP Miner
4. Meta Data
• Meta Data Terms
• Benefits of Meta Data
• Meta Data Impact
• The Meta Data Challenge
• Common Models
• Point-to-point Bridges
• Leading Approach
• An Integrated View
• The Current State of Meta Data
• Ascential MetaStage Lab
5. Portal
• Decision Portal Overview
• Terms and Definition
• Portal Characteristics
• Cross-discipline
• Portal Pitfalls
• How Decisions Effect Design
• Decision Based Designed
• Decision Factor Analysis
• Portal Architecture
• Process Architecture
• Process Flow
• Component Architecture
• ArcPlan Portal Lab
6. BAM
• Terminology Trends
• Zero-latency
• Real-time Data Warehouse Alternatives
• Business Activity Monitoring
• Network & Systems Management
• Sagent Enterprise Information Integrator Lab