Overview
A one-day workshop providing the definitions, concepts, and practices related to business intelligence and analytics. The session is designed to expose the participant to the basic tools and techniques for determining appropriate data, data collection, data normalization, data storage, and data access for business intelligence analysis.
Working with the client, examples can be provided to participants directly applicable to their organizational area.
Length
8 hours
Outline
Level I: Minimal exposure (2 hours 15 Minutes)
Definitions
- Business Intelligence
- Business intelligence versus competitive intelligence
- Business Analytics
- Statistical analysis
- Quantitative analysis
- Qualitative analysis
- Online Analytical Processing (OLAP)
- Multi-dimensional analysis
- Forecasting
- Optimization
- Predictive modeling
- Business rules engine
Intelligence cycle
- Planning & direction
- Collection
- Processing
- Analysis & production
- Dissemination
Areas that should be addressed
- Markets and customers
- Technology developments and sources
- Corporate security threats
- Competitor capabilities, plans, and intentions
- Political, economic, and social forces
- Industry structure and trends
Information categories
- Marketing
- Production
- Product
- Organizational
- Financial
Steps
- Sources
- Collection
- Evaluation
- Control
- Display
- Action
Quality
- Source quality
- Content quality
Drawing conclusions/predictions based on data
- Model types
- Modeling techniques
- Patterns in data
Level II: Foundational (2 hours 15 Minutes)
Types of software for data analysis
- Excel
- MathLab
- SAS
- SPSS
Building models
- Data access
- Data normalization
- Data loading
Analyzing data
- Descriptive statistics
- Analytical statistics
- Thresholds/Alerts
- Probabilities
- Correlations
- Time series analysis
Design of experiments
- Dependent variables
- Independent variables
- Multi-dimensional analysis
Level III: Capable (2 hours 15 Minutes)
Application
- Elements
- Data feeds
- Data warehouses/Data Marts/Databases
- Data currency
- Data dictionaries
Data presentation
- OLAP
- Spreadsheet
- Graphical
- Tabular
- Excel Pivot tables
Understanding variation
- Normalization
- Information “noise”
Summary & Wrap-up