1. Programming Languages
1.1. SQL
1.2. VBA
1.3. R
1.4. LINGO
1.5. Python
1.6. DAX
1.7. SAS
2. Data Storage & Structure
2.1. Tools
2.1.1. SQL Server
2.1.2. Access
2.1.3. Visual Studio
2.1.4. Visio
2.1.5. GitHub
2.2. Courses
2.2.1. INFO 3140 Foundations of Info Mgmt
2.2.2. INFO 3240 Enterprise Info Mgmt
2.2.3. INFO 3300 Data Warehousing and Data Mining
2.3. Techniques
2.3.1. Scripting/Programming
2.3.1.1. SQL
2.3.1.2. SSMS
2.3.2. Visualization
2.3.2.1. PowerBI
2.3.2.2. Visual Studio
2.3.2.3. PowerPivot
2.3.3. Reporting
2.3.3.1. Dashboards
2.3.3.2. Business Write-Up
2.3.3.3. SSRS
2.3.4. Normalization
2.3.5. ETL (Extract, Transform, Load)
2.3.6. Quering
2.3.7. Scalability
2.3.8. DB Planning
2.3.8.1. ERD
2.3.8.2. Business Requirements
2.3.8.3. Relationships within data/entities
2.3.9. Data mining
3. Business Problem-Solving
3.1. Tools
3.1.1. VBA
3.1.2. Microsoft Project
3.1.3. R
3.1.4. Python
3.1.5. JMP
3.1.6. Excel
3.1.7. LINGO
3.1.8. PowerBI
3.1.9. Solver Add-In
3.2. Techniques
3.2.1. Automation
3.2.2. Linear & Nonlinear Programming
3.2.3. Optimization
3.2.4. Descriptive Statistics
3.2.5. Project Management
3.2.5.1. Constraints - scope, time, resources
3.2.5.2. Waterfall vs interitive project plan
3.2.6. Query
3.2.7. Presentation
3.2.7.1. Reporting
3.2.7.2. Power Point
3.2.7.3. Dashboards
3.3. Courses
3.3.1. INFO 3340 Project Mgmt & Simulation
3.3.2. INFO 3440 Optimization Modeling
3.3.3. INFO 3500 Capstone
3.3.4. INFO 3110 Non-parametric Statistics
3.3.5. INFO 3100 Automating Business Processes
4. Data Analysis
4.1. Tools
4.1.1. JMP
4.1.2. Tableau
4.1.3. R
4.1.4. SPSS Modeler
4.1.5. PowerPivot
4.1.6. Excel
4.1.7. NodeXL
4.1.8. PowerBI
4.1.9. SSAS
4.2. Courses
4.2.1. INFO 3400 Complex Data Analytics
4.2.2. INFO 3200 Business Forecasting & Visualization
4.2.3. INFO 3700 Sports Analytics
4.3. Techniques
4.3.1. Regression
4.3.1.1. Linear
4.3.1.2. Stepwise
4.3.1.3. Logistic
4.3.2. Prediction/Estimation
4.3.2.1. Decision Trees
4.3.3. Text Mining
4.3.4. Network Analysis
4.3.4.1. Neural Network
4.3.4.2. Social Network Analysis
4.3.5. Descriptive Statistics
4.3.6. Visualization
4.3.6.1. dashboards
4.3.6.2. graphing methods
4.3.7. Cluster/Association
4.3.8. Non-parametric statistics