Business Analytics

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Business Analytics por Mind Map: Business Analytics

1. Enterprise Information Management

1.1. SQL Server Database Design and Programming

1.2. Visual Studio Windows Forms

1.3. Visual Studio Windows Integrated Application

2. Foundations of Information Management

2.1. Database Initial Study, Design and Modeling

2.2. Database Implementation and Data Loading

2.3. Database Querying using Structured Query Language (SQL)

2.3.1. By learning the basics of SQL coding and applying it to a higher level when building database in VS instead of Access

2.4. Microsoft Access

2.5. Visio Graphing: ERD

3. Data Warehousing & Business Intelligence

3.1. Plan, Design, and Model the DW/DM (using VS, Visio, Word and Excel)

3.2. Build the DW/DM (using VS and SSMS)

3.3. Extract, Transform, and Load the DW/DM (using VS and SSIS)

3.4. Develop Tabular and Multidimensional Analysis from the DW/DM (using VS, Excel and SSAS)

3.5. Create Reports and Dashboards from the DW/DM (using VS and Power BI)

4. Data Mining and Visualization

4.1. Exploring/Visualizing Your Data

4.2. Logistic Regression Models

4.3. Time Series Forecasting

4.4. K-Nearest Neighbor/General Linear Models

4.5. Tableau Story and R Dashboard

4.6. Data Mining with R

4.7. JMP

5. Complex Data Analytics

5.1. Concepts of Big Data Analytics

5.2. Text Analytics

5.2.1. Reviews: movies, hotels, restaurants

5.3. Network Analytics

5.3.1. Friendship, Romantic Relationships, Sports Fans

5.4. Social Media Analytics

5.4.1. FB, Twitter

5.5. Disparate Data Sources

5.6. SPSS Modeler Application

6. Capstone/Senior Project

6.1. A combination of all major courses that include all the techniques, skills and sofetwares we learned in college to work on a comprehensive project

7. Automating Business Processes

7.1. Spreadsheet modeling design

7.2. Basic Programming (Python)

7.2.1. Learning the simple coding in Python (simple functions & calculations, pandas dataframe), and learn how to read and write files in python. Also learned the basic of performing analysis such as Regression, ANOVA, and creating graphs

7.3. Excel Bult-in function application

7.4. Excel: Creating functions

7.5. VBA (Visual Basic)

8. Optimization Modeling

8.1. Identify problems appropriate for optimization

8.2. Network Models

8.3. Allocation, Covering, Blending Problems

8.4. Paramter Analysis

8.5. Integer Programming Models

8.6. Optimiaztion Modeling in Python

8.7. Constrainnts for Linear & Nonlinear Models

8.8. Evolutionary Algorithms

9. Project Management and Simulation

9.1. Big Picture: Project Management Overview

9.2. Project Integration Management

9.2.1. Methodology

9.2.2. Predictive & Agile

9.2.3. Strategic Planning

9.2.4. Project Charters and Plans

9.3. Project Scope Management

9.3.1. Work Break Down Structure

9.3.2. Validating & Controlling Scope

9.4. Project Time Management

9.4.1. Planning

9.4.2. Sequencing Activities

9.4.3. Estimating/Simulation

9.4.4. Developing/Controlling Schedules

9.5. Project Cost and Quality Management

9.5.1. Project Cost/Estimating

9.5.2. Budget

9.6. Project Human Resource Management

9.6.1. Managing and Leading People

9.6.2. Developing the HR Plan

9.7. Project Communications Management

9.7.1. Good Communication

9.7.2. Managing & Controlling Communication

9.8. Project Risk Management

9.8.1. Quantitative Risk Analysis

9.8.2. Controlling Risk

9.8.3. Planning for RISK

9.8.4. Qualitative Risk Analysis

9.9. Project Procurement Management

9.9.1. Conducting Procurements

9.9.2. Closing Procurements

9.10. Project Stakeholder Management

9.10.1. Identifying Stakeholders

9.10.2. Managing Stakeholders

9.10.3. Controlling Stakeholders

9.10.4. Using Software to Assist