Modules for Business Analytics

The modules correspond to the weeks in our course Moodle site (with a few twists). Roughly the course is broken up into four sections.

Section 1: Modeling and Excel foundation

The first three modules set the tone and build a foundation for the rest of the course.

Section 2: Data analysis

Excel has numerous functions and tools for ingesting, cleaning, analyzing, visualizing and managing data. We will tackle these over the course of three weeks with two topics per week.

Data organization and power Excel techniques

You can make your Excel life much easier by getting your data well organized before trying to analyze it. In the Power Excel module we’ll cover a hodge podge of useful techniques.

Data cleaning and visualization

Get your data clean and learn to create effective data visualizations.

Exploratory data analysis and dashboarding

We’ll mostly focus on pivot tables and using Excel’s advanced features to create dashboards.

Section 3: Excel VBA

We will learn to program in Excel VBA to automate repetitive tasks and create Excel based analytical applications. In a few weeks we can only scratch the surface but this should give you a good running start to adding VBA to your Excel toolkit. You’ll see that the third VBA module comes after our first advanced modeling topic. This is so we can combine optimization models with VBA to make interesting applications.

Section 4: Advanced modeling

We’ll close this course with an introduction to optimization in Excel using Solver and Monte-Carlo simulation in Excel. Again, we can just scratch the surface of these topics in a few weeks.

After this class, if you want to learn about data science and predictive modeling, you could take MIS 4560/5560 - Intro to Data Science and/or MIS 4470/5470 - Practical Computing for Data Analytics. They are complementary and many students take both. Below I introduce some of the basics within the context of spreadsheets. So, you can always use this to learn about these topics as well.