Module 01 — Variables, Expressions & Data Types#

Graduate MSBA Module Overview

In business analytics, variables, expressions, and data types form the foundation of how we work with information. A variable is a named container that holds a piece of data — think of it like a labeled box where you store a customer’s purchase amount or a product’s sales region. An expression is a combination of variables, operators, and values that produces a result — for example, calculating total revenue by multiplying unit price by quantity sold. Data types define what kind of information a variable can hold, whether that is numbers, text, dates, or true/false values.

Together, these three concepts let you organize, manipulate, and derive insights from business data systematically.

Course Connections#

Understanding variables, expressions, and data types is essential because everything you will do in Python and business analytics depends on them. When you load a dataset, each column becomes a variable holding specific data types. When you filter data, write formulas, or build algorithms, you are constructing expressions that operate on those variables. Later in the course, you will work with libraries like Pandas and NumPy that manipulate thousands of variables and expressions simultaneously — but they all rest on these core concepts.

Quick Code Example#

customer_name = 'Alice Johnson'
customer_id = 1001
purchase_1 = 250.50
purchase_2 = 180.75
purchase_3 = 420.25

total_spent = purchase_1 + purchase_2 + purchase_3
average_purchase = total_spent / 3
is_premium_customer = total_spent > 500

print('Customer:', customer_name)
print('Customer ID:', customer_id)
print('Total Spent:', total_spent)
print('Average Purchase:', average_purchase)
print('Premium Customer:', is_premium_customer)

Expected Output:

Customer: Alice Johnson
Customer ID: 1001
Total Spent: 851.5
Average Purchase: 283.8333333333333
Premium Customer: True

Learning Progression#

Module Pages#

• Concept → — Deep narrative explanation of variables, data types, and expressions
• Advanced → — Extended code example with business context
• Notebook → — Jupyter notebook lab description