1.
A retail company collects daily sales data from its stores. Recently, the
management noticed that profits are decreasing even though sales volume
appears to be increasing.
As a Data Analyst, you are asked to investigate the issue using the company’s
dataset which contains:
• Product ID
• Product Category
• Units Sold
• Selling Price
• Cost Price
• Store Location
• Date of Sale
Tasks:
1. Identify the key metrics you would calculate to analyze profitability.
2. Describe the steps you would take to clean and prepare the dataset
before analysis.
3. Suggest two possible reasons why profits might be decreasing despite
higher sales.
4. Recommend two data visualizations that would help management
understand the problem.
2. You are a data analyst at a real estate company. The company wants to
predict house prices based on historical data. You have been given a dataset
with information about houses, but the data contains missing values and
categorical features. Your task is to preprocess the data so that it can be used
for machine learning models.
Dataset:
House ID
Size (sqft)
Bedrooms
Age (years)
Location
Price ($)
1
2000
3
10
A
500,000
