CDPP Data Analysis & Modeling

Question 1

What is the primary goal of data analysis in demand planning?

Accepted Answer

To predict future demand based on historical trends

Answer

To analyze market conditions and competitors' strategies

Answer

To track customer behavior in real-time

Answer

To assess the financial performance of the company

Question 2

Which of the following is a common technique used for forecasting demand in data modeling?

Accepted Answer

Time-series analysis

Answer

Regression analysis

Answer

Factor analysis

Answer

Cluster analysis

Question 3

What is the purpose of regression analysis in data modeling?

Accepted Answer

To predict future demand based on relationships between variables

Answer

To identify trends and patterns in historical data

Answer

To visualize data distribution over time

Answer

To analyze customer behavior and preferences

Question 4

What is the main advantage of using machine learning models in demand planning?

Accepted Answer

They automatically adjust demand predictions based on new data

Answer

They provide real-time inventory tracking

Answer

They replace the need for historical data

Answer

They only forecast future demand based on linear trends

Question 5

How does clustering analysis help in demand planning?

Accepted Answer

By grouping similar data points for pattern identification

Answer

By identifying the relationship between supply and demand

Answer

By predicting future demand based on historical trends

Answer

By visualizing the seasonal demand cycles

Question 6

Why is it important to validate data before using it in demand forecasting models?

Accepted Answer

To avoid errors and improve the accuracy of the forecasts

Answer

To ensure the data is processed efficiently

Answer

To simplify the data modeling process

Answer

To reduce the computational time of the models