Question

Consider the following steps of a data science workflow to be arranged in correct order :
A. Data preprocessing

B. Model building

C. Data collection

D. Data visualization and interpretation

E. Model evaluation

Choose the correct answer from the options given below :

• A. C, A, B, E, D
• B. A, C, B, D, E
• C. C, B, A, D, E
• D. B, C, A, E, D

Hint:

Remember: You can't clean what you haven't collected, and you can't evaluate a model you haven't built!

Answer 1

The Correct Option is A

Concept:
• The Data Science Lifecycle (similar to CRISP-DM) is a standard process followed in data projects.
• It moves from data acquisition to preparation, modeling, and finally to communication of results.

Step 1: First Step - Data Collection (C)
You cannot perform any analysis without raw data. The process starts by gathering data from various sources (Databases, APIs, etc.).

Step 2: Second Step - Data Preprocessing (A)
Raw data is usually "dirty." This stage involves cleaning, handling missing values, and transforming data into a format suitable for algorithms.

Step 3: Third Step - Model Building (B)
Once the data is ready, machine learning models are trained using chosen algorithms and features.

Step 4: Fourth Step - Model Evaluation (E)
The trained model is tested against unseen data using metrics like accuracy, precision, or RMSE to ensure it performs well.

Step 5: Fifth Step - Visualization and Interpretation (D)
The final findings and model outputs are visualized for stakeholders to interpret and make data-driven decisions.