Concept:
A data analytics or machine learning workflow follows a logical sequence from data collection to evaluation.
Step 1: Dataset.
First, we need a dataset.
\[
\text{First step}=E
\]
Step 2: Train and Test.
The dataset is divided into training and testing parts.
\[
\text{Second step}=C
\]
Step 3: Model selection.
After splitting data, an appropriate model is selected.
\[
\text{Third step}=D
\]
Step 4: Prediction.
The trained model is used to make predictions.
\[
\text{Fourth step}=B
\]
Step 5: Accuracy.
Finally, accuracy is calculated to evaluate the model.
\[
\text{Fifth step}=A
\]
\[
\therefore \text{Correct Answer is (A)}
\]