Data Analysis Basics
75%
Lesson 6 of 8

Data Analysis Basics

AI can accelerate analysis, but you still need to define the metric, inspect the data and verify calculations.

Active reading
Why this matters

AI can accelerate analysis, but you still need to define the metric, inspect the data and verify calculations.

Question

What are you trying to learn?

Data

What rows, columns and units do you have?

Check

Can you reproduce the calculation?

Understand the working model

Ask the model to describe its calculation logic and assumptions before trusting a result. Ambiguous column names, missing values and mixed units can quietly change the answer.

Use AI for cleaning suggestions, formula drafting and interpretation, but keep deterministic calculations reproducible in code or spreadsheet formulas when accuracy matters.

Example
Before analysis, report row count, missing values, duplicate rows and units. Then calculate conversion rate by channel and show the exact formula used.
Practice

Apply the pattern above to one real task you already do. Keep the first version small enough that you can inspect every input and output.

Common mistake

Do not accept a surprising number without checking the denominator, units and filters.

Key takeaway

Use AI to accelerate analysis, but keep definitions, calculations and verification explicit.

Next lesson

Reusable Templates

Continue to the next lesson.

Continue →