Day 01 — Part 1: Introduction to Data Analytics¶
Session Overview¶
Welcome to Day 1. Before touching a single tool, you need a mental model of what analytics is, how it fits inside a business, and what analysts actually do on a Tuesday afternoon. This session builds that foundation.
Everything in this course connects back to a single idea: analytics exists to reduce uncertainty in business decisions. A report that nobody acts on is not analytics — it is documentation.
Learning Objectives¶
By the end of this session you will be able to:
Beginners - Explain the analytics lifecycle from business question to decision - Distinguish between descriptive, diagnostic, predictive, and prescriptive analytics - Describe the role of a data analyst within a cross-functional team - Identify at least three industries where analytics creates measurable business value
Mid-level analysts - Map any stakeholder request to the correct analytics type - Recognize which phase of the analytics lifecycle is most likely to fail — and why - Articulate the difference between an interesting insight and an actionable one
Senior analysts - Frame analytics work in terms of decision value, not just output volume - Identify organizational anti-patterns that kill analytics impact - Design the scope and deliverable format for an analytics engagement before touching data
Session Topics¶
| # | Topic | Estimated Time | Difficulty |
|---|---|---|---|
| 1 | The Analytics Lifecycle | 20 min | Beginner |
| 2 | Four Types of Analytics | 20 min | Beginner–Mid |
| 3 | Business Use Cases by Industry | 25 min | Beginner–Mid |
| 4 | The Day-in-the-Life Analytics Workflow | 25 min | Mid–Senior |
| 5 | Real-World Case Studies | 20 min | Mid–Senior |
| 6 | Practice Exercises | 30 min | All levels |
| 7 | Interview Questions | Self-paced | All levels |
Total estimated time: 2.5–3 hours (including exercises)
Prerequisites¶
- No prior analytics experience required for the core content
- Mid and senior callouts assume familiarity with SQL and at least one BI tool
- You do not need any software installed for Part 1 — this is conceptual groundwork
Tools for This Session¶
- A browser (to look up business context and domain examples)
- A notepad or notes app — write down every business question you see; pattern recognition is a skill you build deliberately
- Optional: draw the analytics lifecycle diagram by hand; physical writing aids retention
How to Use These Notes¶
Each file in this session follows the same structure:
- Why this matters — the business case for the concept
- Core explanation — written for a beginner; read this even if you're senior
- Depth callouts — mid and senior layers added via callout blocks
- Business examples — real scenarios, not toy problems
- Common mistakes — what goes wrong in practice
- Key takeaways — what you should be able to say without looking at notes
Read every section in order on your first pass. On review, jump to the depth callouts.
The Central Question¶
Before every analytics task, ask yourself:
"What decision does this analysis enable — and for whom?"
If you cannot answer that question, you are not ready to write a query. Go back and talk to the stakeholder.
Next: 01-analytics-lifecycle