Business & Data Analysis - Interactive Course
A hands-on, plain-English course on analysing data for business decisions: framing measurable questions, preparing and summarizing data, visualizing it accessibly, exploring relationships, defining metrics and KPIs, and communicating insight ethically. Learn by doing with worked, recomputable examples and knowledge checks. Links out to dedicated SQL, Python, and Statistics courses for hands-on practice - without duplicating them.
Start free → The Ethical Sales ProcessFoundations of Business Data Analysis
How analysis serves a decision: the value chain, data types, and framing a measurable question.
- The Analytics Value Chain: From Question to DecisionStart here Trace the path from a business question through data and analysis to an insight and a decision. Free · Open →
- Data Types & Levels of Measurement Tell nominal, ordinal, interval, and ratio data apart and know which summaries are valid. Free · Open →
- Framing a Measurable Business Question Turn a vague business ask into a measurable question with a metric, a population, and a timeframe. Free · Open →
Data Collection, Quality & Preparation
Get data from the right sources, clean it honestly, and shape it for analysis.
- 🔒 Data Sources & Collection Choose fit-for-purpose data sources and understand how collection shapes what you can conclude. Members →
- 🔒 Data Cleaning & Validation Find and handle missing values, duplicates, and errors without distorting the data. Members →
- 🔒 Preparing & Transforming Data Reshape, join, and derive fields so a dataset is ready to analyze. Members →
Describing & Summarizing Data
Summarize data honestly with the right centre, spread, and rate - and know when to go deeper into statistics.
- 🔒 Summary Statistics: Centre & Spread Use mean, median, and spread to summarize data, and link out to the Statistics course for the theory. Members →
- 🔒 Distributions, Shape & Outliers Read the shape of a distribution and treat outliers without hiding them. Members →
- 🔒 Rates, Ratios & Percentage Change Compute and compare rates, ratios, and growth without misleading yourself. Members →
Data Visualization & Accessible Charts
Pick the right chart, make it accessible, and build dashboards that inform rather than decorate.
- 🔒 Choosing the Right Chart Match the chart type to the question and the data, and avoid chart-junk. Members →
- 🔒 Accessible, Honest Charts Design charts that are readable, colour-safe, and not misleading. Members →
- 🔒 Dashboards That Inform Assemble metrics into a dashboard that answers a decision-maker's real questions. Members →
Exploratory Analysis & Relationships
Explore a dataset, test relationships carefully, and segment to find the story.
- 🔒 Exploratory Data Analysis (EDA) Systematically explore a new dataset before drawing any conclusions. Members →
- 🔒 Correlation, Causation & Confounders Read a relationship without over-claiming cause, and spot confounders. Members →
- 🔒 Segmentation & Cohort Analysis Split data into meaningful segments and cohorts to see what an average hides. Members →
Metrics, KPIs & Experimentation
Define metrics that drive good decisions, connect them into driver trees, and test changes fairly.
- 🔒 Defining Good Metrics & KPIs Choose metrics that are meaningful, hard to game, and tied to a goal. Members →
- 🔒 Metric Trees & Driver Analysis Break a top-line metric into the drivers you can actually move. Members →
- 🔒 A/B Testing Basics Understand the logic of a fair comparison and the limits of a single test. Members →
Querying & Wrangling Data
Get data with SQL, wrangle it with Python, and know when a spreadsheet is enough - links out to the deeper SQL and Python courses.
- 🔒 SQL for Analysts (Overview) What SQL is for in analysis, with a link out to the hands-on SQL course - no duplication. Members →
- 🔒 Python for Data Analysis (Overview) Where Python fits in an analyst's workflow, with a link out to the hands-on Python course. Members →
- 🔒 Spreadsheets & When to Move to Code Use spreadsheets well and recognise when code is the better tool. Members →
From Analysis to Decision
Turn analysis into a decision: communicate the insight, avoid misleading it, and respect ethics and privacy.
- 🔒 Communicating Insight & Storytelling with Data Tell a clear, honest data story that leads to a decision. Members →
- 🔒 Avoiding Misleading Analysis Recognise and avoid the common ways analysis misleads. Members →
- 🔒 Ethics & Privacy in Analytics Handle data responsibly: consent, privacy, bias, and honest reporting. Members →
The full course is laid out above so you can see exactly where you're headed. Start with the free lessons — the analytics value chain lesson takes about fifteen minutes and you will map every stage from first contact to keeping the customer.