Skill Paths
Step-by-step paths for the practical skills you use at work, from spreadsheets and SQL to visualisation, pipelines and agile delivery.
Why Skills Are Taught by Doing
Role programmes teach the decisions your job involves. Skill paths teach the practical skills behind them, whether that is a tool such as Power BI, a language such as SQL, or a way of working such as agile delivery. All of them are built around practice rather than explanation.
Reading is only the first step
A tutorial can explain a query perfectly well, but following along feels easier than it is. Skill comes from attempting something slightly beyond your current level, getting feedback, and trying again.
Feedback has to be immediate1
The research on expertise is consistent on one point: practice only improves performance when it is focused on a specific task and followed by prompt, informative feedback. Every exercise here runs, and tells you what went wrong.
The closer to real work, the better it sticks2
Skills transfer best when the practice setting resembles where the skill will be used. So exercises use realistic tables, business questions and the errors the real tool would give you.
Difficulty in the right place3
Being told the answer is comfortable and teaches little. Working it out, with a hint if you are stuck, is harder and lasts longer, which is why the worked solution appears only after three attempts.
Sources: 1Ericsson, K. A., Krampe, R. T. and Tesch-Römer, C. (1993), ‘The Role of Deliberate Practice in the Acquisition of Expert Performance’, Psychological Review 100(3), 363–406, on practice that targets a specific task with immediate feedback. Later work, including Macnamara and Maitra (2019), Royal Society Open Science 6(8), finds practice explains less of the variation in performance than originally claimed, so we treat it as necessary rather than sufficient. 2Baldwin, T. T. and Ford, J. K. (1988), Personnel Psychology 41(1), 63–105, on job relevance and practice opportunities in training design. 3Dunlosky, J. et al. (2013), Psychological Science in the Public Interest 14(1), 4–58, on practice testing and spacing.
What Every Exercise Gives You
Whichever path you choose, every exercise is built the same way, so you always know what you are getting.
A real scenario
One sentence of context: the table, the business question, and who is asking for it.
A dataset you can read
Small enough to check by eye, realistic enough to behave like real data.
Run it yourself
Write, run, and see output or an error. Unlimited attempts, and nothing is timed.
Checked, not marked
Your result is compared with the expected answer, not with exact wording.
Hints, then the solution
A hint after two attempts, the worked solution after three, with why it is written that way.
Why it mattered
What the result tells the business, so it is never just syntax practice.
Learn the Skills Your Role Needs
Hands-on paths that take you from the fundamentals to advanced use, at your own pace. Some teach a tool, some teach a technique, and some teach a way of working.
What the levels mean
Paths are listed with the gentlest starting point first. If you are at Level 1, start with Spreadsheets & Everyday Data, or with the short Data Basics course.Start with Data Basics →
Data Basics
Spreadsheets & Everyday Data
Data Visualisation & Insight
Product & Agile Planning
Python & Automation
SQL & Databases
Building Data Pipelines
Building with AI
Cloud Data Platforms
Preparing Data for AI
New to Working with Data?
Every skill path assumes you are comfortable with the basics. If any of this is new, start with the short course first.
Try the Query Workbench
Write real SQL against a real dataset in the page, with instant feedback, hints and worked solutions. This is the practice block behind every SQL lesson.
Open the workbench →Start Here: Data Basics
Eight lessons covering tables, measures and dimensions, averages, percentages, charts, and how fresh a figure is.
Open Data Basics →Visualisation Guide
Forty-six visual types, with what each one shows and when to choose something else.
Open the Visualisation Guide →How Each Skill Is Practised
Most paths let you write something and run it in the page. Where a tool cannot run in a browser, you work through a version of it instead, and we say so. Your role decides which of these you need, and most people need two or three.
An analyst spends most of their time in SQL, spreadsheets and visuals. An engineer works in pipelines and cloud platforms. A product owner uses none of them, and works in agile planning instead.Find your role first →
Six Places to Practise Right Now
Each one runs in the page, with your work saved on this device. Three are real, three are simulations, and each says which it is.
SQL Query Workbench
Write real SQL against a live dataset, with results, errors and a checked answer.
Open the workbench →Formula Grid
Real spreadsheet formulas on a live sheet: SUM, COUNTIF, SUMIFS, XLOOKUP and IF.
Open the formula grid →Star Schema Builder
Join facts to dimensions and watch a wrong join break the totals.
Open star schema builder →Dashboard Critique
Find six faults in a deliberately poor dashboard, with the rule behind each.
Open dashboard critique →DAX Sandbox
Write DAX measures and have them evaluated. A simulation, not Power BI.
Open dax sandbox →Metric Detective
A figure moved. Slice it by the right dimension to find out why.
Open metric detective →Build Your Confidence with Data
Start where it helps most today, and come back for the rest.