Course · Data Analytics

Data Analytics from Scratch: SQL, Spreadsheets and Metrics

A practical data analytics course in English: thinking like an analyst, metrics done honestly (mean vs median, percent vs percentage points), basic SQL (SELECT/WHERE/GROUP BY/HAVING/JOIN), spreadsheet analysis (formulas, pivots) and honest visualization. With interactive SQL gap-fills and formula entry.

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Unit 1 — The analyst's mindset and the nature of data

Why analytics, and the four kinds of analysis

6 exercises · Learner can explain what a data analyst actually does and tell apart descriptive, diagnostic, predictive and prescriptive analysis in order of increasing complexity.

Data types and how to tell them apart

5 exercises · Learner can classify a variable as quantitative vs categorical and, for numbers, as discrete vs continuous, and explain why the type drives which analysis is valid.

Dirty data, and the question before the data

6 exercises · Learner can spot the four common data-quality problems and can sequence an analysis starting from a clear question rather than from the dataset.

Unit 2 — Metrics without lying

Mean, median and mode — and when the mean lies

6 exercises · Learner can compute mean, median and mode on a small dataset and choose the median when outliers make the mean misleading.

Shares, percentages — percent vs percentage points

7 exercises · Learner can compute a share and a percent change and can correctly distinguish a change in percentage points from a relative percent change.

Absolute vs relative numbers in practice

5 exercises · Learner can decide when an absolute number, a rate, or a percentage best answers a question and can spot when a relative number hides a tiny or huge base.

Unit 3 — SQL: getting the data out

The relational model and your first SELECT

6 exercises · Learner can describe tables as rows and columns with keys and can write a simple SELECT … FROM to return chosen columns.

Filtering, sorting, DISTINCT and LIMIT

5 exercises · Learner can refine a query with WHERE, ORDER BY, DISTINCT and LIMIT and can predict the exact rows returned on a small table.

Clause order vs execution order

6 exercises · Learner can put SQL clauses in the correct written order and can explain why the logical execution order differs.

Unit 4 — SQL: grouping and relationships

Aggregates and GROUP BY

6 exercises · Learner can use COUNT, SUM, AVG, MIN, MAX with GROUP BY to summarise rows into per-group results and can predict the numbers on a tiny table.

HAVING vs WHERE

6 exercises · Learner can choose WHERE to filter rows before aggregation and HAVING to filter groups after aggregation, and can fix a query that uses the wrong one.

Joining tables: INNER and LEFT JOIN

5 exercises · Learner can join two small tables with INNER JOIN and LEFT JOIN and can predict which rows (and which NULLs) appear.

Unit 5 — Analysis in spreadsheets

References and core functions: SUM, AVERAGE, COUNT

6 exercises · Learner can write SUM, AVERAGE and COUNT/COUNTA formulas over a correct cell range and avoid off-by-one range errors.

Conditions and lookups: IF, COUNTIF, VLOOKUP

6 exercises · Learner can write IF and COUNTIF conditions and a VLOOKUP to pull a value from another table, and explain the common VLOOKUP pitfalls.

Sorting, filtering and pivot tables

6 exercises · Learner can sort and filter a small table and read a pivot table that aggregates a category, connecting it to SQL GROUP BY.

Unit 6 — Visualisation and conclusions

Which chart for which question

6 exercises · Learner can choose the right chart type (line, bar, scatter, histogram, pie) for a given analytical question.

Honest charts and thinking traps

6 exercises · Learner can identify misleading visuals and can name and apply correlation≠causation, survivorship bias and Simpson's paradox.

Capstone: from dataset to a defensible conclusion

5 exercises · Learner can take a small dataset situation end to end — frame the question, pick the metric, the query/aggregate and the chart, check the thinking traps — and write a correct, hedged conclusion with self-review.