SQL, analysis, and business decisions

Data Analyst

Learn to retrieve, clean, summarize, and explain data so a stakeholder can make a defensible decision.

By the end

Turn raw tables into trustworthy metrics, analytical reports, and clear product recommendations.

Start here

Filtering Rows

Ask a table for exactly the rows and columns you mean, and nothing else.

Start with Filtering Rows
01

Ask useful questions with SQL

Select the right records, summarize them, and combine related tables.

0 / 4 core
  1. SQL & DataFiltering RowsAsk a table for exactly the rows and columns you mean, and nothing else.
  2. SQL & DataGrouping and AggregationCollapse many rows into one answer per group, and know exactly which rows each number counted.
  3. SQL & DataJoining TablesPut rows from two tables side by side, keep the ones that should survive, and find the ones with no partner.
  4. SQL & DataSubqueries, CTEs and Set OperationsUse one query inside another: as a value, as a list, as a table, as a named step, and as a set to compare against.
02

Clean and reshape answers

Handle ordering, text, dates, duplicates, and awkward gaps in real data.

0 / 4 core
  1. SQL & DataSorting and PaginationPut rows in the order the reader expects, break every tie on purpose, and hand back one page at a time.
  2. SQL & DataStrings and TextCut, clean, count, and combine text with a handful of functions that compose into anything.
  3. SQL & DataNumbers and DatesDo arithmetic the way the database does it, and treat dates as values you can subtract, shift, and take apart.
  4. SQL & DataDuplicates, Median and ModeFind what repeats, keep one of it, and summarise a column by its middle and its most common value.
  5. SQL & Data · OptionalRanges and GapsFind what is missing from a sequence, what runs together, and what overlaps in time.
03

Build analytical reports

Use windows, reporting shapes, and product metrics to explain what changed and why.

0 / 4 core
  1. SQL & DataWindow Functions I: Ranking and Top-NCompute a value across a set of rows without collapsing them, then rank, pick the top few, or compare each row to its group.
  2. SQL & DataWindow Functions II: Running ValuesLet each row see the rows before and after it: running totals, changes from the previous row, gaps to the next, and moving windows.
  3. SQL & DataReporting and ReshapingTurn rows into columns and columns into rows, bucket values, fill blanks with zeros, and add the total line.
  4. SQL & DataProduct Analytics PatternsRates, active users, retention, funnels, and churn: the handful of query shapes behind almost every product metric.
  5. SQL & Data · OptionalHierarchical and Recursive QueriesWalk trees of any depth, build paths, and generate the rows you do not have, with one recursive CTE shape.
  6. SQL & Data · OptionalChanging DataInsert, update, and delete rows safely: from literal values, from other tables, with conditions, and inside a transaction.
04

Add Python and statistical judgment

Move beyond a query to inspect data, quantify uncertainty, and evaluate an experiment.

0 / 3 core
  1. Data Science & MLPython for Data WorkTurn Python records into trustworthy, analysis-ready tables with NumPy and pandas.
  2. Data Science & MLProbability and Statistical ReasoningBuild probability from cases, then use it to reason about repeated observations and evidence.
  3. Data Science & MLExperimentation and Product AnalyticsTurn an advertising-product experiment into defensible metrics, comparisons, and a product recommendation.