Guides to working with data.

Learn data analysis

• How to do data analysis: six steps, worked on a real example

  The six steps of data analysis (question, collect, clean, explore, analyse, report), each worked on one 30-day dataset with Excel, SQL and Python code you can run.

  4 min read

• Data analysis methods and techniques: what each answers and when to use it

  The main statistical and analytical methods, grouped by the question they answer: averages, spread, relationships, uncertainty and trends, each with a worked value.

  3 min read

• Excel data analysis: the formulas, PivotTables and ToolPak that matter

  How to analyse data in Excel: the formulas that answer most questions, how to build a PivotTable, and how to turn on the Analysis ToolPak, with every formula tested.

  3 min read

• Python and SQL for data analysis: the same questions answered both ways

  Learn when to use SQL and when to use Python (pandas) for data analysis, with the same six questions answered in both and every query run against a sample dataset.

  3 min read

• Data analysis examples: six questions answered from one dataset

  Six data analysis examples from one 30-day dataset: totals, a sale-day outlier, ad spend versus orders, a trend, a channel test and a forecast, each with its result.

  3 min read

• Free online data analysis tools, and how to choose one

  Free ways to analyse data online: spreadsheets, SQL engines, Python, calculators and AI tools, what each is good for, and a checklist for choosing one you can trust.

  3 min read

Working with your own data

• How to find out what changed in your sales data

  A step-by-step way to work out when a number moved, which part of the business moved it, and whether it is worth acting on.

  2 min read

• Real change or random noise? A plain guide to reading your numbers

  Why every business number wobbles, how to tell a meaningful move from the usual wobble, and the five mistakes that produce false alarms.

  2 min read

• Where to find free public data, and how to check it before you trust it

  The main places public data lives, the checks to make before using it, and the traps that quietly spoil an analysis.

  2 min read

• How to clean a messy CSV before you analyse it

  A checklist for the problems that break spreadsheets and charts: stray header rows, decimal commas, ambiguous dates, hidden totals and more.

  2 min read

• How to forecast next quarter’s numbers without fooling yourself

  A forecast is only worth having if it has been tested against the past. How to build a baseline, test methods, read a range and know when to say no.

  2 min read

• Chat with your data: what it takes to trust the answers

  Asking questions of your data in plain words is easy. Trusting the reply is the hard part. What to check before you act on an answer.

  2 min read

• How to analyze your data without SQL or code

  A practical path for people with a spreadsheet and a question but no analyst: what to ask, in what order, and where plain-language tools help.

  2 min read

• ChatGPT or a data analysis tool? How to choose

  General chatbots and purpose-built data tools both answer questions about your numbers. Where each is the right choice, and what to check either way.

  2 min read

• Spreadsheet or AI data tool: which one for which job?

  Spreadsheets are still the right tool for many jobs. Where an AI data tool saves time, where it does not, and how to use both together.

  2 min read

• Types of data analysis: descriptive, diagnostic, predictive and prescriptive

  The four types of data analysis in plain words, what question each one answers, and which tools suit each one.

  2 min read

• Data visualization techniques: which chart for which question

  A practical guide to data visualization examples and techniques: choosing a chart by the question you are asking, and the mistakes that mislead readers.

  2 min read

• How to choose a data analysis tool: a checklist for business teams

  What to compare when choosing online data analysis, business analytics or data visualization software, and the questions that separate them.

  2 min read

New to choosing software? Start with data analysis software: which kind fits your job.

Prefer to see it work? Try the live demo or browse the worked examples. For formulas, see business metrics and statistics methods.