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Data analysis from zero flashcards

Turn a question and a messy file into a clear answer: ask, clean, explore, chart and explain, with spreadsheets, SQL and Python.

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Beginner friendly, starts from zero
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Data analysis from zeroStart from zero · 1 of 11

What is data analysis, in one plain sentence?

Using facts stored in tables to answer a real question, like "which product should we stock more of?", and explaining the answer clearly.

Question in, decision out.
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What you will learn

  1. Start from zero

    • What it is4 cards
    • The key words4 cards
    • The journey3 cards

  2. Core basics

    • Asking the right question3 cards
    • Clean and tidy data4 cards
    • Summarise and compare4 cards
    • Charts3 cards
    • Sharing results2 cards

  3. Next steps

    • Querying with SQL3 cards
    • Analysing with Python2 cards
    • Business analyses7 cards
    • Dashboards and experiments4 cards

  4. Go deeper

    • Metric design3 cards
    • Data quality at scale4 cards
    • Thinking about causes4 cards
    • Privacy and ethics3 cards
    • Working like a senior analyst3 cards

Final test and certificate

10 questions drawn fresh from the whole topic, about 15 minutes. Sign in, score 80% or more and get a free certificate with your name and a public check link anyone can open, such as an employer or a teacher. Not signed in? Try a practice test from the cards.

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About these cards

  • Reviewed 26 October 2026
  • CoversPostgreSQL 18pandas 3.1Microsoft 365 Excel and Google Sheets, 2026
How these cards are made

Data analysis from zero at a glance

Data analysis means using facts in tables to answer a real question, then explaining the answer so people can act on it.

A data analyst is like a detective: you start with a question, collect clues, throw out the false ones, and present the case so others are convinced.

Words you will meet

Dataset
A collection of data, usually one or more tables
Row and column
A row is one record, like one sale; a column is one detail, like the price
Metric
A number you track to judge how things are going, like monthly sales
Cleaning
Fixing mistakes, gaps and repeats in the data before using it
Chart
A picture of numbers, like a bar or line chart
SQL
A language for asking questions of data stored in a database
Insight
A finding that changes what someone will do

The steps

  1. 1. Start from zero (11 cards): What data analysis is, who does it, the steps of every analysis and the words used later.
  2. 2. Core basics (16 cards): From a vague request to a clean table, a summary and a clear chart.
  3. 3. Next steps (16 cards): SQL and Python for analysis, plus the business analyses analysts run every week.
  4. 4. Go deeper (17 cards): Metric design, data quality, causal thinking, privacy and the career skills that separate senior analysts.
All 11 cards in Start from zero
What is data analysis, in one plain sentence?
Using facts stored in tables to answer a real question, like "which product should we stock more of?", and explaining the answer clearly.
Why do people and businesses do data analysis?
To decide based on facts instead of guesses. A shop that knows which items sell on Fridays can stock better and waste less.
Where do you meet data analysis in everyday life?
Your phone's screen time report, your bank's spending summary, cricket player stats, election result charts and a shop's monthly sales sheet are all data analysis.
What everyday job is a data analyst like?
A detective. Start with a question, gather clues (data), drop false clues (cleaning), find the pattern, and present the case so people believe it.
What are a dataset, a row and a column?
A dataset is the collection of data. In a table, each row is one record, like one sale, and each column is one detail about it, like date, item or price.
What is a metric?
A number you track to see how things are going, like total sales per month or the share of students present each day.
What does cleaning data mean?
Fixing problems before using the data: removing repeated rows, filling or flagging empty cells, and making spellings match, like "Chennai" and "chennai".
What are a chart, SQL and an insight?
A chart is a picture of numbers. SQL is a language for asking a database questions. An insight is a finding that changes what someone will do.
What are the steps of almost every analysis?
Ask a clear question, get the data, clean it, explore it, analyse it, show it with a chart, and explain what to do. Then check whether the action worked.
What tools do you need to start?
A spreadsheet like Excel or Google Sheets is enough to begin. SQL and Python come next, for bigger data and repeatable work.
What will you be able to do after this topic?
Frame a good question, clean and explore data, choose the right chart, run common business analyses like funnels and cohorts, and present findings people trust.
Data analysis from zero cheatsheet

The analysis loop

  • Ask Decision, metric, deadline
  • Get Source, date pulled, data dictionary
  • Clean Count, dedupe, types, trim, gaps
  • Explore Min, max, distinct values, shape
  • Analyse Compare, segment, trend
  • Share Answer, evidence, action, caveats

SQL for analysis

  • GROUP BY city One row per group
  • HAVING COUNT(*) > 100 Filter groups
  • LEFT JOIN ... ON Keep all left rows
  • date_trunc('month', ts) Month bucket
  • LAG(x) OVER (ORDER BY month) Previous value
  • COUNT(DISTINCT id) Unique count

Pick a chart

  • Bar (sorted) Compare categories
  • Line Change over time
  • Scatter Link between two numbers
  • Histogram Spread of one number
  • Funnel Drop between steps
  • Cohort grid Retention by start month

Sanity checks

  • Totals match a known report Finance or source system
  • Row count before and after joins Catches duplication
  • Group totals add to the whole Catches dropped rows
  • Latest date is recent Catches stale data
  • Business time zone Correct daily totals
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