Data Analysis

6 subjects · 13 chapters · 52 topics

1. 01

   Thinking Like an Analyst

   1.1 Framing the question

   • Turning a business question into a data question
   • Metrics, dimensions and grain
   • Defining success before you start
   • Common analytical mistakes

   1.2 Data types and sources

   • Structured, semi-structured and unstructured
   • Databases, files and APIs
   • Sampling and bias
   • Data dictionaries
2. 02

   Excel and Spreadsheets

   2.1 Core spreadsheet skills

   • Formulas, references and named ranges
   • Lookup functions
   • Conditional logic and text functions
   • Data validation

   2.2 Analysis in the sheet

   • PivotTables and slicers
   • Charts that answer a question
   • What-if analysis and Goal Seek
   • Power Query basics
3. 03

   SQL for Analysis

   3.1 Querying

   • SELECT, WHERE and ORDER BY
   • Aggregation and GROUP BY
   • Joins across tables
   • Subqueries and CTEs

   3.2 Going further

   • Window functions
   • Date and string handling
   • Cleaning data in SQL
   • Writing readable queries
4. 04

   Python for Analysis

   4.1 Pandas

   • Series and DataFrames
   • Reading and writing files
   • Filtering, sorting and grouping
   • Merging and reshaping

   4.2 Cleaning data

   • Missing values
   • Duplicates and outliers
   • Type conversion and parsing dates
   • Validating a cleaned dataset

   4.3 Exploratory analysis

   • Descriptive statistics
   • Distributions and correlations
   • Segment comparison
   • Documenting what you found
5. 05

   Statistics You Will Use

   5.1 Describing data

   • Mean, median and spread
   • Percentiles and quartiles
   • Skew and outliers
   • Confidence intervals

   5.2 Comparing groups

   • Hypothesis testing in plain terms
   • A/B tests and sample size
   • p-values and what they do not mean
   • Practical versus statistical significance
6. 06

   Visualisation and Communication

   6.1 Charts that work

   • Choosing the right chart
   • Colour, scale and axis honesty
   • Dashboards with Power BI or Tableau
   • Interactivity and filters

   6.2 Telling the story

   • Structuring an analysis narrative
   • Writing an executive summary
   • Presenting to non-technical stakeholders
   • A capstone analysis, end to end