The Data Education in Schools team from the University of Edinburgh will be populating this post with links to software that can be used to support learners. There is another post that contains links to data sets that are openly available for learners and teachers.
| Spreadsheet Software | |||
| Tool | Link to access | Pros | Cons |
| Excel | Part of Microsoft suite | Can set up relationships between data tables
Wide arrange of graphics options Can write code using VBA |
Version control not automatic
Cost if not a member of a free programme Need to apply for free access |
| Google sheets | sheets.google.com | Free for everyone
Can publish to the web Can write code using Apps Script |
Limited dataset size: 5m cell max – excel is 17bn
Limited range of chart options |
| Point and click data analysis software | |||
| Tool | Link to access | Pros | Cons |
| CODAP | codap.concord.org | Free, open-source and designed for educational purposes
Lots of examples Intuitive data exploration Good data manipulation capability, online capability |
Data security
Version control Not very attractive – designed by academics, not designers |
| Orange | orange.biolab.si | Very detailed data analysis capability
Enables predictive modelling |
Need to download, not web-based
A small learning curve |
| Commercial visualisation software | |||
| Tool | Link to access | Pros | Cons |
| Power BI | powerbi.microsoft.com | Good training materials
Works well online Intuitive interface |
Need to apply for free access
Lack of data preparation tools |
| Tableau | tableau.com | Can write R code
Easy to use Integrates well with databases |
Need to apply for free access
Need to structure data first Version control not easy |
| Qlik | qlik.com | Attractive and easy to use | Need an account for free access
Syntax not very clear |
| Infogram | infogram.com | Free basic account
Simple to use online |
Basic package has limited functionality |
| Programming environments for data science | |||
| Tool | Link to access | Pros | Cons |
| R | www.r-project.org | Open-source
Great interactive development environment (IDE) Packages enable all types of analysis and visualisations Rshiny is used for dashboard and web applications |
Steep learning curve
Requires some coding capability |
| Python | Python.org | Open-source
Add on packages available to support data science Many different packages for visualisation Plotly is used for interactive plots |
Complexity – a full programming language
No centralised IDE Steep learning curve Requires some coding capability |