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 |