Suggested tools that might be used by learners for the core and optional units in the National Progress Award qualifications in Data Science at Levels 4, 5 and 6

1. NPA Data Science
Tools Review
Kate Farrell
Director of Curriculum Development
and Professional Learning
Dr Jo Watts
Founder, Effini

2. Tools review
• Power BI
• Tableau
• Qlikview
• Infogram
• R
• Python
• Orange
• CODAP
• Excel
• Google sheets
Spreadsheet
tools
Point and click
analysis
Visualisation
packages
Programming
languages

3. Spreadsheet tools
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
Excel
Google
Sheets

4. Commercial visualisation packages
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
Power BI Tableau Qlik Infogram

5. Point and click analysis/visualisation
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
CODAP
Orange

6. Programming languages
Tool Link to access Pros Cons
R www.r-project.org
rstudio.com
• Open source
• Great IDE
• Packages enable all types of analysis and visualisations
• Rshiny can be 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 can be used for interactive plots
• Complexity – full programming
language
• No centralised IDE
• Steep learning curve
• Requires some coding capability
Rshiny
Using R
Plotly
Using
python

7. Kate.Farrell@ed.ac.uk
jo@effini.com