1 Summary of available resources

1.1 Analytical IT Tools Strategy

The MoJ Analytical IT Tools Strategy describes the analytical IT tools analysts are recommended to use along with the ways of working to be followed.

1.2 Analytical Platform

The Analytical Platform is a data analysis environment, enabling the use of modern open source tools such as R and Python, and holding key datasets for MoJ analysts.

To learn more about the Analytical Platform and to get up and running, go to the Analytical Platform chapter. More extensive information is provided by the Analytical Platform user guidance.

1.3 R mentoring

It is recommended that all who are new to R or Data and Analysis request an R mentor. The purpose of the scheme is to provide a better on-the-job R learning experience and raise awareness of the preferred Data and Analysis ways of working that will for instance enable people to get up to speed more quickly with others’ code. The scheme is also open to non-coders who need to use the Analytical Platform to advise them through the learning process, and for those commencing a more complex project involving the use of R.

To request an R mentor please complete this mentee form. If you could become an R mentor (we have a shortage of mentors) please complete this mentor form. For more information please contact Jose Vieira.

1.4 R/SQL/Git/Python Training Groups

Those working in Data and Analysis are recommended to take the internal training courses as they are run using the MoJ Analytical Platform. The main introductory R, SQL and Git/GitHub sessions are usually run live in February/March, June/July and October/November each year while you can also work through R, SQL, Git/GitHub and Python sessions yourself using the training material and/or recordings. To learn more about the sessions currently available and how to access the material and recordings, go to the R/SQL/Git/Python Training Groups chapter.

1.5 Coffee and Coding

The internal training (see above) is complemented by Coffee and Coding presentations. These presentations usually take the form of a demonstration of a tool or technique and/or a show and tell of work done within the department using particular coding methods. For more information go to the Coffee and Coding chapter.

1.6 Bite-sized sessions

There are also short sessions (generally talks of up to 15mins followed by Q/A) on a variety of topics including specialist as well as softer skills. Recent topics have included:

  • New statistical methods guidance for MoJ analysts
  • How to use the Evidence Library to support your work
  • Prototyping - why, how and when?
  • Key components of RAP in MoJ coding projects
  • ChatGPT for coding - Know your Frenemy
  • Hints and tips on public speaking
  • What are faith and belief?

You can find recordings of bite-sized sessions:

For more information including if you are interested in presenting a session or joining the bite-sized session facilitation team please contact Aidan Mews or Edward Adams.

1.7 Analytical Function training

There are many Analytical Function training opportunities for analysts including about specialist topics not presently covered internally. Examples useful for RAP practitioners include Best practice in programming – clean code and a more lengthy Introduction to unit testing than currently available internally. You can learn more about such opportunities via:

1.8 DataCamp

DataCamp licenses are beneficial to cover gaps in current training provision that are not currently picked up by either internal or Analytical Function training e.g. training in Power BI and more advanced or niche R, SQL, and Python skills.

1.9 Slack

Technical help can be requested via the following Data and Analysis slack channels:

  • ask-operations-engineering - this provides support to those with Analytical Platform issues
  • intro_R - this provides support to those starting out in the world of R
  • R - this is for beginners and experts alike
  • sql
  • git
  • python
  • RAP

More information about Slack including how to get set up is available via the Analytical Platform User Guidance and the Data and Analysis Hive.

1.10 Other assistance

You may also find useful:

There are also many useful free R and Python books on the web, for instance for Python: