Analysts’ Guide

Author

statistics.development@education.gov.uk

Published

September 6, 2024

This website is a guide aimed at anyone working in analysis or statistics in the Department for Education (DfE). It includes tips on best practice and learning resources across a number of areas.

We hope it can prove a useful community driven resource for everyone from the most experienced analyst right through to those just starting out. If you have any feedback, suggested additions, or wish to challenge any of the guidance, feel free to use the GitHub links to suggest changes directly, or contact us at the email you can find at the bottom of the page.

Learning and development

Learning support - Useful learning resources, and support to get you started

SQL - Guidance and tips for accessing data via databases with SQL

R - Guidance and tips for using R

Git - Guidance and tips for version control with Git

Python - Guidance and tips for using Python

Accessibility - Tools and resources for digital accessibility

Statistics production

Routes for publishing - Guidance for how to publish different types of statistics

RAP in statistics - Detailed RAP guidance for statistics publications

Open data standards - Guidance on how to structure data files

Explore education statistics (EES) - Tips on using the explore education statistics service

Good examples in EES - Good practice examples in the explore education statistics service

Embedded visualisations in EES - How to embed R-Shiny charts in EES publications

Publication scrums - Information on the scrums we run and tips for writing statistical commentary

User engagement - Guidance on understanding and engaging with the users of published statistics

EES analytics - Understanding how users are interacting with your publications

Writing and visualising

Public dashboards - Guidance for publishing public facing statistics dashboards

Publishing an R-Shiny based dashboard - Guidance for publishing public facing statistics dashboards using R-Shiny

Visualising data - Resources and best practice to guide you when visualising data

Writing about data - Resources and best practice for writing about data

Reproducible Analytical Pipelines (RAP)

RAP in statistics - Detailed RAP guidance for statistics publications

RAP expectations - Guidance for all analysts on expectations of RAP

RAP support - Details on support available for RAP in DfE

RAP FAQs - Frequently asked questions about RAP

Analytical Data Access (ADA) and Databricks

Analytical Data Access (ADA) and Databricks - Guidance for analysts on how to interact with and use data stored in ADA using Databricks

Databricks Fundamental Concepts - Fundamental concepts in DataBricks that will help you navigate and understand the platform

Databricks Notebooks - Guidance on Notebooks in DataBricks

Databricks Workflows - Guidance on Workflows in DataBricks

Setup Databricks SQL Warehouse with RStudio - Guidance for analysts on how to connect to a Databricks SQL Warehouse from RStudio.

Setup Databricks personal cluster Warehouse with RStudio - Guidance for analysts on how to connect to a Databricks personal cluster from RStudio.

Contact us

Our mailbox is always monitored and is available for anyone in DfE to ask questions about statistics, whether that is about RAP, building dashboards, coding support, learning and development or statistics publications.

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