All datasets needed to be uploaded to OneDrive. This is something I am familiar with and I had no issue in utilising OneDrive as required. It is vital to store datasets securely when using these for analysis. As good practice, ensuring data is stored and only accessible by those who require it again follows the Data Ethics Framework and GDPR principles. OneDrive can only be accessed using my login credentials and then is further protected using two-factor authentication.

Further protection can be provided by password-protecting the folder storing all datasets. I chose not to do this as it may impact on my ability to work with the data in Power BI due to access issues. Overall this was a straightforward process to set up and organise my project.

I also created a backup version of my datasets to ensure I had a clean copy of the original data if I lost data or made a mistake.

After selecting the data sets from the UK government and Office for National Statistics, the next step was to combine them for analysis and eventually output as visualisations into a dashboard using Power BI.

Before importing the data sets into Power BI I needed to filter the ONS datasets and narrow down which data sets I would require for my project. In total, I narrowed this down to six data sets that felt best fit with the intended objectives of my project. The data sets chosen focused on the public/private sector, as I thought this could add an additional area of analysis to my project. I also included the occupation, age by occupation, age by industry, work region industry and work region occupation.

Refining the datasets needed was quite time-consuming to look at the twenty individual datasets and judge whether they would be useful to my investigation.