Our A Day in the Life of Series continues today with a new post – A Day in the Life of a Data Analyst. Here at The Workplace Depot we enjoy being involved in the community and like to think together we can make a difference. Recently we have started offering 12 weeks placements and internships to students from the University of Nottingham. Placements and internships represent a great opportunity for both students and graduates to get the much needed work experience. Freya is currently on a 12 weeks Internship with us and she analyses data, but let’s see what she has to say about her usual days at work.
@8.45am… I am sitting at my computer with a cup of tea looking at the spreadsheet I will be working on today. As an intern I tend to only have one project running at a time, so this will be my main focus for the day. Today I’m working on the sales figures for this month; running them through a formula, dividing it into categories and presenting it with previous sales figures. My degree taught me some aspects of statistical analysis and data manipulation, but during my final year project I started teaching myself new, quick ways to analyse and process data. This learning was mostly self-taught and developed my interest in data analysis.
@9.30am… Still working through the spreadsheet; this is a very large set of data so it can take time for the computer to process it.
@11.00am… Starting to put all of the processed data into a summarised sheet and merrily eating a clementine.
@13.00pm… For lunch I tend to take a walk to stretch my legs and look away from the computer screen. I love data analysis and spread sheets, but if I don’t have a break from staring at the screen I see thousands of excel cells when I close my eyes at night. When I’m back from my walk I still have some of my lunch break left, so I eat my anticipated lunch while socialising with colleagues in the kitchen – then it’s back to work.
@2.00pm… I’ve finished the analysis of direct and indirect sales for the last month so now I will move onto gathering data on particular distributors and re-sellers. From this data I will locate the most popular items, trends in the data, relationships that can be drawn from the findings and generally anything I find that could be deemed as interesting or relevant.
@4.30pm… I have all of my data collected for the specific re-seller, and have created graphs and charts of relevant material. Now I will write in any notes that I believe are relevant to the data, such as assumptions as to why some changes in sales occurred, and highlight trends and changes in sales and the re-seller’s buying patterns. This is important as these changes may not be obvious in the chart/graph set.
@6.15pm… I’ve been home for around 15 minutes, which means I am cooking dinner – something I really enjoy (almost as much as eating it).
@8.30pm… I am running to the cinema, I always forget how long it takes to walk there and the show starts at 8.45. I want to get a Coke before I run in, but last time this happened I missed the start of 10 Cloverfield Lane and had no idea how Mary Winstead ended up in John Goodman’s home, or why his home looked like that of an extreme coupon clipper.