The most frustrating thing for me about working with Student Record data has always been the free-text Course Title field. Improving the speed and quality of analysis means better decision making.
Across three years of data, there are almost 59,000 different first degree and PGT programme titles, with misspellings, random codes and hundreds of different ways to write “with placement” making powerful programme-level analysis more difficult.
With UniViz, you can receive insightful analysis more quickly as I have made three key additions that improve programme titles:
1) The ๐จ๐ป๐ถ๐ฉ๐ถ๐ ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ๐บ๐ฒ ๐ง๐ถ๐๐น๐ฒ strips out all of the unnecessary information, leaving only a clean, consistent titles. This means programme searching and cleaning takes minutes, not days.
2) ๐๐๐ฎ๐ฟ๐ฑ๐ have been removed from programme titles and given their own column in the data. This makes trends more obvious as there is no need to spend time matching a BSc in one year to a title without an award in others).
3) The ๐จ๐ป๐ถ๐ฉ๐ถ๐ ๐ฃ๐ฟ๐ผ๐๐ถ๐ฑ๐ฒ๐ฟ field improves how satellite campuses and partner institutions are treated. As far as possible, they are now separate, so you can benchmark against your peers, not the students they provide degrees for in other parts of the country.
I now work with almost ๐ฐ๐ฑ% ๐ณ๐ฒ๐๐ฒ๐ฟ ๐๐ถ๐๐น๐ฒ๐, freeing my time to focus on what actually matters: deep-diving into your programmeโs performance and making recommendations to boost its market position.
Clean data isn’t just a nice-to-have, it is vital to improving the recommendations we can make from it too.
๐ฃ๐น๐ฒ๐ฎ๐๐ฒ ๐ด๐ฒ๐ ๐ถ๐ป ๐๐ผ๐๐ฐ๐ต ๐๐ผ๐ฑ๐ฎ๐ ๐ถ๐ณ ๐๐ผ๐ ๐ต๐ฎ๐๐ฒ ๐ฎ๐ป๐ ๐ฝ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐๐ ๐๐ต๐ถ๐ฐ๐ต ๐ฐ๐ผ๐๐น๐ฑ ๐ฏ๐ฒ๐ป๐ฒ๐ณ๐ถ๐ ๐ณ๐ฟ๐ผ๐บ ๐ถ๐ป๐๐ถ๐ด๐ต๐๐ณ๐๐น ๐ฝ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ๐บ๐ฒ-๐น๐ฒ๐๐ฒ๐น ๐ฎ๐ป๐ฎ๐น๐๐๐ถ๐.
