Not just another Qlik hints, tips and news blog. I'll use this site to analyse interesting and fun data sets to demonstrate Qlik's ease of use and along the way discuss business intelligence in general. If you would like to contribute please get in touch.
Since it was announced in the 2015 Conservative party manifesto the TEF (a measurement of excellence that will allow high performing colleges and universities to increase tuition fees) has caused quite a stir in the world of higher education. There has been a lot of opposition, non more so than the National Union of Students (NUS) which has discussed encouraging a boycott. Despite this, it is set to go ahead and institutions are preparing by trying to predict their scores. Beyond these first results they will have to decide how to improve their scores and which metric to target first. However, which metric should they start with and are all the metrics related so that a positive impact on one will have a positive impact on the others? Using Scatter Charts in QlikView we take a look using UNISTATS data.
I’ve finished work for Christmas so I’ll be taking a short break from the blog to eat, drink and be merry with my friends and family. Driving back home from work earlier today Chris Rea’s dulcet tone came floating out of the car speakers with his aptly named song ‘Driving Home for Christmas.’ Continue reading
As a nod to the release of Star Wars Rogue One (and and excuse to try out a dark theme dashboard) I’ve put together a Qlik dashboard with some of the freely available Star Wars stats and data from around the internet.
You can do all sorts with charts, and people do. They should quickly convey accurate and insightful trends but they can be abused – twisted or exaggerated to tell whatever story the developer wants. They can also be mishandled by a well-meaning developer who has accidentally ticked the wrong option.
Often it’s easier to get the point across when it’s quicker to get to the point. That’s why we use charts. As a visualisation they should draw us to the key trends and figures without having to trawl through rows and columns of data. However, aren’t they a bit boring? Can’t we get the point across in a more immediate and engaging way? So let’s strip away those axes and titles then see what we can do with a data set on pet ownership in the UK which I’ve taken from http://www.pfma.org.uk/regional-pet-population-2016 and stripped down to just the northern regions. Here’s the raw data: