demonCoreData

Photo by Walter Nissen (Wnissen). (Own work) [Public domain], via Wikimedia Commons I first encountered the term ‘Dogfooding’ or ‘to eat your own dog food’ last year at the 2016 Tableau conference in Austin, TX. I was attending a session on how Tableau use their own product to visualise their HR data. The presenter uttered the line ‘We firmly believe in eating our own dog food’. The meaning was immediately clear to me – if it’s not good enough for internal usage, it’s hard to make the case that others should invest in the product. Literally: if it’s not good enough for me, it’s not good enough for my dog. Great … I get the idea fully & clearly … Unfortunately, I also have a strong smell-memory of dog food that’s triggered every time I hear the term. I’m not joking! As I’m writing this the air is heavy with the imagined scent of tinned dog food … it’s not pleasant! Once the Tableau presentation ended I was free of the term – while it may have some currency in the US...

Screenshot of the Tableau Dashboard. Available [ here ] and at the end of this post. [Note: the dashboard is best viewed in Full Screen (F11) Mode] This Visualisation uses two datasources provided by OpenDataNI. The first is the Belfast Bike Hire Rentals and Returns dataset ( https://goo.gl/fjkRj3 ). Along with the numbers or Rentals and Returns, it is broken down by Location, Month, and Year. Each location name is accompanied by a Station Number. This is used as the key to join to the Belfast Bike Hire Stations dataset ( https://goo.gl/CxpjXM ) which, among other things, has contains the Latitude & Longitude (even if it is mistitled 'Longfitude'). There are a number of location naming inconsistencies in the Rentals data, so I've used the names as supplied in the Stations resource instead. The left side of the visualisation is taken up with a map of central Belfast. There is a dot for every Bike Station, sized by the number of Rentals or Returns & colou...

Screenshot of the Tableau Dashboard. Available [ here ] and at the end of this post. [Note: the dashboard is best viewed in Full Screen (F11) Mode] Back in early 2016, when Trump was still seen as unelectable, he directed a portion of his Twitter barrage against President Obama on the latter’s use of Federal Executive Orders . I’m not going to pretend that I’m so politically astute that these comments caught my attention at that time. However, when commentators started to contrast Trump’s statements with his actions once in office, I immediately felt that this was a place where a visualisation of the data would be of use and interest. In my defence, I would note that I’m not so naïve that I believe that actual facts and figures hold sway any longer in either US or British politics … we can but try! The datasource My initial experimentations and explorations of this data started with the List of United States federal executive orders Wiki page. This is quite high-level d...

Screenshot of the Tableau Dashboard. Available [ here ] and at the end of this post. A dream of Bob Dylan When I was a kid, my parents wanted to ensure that I’d do as well as I possibly could in exams and get a place in University. To this end they hired a personal tutor to give me additional tuition in a variety of subjects that I kinda sucked at.* That’s why they hired JS. The routine was always the same … JS would come to my house and I’d attempt to feign interest and proficiency in my coursework for an hour or so, a couple of times a week. One evening I was listening to the radio when he came over and his first words were ‘What’s that on the radio?’ … well, no, actually … he didn’t say that at all … his language was peppered with obscenities and, when I said it was just something from the charts, he only got more agitated. Lessons were abandoned for the evening as I was treated to a tirade on the poor quality of what made the charts (it was the mid 80s … he wasn’t wrong)...

Screenshot of the Tableau Dashboard. Available [ here ] and at the end of this post. (Updated: see notes at end) After much legal wrangling and foot-dragging, the Northern Ireland Department of the Economy have finally published a partial list of recipients of money from the botched Renewable Heat Initiative scheme . At present only limited companies and limited liability partnerships who received in excess of £5,000 (cumulative) are listed. The data runs from the start of the scheme to 28 February 2017. After the list was published (16 March 2017) a number of people complained that they should treated as individuals, and not as limited companies. These corrections were made and a second list was issued the same afternoon. The dataset used here is based on this second list. The first thing I want to note about the document made available by the Department of the Economy is that it is presented as a PDF. This is data! To analyse data you need it in a suitable format su...

Screenshot of the Tableau Dashboard. Available [ here ] and at the end of this post. I was recently thinking back to last year’s ODI Belfast unConference where someone mentioned one of the smallest (and, by implication, the least useful) datasets available on their website [ here ] – the  list of 22 Bowling Pavilions in Belfast City. The question was ‘what can you possibly do with a list of 22 bowling pavilions?’ I seem to remember the suggestion that they might be useful in the event of a Zombie Apocalypse where they could be put to use as holding centres for the contaminated. I’m not a huge fan of the Zombie genre, but even I know that this approach will not end well. So … what do you do with a list of 22 Bowling Pavilions? This is a question that has been ticking away in the back of my head for a while now (wow … I really don’t have the richest internal life, do I?) … how do you use this kind of data in a useful way? Sure … I can build you a dashboard that shows all of...