When lockdown rules are relaxed it will be interesting to see if shopper’s return in the numbers we saw before the Covid-19 breakout. A large factor in this will be consumer’s confidence in stores to enforce social distancing and therefore retailers will be keen to measure performance in this new KPI. Offices and warehouses may also be thinking along the same lines. With footfall cameras and other IoT feeding data to Qlik Sense it’s possible to build a customer tracker and even an alert system. Here’s how…Continue reading “Customer Tracking on Floor Plans With Social Distancing Alerts”
There are plenty of Covid-19 dashboards out there (which is doing wonders for data literacy) but something caught my interest the other day when I was looking for my hometown of Sunderland in the government’s data. I was surprised to see the city in its elevated position in the ranked table of cases by upper tier local authority. The narrative we usually hear is that highly and densely populated regions are worst hit but there was Sunderland, above its larger neighbour, Newcastle.
I decided to scrape the data and then use Qlik’s associative engine to compare it with population data from data.gov.uk. For tips on working with geographic data on different administrative regions, KML files and more see the end of this article.