What we’ve been reading this week 26 July 2019
It’s been a busy few weeks for us at Analytics Engines. Preparations for Big Data Belfast continue and we’re delighted to have Ernst & Young (EY) as our headline sponsor for this year’s event. We’re also delighted to be supported by DELL, Allstate Northern Ireland, SmashFly, SpotX and Altra Executives. Tickets for Big Data Belfast 2019 are available from Eventbrite. Looking to the world of data, here are some of the things we’ve been reading and have found interesting this week.
Echoing sentiments made in our “making better decisions” blog series, this article from Quartz explores the collaborative approach between humans and data that is needed in order for meaningful insight to be created.
Article author, Andrea Jones-Rooy states “Data can’t say anything about an issue any more than a hammer can build a house or almond meal can make a macaron. Data is a necessary ingredient in discovery, but you need a human to select it, shape it, and then turn it into an insight”.
The Open golf championship at Royal Portrush concluded this week with Shane Lowry taking home the famous Claret Jug. Despite being the oldest golf championship in the world, organisers of the event have set their sights firmly upon the future, utilising Artificial Intelligence at this year’s event to automatically process video highlights and to analyse player performance.
Sticking with sport, this article from Cycling Tips looks at the up and downs of the first week of the Tour de France. For those interested in taking a closer look at the data, be sure to also check out these interactive visualisations.
In a recent blog, we discussed the way by data can help organisations to identify new opportunities, looking specifically at Netflix and their recommendation engine. This article from the Netflix blog looks at how they use data to determine which artwork is shown to individuals in order to deliver a more personalised customer experience.
We end this week’s reading list with a question. Did the 80s really have the most one-hit wonders? This article from Towards Data Science seeks to answer just that, taking a look at the data behind some unforgettable tracks!
