Burbing: to cycle every road in a suburb (this can be done across multiple rides)
It’s a simple concept; ride every road in a suburb and share it on Strava.
Back in 2014, I rode every road in my suburb Eaglemont, hot on the heels of a friend who rode every road in Montmorency, thus the concept of Burbing was born.
Fast forward to September 2021 and over 400 burbing rides have been undertaken. Burbings have been completed in USA, UK, Singapore, most Australian capital cities, but the primary focus so far has been Melbourne. Lockdown has driven a renewed interest in the necessity of exploring your own neighbourhood.
The key to success here is the data. Satisfaction in completion of the task can only come when the data is represented visually and celebrated verbally. Some have even taken to making imaginative ‘data pictures’ by forming dinosaurs or words in the patterns they have ridden. Data visualisation makes this all possible.
The importance of this data is also central to organisations and the vital decisions they need to make.
However, this does not always go as planned. For example, opening up Strava’s fitness-tracking data set made for fun data visualisation; until someone pointed out that the company had unintentionally revealed secret military bases around the globe, putting individuals and nations at risk. Effective solutions to many types of problems require accurate data and thoughtful decision-making.
Everyone in an Organisation Needs to be a Data Analyst.
Everyone in the organisation needs to understand how to analyse, understand, and act on data. Data analysis needs to be seen as more of a trait and skill, and less of occupation, job title, or certification.
You have probably heard about both the Internet of Things and Big Data. In a lot of ways, the two terms refer to completely different concepts. The IoT encompasses all things connected — like a smart home to a connected car. Big data refers to large sets of data that can be analysed and leveraged to capture patterns, trends, and associations.
Though they differ, the two intertwine in a few key ways.
There is no doubt the unification of analytics, data science, and integrated process automation is critical to delivering business outcomes that are both insightful and actionable. With this unification also comes a heightened need for self-learning and self-service, especially as more workforces look to upskill in remote working environments.
Transforming an organisation into data junkies, like most things, begins with the overall company culture. One key shift is a cultural move towards increased transparency.
Data provides answers, but only if it is accurately, promptly, and effectively shared. Smart companies leverage data into actionable insights. However, to do so, there must be a culture of trust and transparency.
Accurate bad numbers provide much more value to a business than massaged good numbers. Thus, employees must know that