Lakes and Data

by | Sep 10, 2019 | ICT4D |

Growing up beside the Great Lakes in Canada gave me a distorted view of the size of lakes, but I didn’t realise it. Lakes come in all shapes and sizes, but because of my starting point, I viewed most lakes as just big ponds. The first time I saw the ocean, I can remember not being impressed as it just looked like a ‘great lake’ I’d grown up around. Not being able to see the other side was not a unique feature for me as it was normal when I stood on the shores of one of the Great Lakes.

Size is relative, at least in how it is perceived because even the Great Lakes are small droplets in comparison to the oceans when we look at globe.

Something similar happens when we talk about ‘big data’ – the ‘big’ can be quite relative depending on who is looking at it. While NGOs and even the humanitarian community collect a lot of data, the dataset is quite small in comparison to the data generated daily on YouTube or Facebook or the data Amazon, Google, Microsoft, Apple handle each day.

One is not better or worse than the other, it is simply important to be clear on the size of the body of water (dataset) on whose shores you stand.

Photo by Ludovic Charlet

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