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Archive | Data Science

Book cover - interactive visualisation for the web

Book review: Interactive Data Visualization for the web by Scott Murray

Next in my book reading, I turn to Interactive Data Visualisation for the web by Scott Murray (@alignedleft on twitter). This book covers the d3 JavaScript library for data visualisation, written by Mike Bostock who was also responsible for the Protovis library.  If you’d like a taster of the book’s content, a number of the examples […]

A sea of data

My friend Simon Holgate of Sea Level Research has recently “cursed” me by introducing me to tides and sea-level data. Now I’m hooked. Why are tides interesting? When you’re trying to navigate a super-tanker into San Francisco Bay and you only have few centimetres of clearance, whether the tide is in or out could be […]

Asking data questions of words

The vast majority of my contributions to the web have been loosely encoded in the varyingly standard-compliant family of languages called English. It’s a powerful language for expressing meaning, but the inference engines needed to parse it are pretty complex, staggeringly ancient, yet cutting edge (i.e. brains). We tend to think about data a lot […]

Data Visualization Cover

Book Review: Data Visualization: a successful design process by Andy Kirk

My next review is of Andy Kirk’s book Data Visualization: a successful design process. Those of you on Twitter might know him as @visualisingdata, where you can follow his progress around the world as he delivers training. He also blogs at Visualising Data. Previously in this area, I’ve read Tufte’s book The Visual Display of […]

Data Science Magic

As a business person, if I want insight into my business needs, I can ask a data scientist for answers, so I can make better decisions! Urgh: the sound I make reading that. I am starting to wonder if Data Science is seen as magic, and insight as arcane wisdom distilled from eyes of newts […]

Data Business Models

If it sometimes feels like the data business is full of buzzwords and hipster technical jargon, then that’s probably because it is. But don’t panic! I’ve been at loads of hip and non-hip data talks here and there and, buzzwords aside, I’ve come across four actual categories of data business model in this hip data […]

Hip Data Terms

“Big Data” and “Data Science” tend to be terms whose meaning is defined the moment they are used. They are sometimes meaningful, but their meaning is dependent on context. Through the agendas of many hip and not-so-hip data talks we could come up with some definitions some people mean, and will try and describe how […]

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