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Jamie Skipworth

Technology Generalist | Software & Data

  1. Data Bashing

    I’ve spent a long time tinkering around with data, moving it around, mangling it and generally trying to make it a bit more useful. There are plenty of fancy and expensive tools out there like IBM InfoSphere, Informatica, Talend, and Ab Initio you can use to do this sort of stuff. So far, so boring. …

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  2. Extracting text from XML

    Earlier on I wrote a post where I performed word counts using programs written in Go. The text data came from StackOverflow’s bitcoin forum. However, those files are XML, so I had to perform some jiggery-pokery to extract the text from them. So, because my memory is terrible, I thought I’d spend some time here to document how I did it (well, for the Posts.xml file). …

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  3. Fun with concurrency and Go.

    You’d be surprised how deep a hole you can dig with a fork(). Sounds like a weird thing to say, but if you’ve ever written concurrent code then you can understand some of the headaches/nightmares it can cause. You start off with a simple enough idea, but then you either need better performance or it needs to handle multiple things at once. …

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  4. Behaviour Driven Development - BDD

    Sometimes you take a day or two off work and come back having missed some major development in, er, development. A while ago I was told I was doing testing wrong; test-driven development wasn’t good enough, it has to be behaviour driven. Easy mistake to make, I guess. …

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  5. Data is the new plutonium

    It used to be said that data was “the new oil”, and those who had it had the ability to mine rich seams for insights. In recent times with all the hacks, leaks and shady dealings it seems it’s less like oil and more like “the new plutonium”, and should also be considered a liability. …

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  6. AI Is The New Big Data

    I have a feeling that AI/ML is going to be the Big Data of 10 years ago - everybody thinks they need it, but they’re not sure why. It’s currently very fashionable to be an AI/ML play just like it was with Big data years ago, despite not having a problem that really warrants it. I’ve seen countless “big” data projects that cost millions, store and process tiny amounts of data. …

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