Remove the admin burden of data collection

With so much more data available, there is a growing appetite for reducing the time spent on the admin part of data gathering to using that time for analysis and interpretation.

Many organisations are looking to automate their processes. But where these types of projects often become difficult is to know where to automate, and at which part of the process to start.

Lots of commentary around data management is about Artificial Intelligence (AI), Bots and Machine Learning. So that might seem like a good place to start, surely?

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Make the most of your data and statistics

As the amount of data organisations has continues to increase, regulation such as the upcoming EU General Data Protection Regulation (GDPR) comes into force and technology advances, 2017 is the year to define data journeys and put a strong data strategy in place.

It may be a daunting prospect, and some in your organisation may not see the need as much as others, so we have put together our top five tips to help those thinking about getting more from the data in their organisation.

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What if we automated this process?

These days new products and software help and support us in our everyday lives. As with many new ideas it's just about those lightbulb moments … ‘what if we automated this process?’.

It’s only within the last two centuries that automation really took hold. The first automated wool spinning mill started the industrial revolution and aircraft first flew by autopilot, a 100-year-old idea that has been reinvented into my smartphone telling me where I am, where I should go and how I should get there (I’ve not looked for a wool spinning app yet).

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Spreadsheets overflowing with data?

We are just in the middle of helping a client move some of their data from spreadsheets into DataLab, and the process just serves to remind me of the limitations found using spreadsheets like Excel.

Don’t get me wrong, I am a huge fan of Excel as it is a really powerful tool, and indeed I still use it extensively for the right reasons. It becomes clear however that, as more and more data becomes available, spreadsheets are easily overloaded when they are used to try and do too much.

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Data visualisation

In preparing data for DataLab and seeing some of the coding that sits behind our work, it often seems that patterns in data produce a form of art. Fortunately, it isn’t just me needing a break. When you start looking, there's lots of inspiring art made from the visualisation of data that go above and beyond the humble interactive CloudCharts. Here are two examples I came across recently.

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