Managing analytics projects Archives

Four reasons why getting started with predictive analytics is simpler than you think

We spend a great deal of our time at Smart Vision helping our clients to establish the use of predictive analytics in their business. For many organisations, getting started with predictive analytics can feel like a real departure from more traditional and familiar areas of activity. That said, organisations in almost every industry sector are becoming …

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Data science projects – what skills do you need and where can you get them from?

By Rachel Clinton

Data science is on the rise. A couple of years back Harvard Business Review suggested that ‘data scientist’ is the sexiest job title of the twenty first century and the hype around data science shows no sign of abating. The term ‘data scientist’ itself was only coined in 2008 but since then the number of data …

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Predictive analytics – what can you do with your results?

By Berni Simmons

I talked in my last blog post about the confusion that often emerges around how much data is enough to effectively deploy predictive analytics. I argued that sample selection is much more important than sample size when it comes to ensuring accurate results. As an example I talked about two political polls from the 1936 …

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Predictive analytics – how much data do you really need?

By Berni Simmons

When I’m talking to prospective clients something I hear a lot is ‘but we don’t really have enough data to do any data mining’. It’s a common misconception that you need vast terabytes of data to be able to do anything meaningful in terms of analytics. In fact there are a number of similar misconceptions …

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Deployment of analytics – a great example of the Anna Karenina principle?

By Berni Simmons

The Anna Karenina principle describes an endeavour in which a deficiency in any one of a number of factors dooms it to failure. Consequently, a successful endeavour (subject to this principle) is one where every possible deficiency has been avoided. The name of the principle derives from Leo Tolstoy's book Anna Karenina, which begins “Happy …

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Are the results of predictive analytics really that surprising?

By Rachel Clinton

It’s common to hear claims about how businesses will be transformed through the use of predictive analytics techniques with surprising and shock results that they never would have imagined to be the case. It’s particularly common for product or service vendors to make these kinds of claims when in pursuit of a possible sale. After …

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How the CRISP-DM method can help your data mining project succeed

By Julian Clinton

I’ve worked in predictive analytics for many years and have seen that a key factor for increasing the prospects of a project being successful is using a structured approach based around a data mining methodology such as CRISP-DM (a quick declaration of interest here – I was one of the team who originally developed the …

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The first step in predictive analytics – understanding your data

By Rachel Clinton

I speak to a lot of people in organisations just starting out on their analytics journey, organisations that have started to recognise that they could make better decisions if they could find the hidden patterns and nuggets of information in their data. Data talks and you can tell very quickly if it has something interesting …

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6 ways to increase the value of your predictive analytics project

By Jarlath Quinn

In my last blog post I talked about how it’s now possible to automate large parts of your predictive analytics projects, removing the need to get stuck into the complex statistics yourself. In this post I’ll suggest some ways to maximise the chances of your predictive analytics projects being successful. 1. Use a proven analytics …

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Getting started with advanced analytics – advice for analytics virgins

By Jarlath Quinn

What do you think of when you hear phrases like predictive analytics, data mining or machine learning? For many people these terms sound suspiciously like ‘statistics on steroids’ and unfortunately, even in the more data-centric and numerate industries, that isn’t likely to elicit the most enthusiastic of responses. To be fair that’s hardly surprising, as …

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