Category Archive: Data science

Data science = Data analysis "plus"

Hospital Analytics – are we getting there?

In the research literature we find thousands of papers documenting academic projects documenting analytical models for the hospital environment. But the big question we need to investigate is – how much of it is actually used operationally to make a real change to treatments and patient outcomes?

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Using an Analytics Platform for Hospital Research

Applying complex analytics on a very wide and rich dataset data is fundamental to deriving insights when researching new approaches to specialised care, optimising the effectiveness of clinical trials, reducing the lead time from research to clinical practice – all with the objective of improving quality and longevity of life. However, identifying, accessing, managing and …

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Empowering Employees to become Data-Centric

Building a data-centric organisation is becoming critical if you want to develop a strong competitive advantage. In this post I examine some insights into, what I consider, a key step, in actually ‘being’ data-centric. Given that any company is made up of more than just its executive team, it therefore makes sense that it should …

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Using a Modern Analytics Platform

The increased use of analytics, coupled with an exponential growth in the volume and complexity of data, has changed the business intelligence landscape forever. Business users’ sophistication has extended beyond descriptive reports and dashboards into data exploration, predictive modelling and aspects of cognitive computing. Traditional requirements-driven ETL, data warehouse and reporting approaches do not meet …

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Benefits of Data Visualisation

Data visualisation has become one of the most popular technologies today. Not only does it provide an organisation with the ability to visually present and analyse its information, but more importantly, it gives the organisation a new way of seeing and interacting with its data.

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Communication in Data Science

Data science and the outcomes it delivers can be complex and hard to explain. Presenting your approaches and findings to a non-technical audience, such as the marketing team or the C-Suite, is a crucial part of being a data scientist. You need to have the ability to interpret data, tell the stories contained therein, and …

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8 Aspects to Avoid in Visualisation

In my previous piece, I touched on the rise of data visualisation, and how it should be positioned in the organisation to achieve real insight from their data. In this piece I cover 8 aspects that should be avoided, in order to ensure that only clear and correct messages are conveyed to the business. Failing …

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The Rise of Data Visualisation

Over recent years, data visualisation has certainly made a positive impact, which is no surprise given that it can help organisations achieve real insight from data. But beyond this, it’s also a smart way for us to understand complicated information in a more user friendly way that furthers cognitive understanding. To my mind, if organisations …

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Overcoming analytical program hurdles

Over the last few years, we have noticed a sharp increase in the number of organisations that have shown an interest in implementing an analytics program with the hope and intention of gaining business benefit from it. However, as with everything ‘new’, there are always challenges that need to be overcome, before the real benefit …

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So you want to do data science?

Before your organisation blindly jumps in and starts “doing” data science, there are a number of issues you should first figure out and get clarity and agreement on.

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