data is complex - our purpose is to make
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sense of it enabling your business to exploit its creative and
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strategic potential
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This first step is crucial. If your data is not suitably captured, it becomes hard to later collate all the information
to draw firm conclusions that test out your hypotheses. Not only do you need to capture results, but you need to ensure the correct
level of context around these results is also stored (the experimental conditions or environmental factors that could affect the
outcomes). It is important to avoid redundancy in dictionaries which describe these conditions and to avoid the creation of data silos
(isolated buckets of numbers that have only a limited value). Another factor to consider is the choice of the most suitable data
repository, which will vary with the style of data that is being captured.
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