Data quality problems all, at their root, involve some form of human error. Whilst this is easy to say, it is perhaps harder to identify and resolve the causes of these human errors. In this blog post, I will explore
When talking about data quality, it is usual to consider different aspects or ‘dimensions’ of data quality – validity, completeness, uniqueness, consistency, timeliness and accuracy. These six dimensions were agreed as the most relevant and representative of data quality as
The world is changing, people are changing, organisations are changing, and this is no different for data requirements. An organisation needs to accept this and makes sure that change requirements are captured, impact assessed, acted upon and communicated. During my
Most people should be familiar with the old adage “Garbage In, Garbage Out” intended to remind people that if your input data is poor, then any outputs will also be poor. There is a variant of this that cropped up
A colleague of mine recently posted a very interesting blog titled Do you trust your data? This led me to think about the issues from the perspective of the data i.e. if I am a data set can I trust
Those days when you need to make an important decision can be trying at the best of times. The old saying “Garbage In, Garbage Out” is never more relevant (particularly if an AI tool is making automated decisions).
In the Victorian era, accident rates were far higher than today yet at the time were considered regrettable, but just the way things are. How about modern attitudes to data?
The social housing sector in the UK continues to operate in challenging times – the combination of a continued shortage of housing, reduction in grants from government and ageing asset stocks means that there needs to be a consistent drive
How you manage your data quality can have quite an impact on your organisation’s results. If you think about taking your car for an MOT*, you’re taking it to be assessed against the criteria set out by the government to
Many organisations use and manage data in ways that are less than ideal, however what does a data enabled organisation look like? This question was recently asked by one of our clients who wanted to find ways to visualise what