The permanence of data

A number of recent events have lead me to consider a little bit more about the permanence of data. Is data a permanent or a temporary thing?

Attitudes to recycling and data

Having just come back from a trip to the USA, we noticed many cultural differences which we had to get used to:

• Use of the word ‘pavement’ to describe the surface cars drive on, whereas in England ‘pavement’ is the surface at the side of the road that pedestrians walk on (sidewalk in the US)
• The majority of road signs being text whereas in Europe they tend to be symbols
• Having to remember to add sales tax onto the price of items being purchased
• Having to show ID to purchase alcohol, despite being well over 21

Amongst the many cultural differences, it was interesting to note some of the different approaches to recycling. Since waste minimisation, like good data quality, may take more effort than sending waste to landfill or providing poor quality data updates we need to ensure that people have the right motivation and awareness both to minimise waste and to maximise data quality.

Different approaches to waste minimisation provide a few useful comparisons of the approaches needed to improve approaches to data quality

Right good data or The right good data?

Most businesses are trying to ensure that they have good data, or as they might say in Yorkshire “Reet good data” (hence the flat cap image).

Before expending lots of time (and money) polishing and honing your data to perfection, have you assessed whether you are improving the right data?

Have we reached the “Data Event Horizon”?

A recent Twitter conversation with Sarah Burnett (a leading UK public sector analyst) was the trigger for this slightly tongue in cheek blog post. Sarah originally posted the following tweet:

Which is an astounding statistic. Sarah and I then the following short discussion:

So, have we now reached the “Data Event Horizon”?

Data accident reporting

Those of you who are familiar with our blog will recall that we periodically compare how people treat data compared to real life situations. Two examples of this approach are “Would you allow this?” and “The Data Accident Investigation Board”.

Taking a similar approach this post will compare data accident reporting with Health and Safety Reporting.