Over the past few years I've pondering what is wrong with most of the data systems I interact with.
To be honest I've been pondering this for most of my career as I was frequently sent to the dungeon (aka medical records) to review, sometimes also find on the stacks when that was allowed and synthesise it into something. That evolved to doing the same digitally and that is what most data analysts and scientists spend most of their time doing. Granted they generally use more sophisticated techniques then I ever did.
That is probably the first concern.....data capabilities have become incredibly good but in big data before it and AI more contemporaneously the problem is as all good data/computing people know garbage in garbage out (for some reason I prefer it to the more British, and therefore correct, rubbish!). Amalgamating data sets, federation (good and bad forms of this....no I don't mean the FDP specifically), SDEs, data linkage etc all are held up with the promise of moving us to the truth. But the real truth is that improving data quality is a wicked problem.
So what am I getting at? Well I am interested in how people feel about data management, what they might think about how to shift the entire ecosystem if in fact that is needed to tackle said wicked problem and what the critical non-technical considerations need to be. If there is an appetite I will elaborate and we'll see if we can get some conversation going.
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Over the past few years I've pondering what is wrong with most of the data systems I interact with.
To be honest I've been pondering this for most of my career as I was frequently sent to the dungeon (aka medical records) to review, sometimes also find on the stacks when that was allowed and synthesise it into something. That evolved to doing the same digitally and that is what most data analysts and scientists spend most of their time doing. Granted they generally use more sophisticated techniques then I ever did.
That is probably the first concern.....data capabilities have become incredibly good but in big data before it and AI more contemporaneously the problem is as all good data/computing people know garbage in garbage out (for some reason I prefer it to the more British, and therefore correct, rubbish!). Amalgamating data sets, federation (good and bad forms of this....no I don't mean the FDP specifically), SDEs, data linkage etc all are held up with the promise of moving us to the truth. But the real truth is that improving data quality is a wicked problem.
So what am I getting at? Well I am interested in how people feel about data management, what they might think about how to shift the entire ecosystem if in fact that is needed to tackle said wicked problem and what the critical non-technical considerations need to be. If there is an appetite I will elaborate and we'll see if we can get some conversation going.