Thursday, 19 June 2014

Big Data and KM - different but complementary

Knowledge, Information and Data; usually linked, often confused, not the same.

Part of the confusion, I have argued, comes from a deficiency in the English language, which uses the same word Knowledge for two different concepts; the accumulation of facts, and the accumulation of Know-how. Where other languages use different words for these concepts, we use the same word.

For me, it is Know-how that has the greater value, and it is KM focused on Know-how that delivers the greatest breakthroughs and the greatest impact to organisations. Know-how gives you the ability to act and to make correct decisions, while the accumulation of facts is closer to Information Management. The accumulation of facts without the know-how leaves you "better informed, but none the wiser".

Now "Big Data" enters the scene, and we see many people claiming that Big Data is part of Knowledge Management, because through Big Data we can gain added insight.

My argument is that Big Data is still data and needs data management rather than being included under knowledge management, and this is neatly illustrated in an article from this week's issue of New Scientist magazine entitled "Too Much Information" and bearing the interesting subtitle "What can you do with 9.8 million DVDs worth of data? Anything .... but you'll still need the know-how".

Big Data and Knowledge at the EBI

The article describes the data within the European Bioinformatics Institute, which houses sequences genome data from all over Europe totalling many petabytes. The sheer size of the database creates problems when it comes to storing, handling and transferring it, but the real issue comes when trying to make sense of it, and draw conclusions from it.

As New Scientist says
"The people who work at the EBI are the jewels of the institution. The work attracts a certain kind of person ... a breed of researchers who are very multidisciplinary and willing to focus on the broader impacts of their work in biology, computing and statistics....'A lot of this is very specific to malaria parasites' says (Olivio Miotto of the Centre for Genomics and Global Health). 'It requires a lot of knowledge about malaria as well as statistics' ".
This is a picture of people applying Knowledge (knowledge of malaria and of statistics) to Big Data in order to make sense of it, and to draw out potential actions.

Big Data does not become Knowledge because of it's size - people have to add Knowledge to the data to make sense of it. The huge data resources of the EBI have to be combined with the specialist knowledge of the staff, and the application of the knowledge is the sense-making step.

Data plus Knowledge = Action.

Data in itself does not lead to action, without the knowledge being applied.  You manage the data itself through data management techniques, and you manage the knowledge itself through knowledge management techniques, and the two together give massively powerful actionable results.  Big Data and KM should work hand in hand, but not be treated as the same thing.

A final word from New Scientist, my clarifications in brackets
"You (ie the knowledgeable scientist) have to work on the translation (of the data) to make it actionable - condensing terabytes into a single sentence. 
This is great fun. It is where science is happening right now - you can really start to understand the genetic drivers behind both rare and complex diseases in a way that was unthinkable four or five years ago".


Chris Collison said...

I agree Nick.
Dave Snowden (I *think* it was Dave) puts it quite succinctly when he says "Our knowledge is what we use to turn data into information".

Nick Milton said...

Indeed, Chris, and knowledge is also what we use to turn information into action (or to put it another way, knowledge is what makes information actionable)

Blog Archive