Doing Big Data – Intelligently
14/12/2016

Last week we blogged about a term used by the Nobel Prize-winning author Daniel Kahneman in his book Thinking, Fast and Slow – WYSIATI (What you see is all there is). It refers to people wanting to see a complex world simplistically, whereas we would advocate that you have to understand (at some level at any rate) the complexity before simplifying – in other words “Simplicity on the far side of complexity”. Totally the opposite of WYSIATI – or “Simplistic on the near side of complexity”.
Many promises of Big Data fall into the area of simplistic on the near side of complexity. We hear Big Data is going to revolutionise our world from retail, financial services etc. through asset management and on into national security. This may be the case with unstructured data (i.e. free text), and possibly with structured data in some circumstances. It is obvious how a retailer might want to analyse all shoppers who purchased a certain washing powder for sensitive shin and run a promotion to also purchase sensitive skin cream and/or clothes made from materials for sensitive skin. Of course, retailers have been doing this for years – just not calling it Big Data.
However, there is a Big Question around Big Data revolutionising the Internet of Things or the Asset Management Industry. With sensor data coming from a myriad of equipment and machinery at the rate of every (typically) 100ms, we are being persuaded that it is necessary to capture every data point as if it has meaning – giving rise to vast so-called “data lakes” of petabytes and zeta bytes or whatever in size, with little hope of analysing it. It may revolutionise sales of Big Data solutions, but does it add value to understanding and analysis?
We came across a world-leading rubber moulding/sealing company in our travels over the past four years or so, and here we found this simplistic on the near side of complexity approach of “just put all the data into one place and run an algorithm to tell us what levers to pull” to get a perfect product. There was little interest in understanding, just “give me an answer”. They were generating large amounts of scrap – and still are.
More recently, we are working with a large transport organisation with many lifts in their buildings. We recognised that every data point did not hold value and that each data point was infected with electrical / mechanical noise that needed removal – in fact, through some intelligent analysis, we reduced the volume of rows by a factor of 400:1. Further analysis allowed us to enter the data into a proprietary time-series analysis platform and we were able to visualise normal behaviour hour by hour over several weeks, spot anomalies, see trends and patterns – all of which have never been seen before.
The Big Question – how would Big Data have provided such insight?
Categories & Tags:
Leave a comment on this post:
You might also like…
Working on your group project? We can help!
When undertaking a group project, typically you'll need to investigate a topic, decide on a methodology for your investigation, gather and collate information and data, share your findings with each other, and then formally report ...
Words matter – a conversational Integrated Vehicle Health Management lexicon
There are many well established barriers to successful digital transformation which prevent full realisation of desired benefits. It is generally recognised that only 30% of digital transformation efforts deliver these results. One of the ...
Library support for new research students
Welcome! We are very excited to welcome you to Cranfield, and we are looking forward to supporting you throughout your research degree. We are always happy to help you – all you need to do ...
Finding full-text Economist articles…
If you’re looking for The Economist, the place to go is ProQuest One Business. Follow these step-by-step instructions to get full-text access. Login here and click on the Publications option at the top, above the ...
New IEEE route to gold open access for UKRI-funded research
You probably know by now that if you publish a paper that acknowledges funding from UKRI (including Innovate UK) it must be made open access immediately upon publication with a CC-BY licence. To remind you, ...
OnePetro subscription ending 5 February
Our access to OnePetro will cease at the beginning of February. This database contains full text documents from professional societies that serve the oil and gas industry. It has experienced a significant drop in usage ...