Big data is always hungry for more
Acouple of months ago I agreed to give a presentation at the Asia Pacific Centre for Food Integrity Conference — the brainchild of the energetic Dr Helen Darling. In a fit of creativity, I named my talk: ‘‘Eating numbers: the role of data in the food chain.’’ This sounded suitably catchy and I had great ideas at the time of what I would include, didn’t write anything down and forgot all about the presentation until this week came around.
Seeing the upcoming event in my calendar, I found the title I was so proud of, dropped my head in my hands, and emailed a colleague asking — ‘‘what was I thinking?’’ Said colleague is a computational modeller — a fancy term for someone who is mighty fine with bigdata sets — and is much more suited to giving this presentation than me. She has now rescued me with some fabulous slides to make up the bulk of my presentation. Now all I have to do is find some additional vignettes to add colour to my presentation. And this, dear reader, is where you become the beneficiary as I practise my colourful vignettes.
Did you know if you were to undertake bigdata analysis of recipes online, you would find the most common ingredient in 5star rated recipes is bacon? Bacon is, of course, a versatile ingredient and we are used to having bacon star in soups and sandwiches, but now it is inundating desserts, cocktails and even clothing! Bizarre to say the least — the analysts noted there are several other ingredients that boost recipe ratings: cream cheese, avocado and strawberries . . . who would have known without bigdata analysis?
Did you know that Kaggle (a data science company) found, through analysis of airflight booking data, the best way to tell if a person is likely to make their flight is if he or she has preordered a vegetarian meal? Their explanation of this was that the psychology of going to the effort to personalise your trip makes you more likely to get to the plane on time. I thought it was probably more indicative of the level of organisation a vegetarian needs to have just to live — they can’t simply grab sausages and fling them on the barbie when unexpected visitors turn up.
And we couldn’t have a food and big data story without McDonald’s. Did you know they sell 75 burgers every second of the day? They use big data analysis to improve their systems and consistency of product. Starbucks is another example, they keep a record of what their customers order so they can provide them with exciting offers and suggestions on side dishes allowing for a ‘‘personalised experience’’. Yes, dear reader, we are about to enter an avalanche of personalised marketing campaigns based on what we buy from supermarkets, view on social media and what our statistics ‘‘say about us’’.
Quirky vignettes aside, more than 90% of all the data in the world today has been generated in the past two years. To understand the exponential rate of data volume growth, the information we could generate from the beginning of time until 2003 can now be created in less than two days. Data will play an increasingly significant role in personalising what we eat and how we are marketed to, reducing food wastage, guiding farming and food production decisions and ensuring product traceability.
A friend of mine said to me recently, ‘‘my daughter is really good at maths, but I am not sure what she can do with that and whether I should encourage her in that direction’’. I just about fell off my perch in my enthusiasm for the opportunities for her daughter’s future. To quote Hal Varian, from Google: ‘‘I keep saying that the sexy job in the next 10 years will be statisticians, and I’m not kidding.’’ Is that a more frightening thought than McDonald’s selling 75 burgers a second? Probably not — those of you with mathematical brains — go hard, it’s your time to shine!
❛ More than 90% of all the data in the world today has been generated in the past two years❜