Data has been the focal point of technology, machine-learning and artificial intelligence for decades now.
While technology has evolved, so has the need for data. As per estimates from American multinational corporation Computer Sciences, we are expected to consume 44 times more data in 2020 than we did a decade ago.
This is also evident from the fact that the vocabulary for data has changed over the years.
While we would recognise terms like ‘gigabyte’ and ‘terabyte’, the millennials are now talking about ‘petabytes’ and ‘zettabytes’.
Data is certainly becoming too big to handle—estimates put it at 35 ZB (one zettabyte is equal to a million terabytes) by 2020.
However, its handlers and machines have also become smarter in collating, linking and deciphering the large datasets.
Timandra Harkness in her book Big Data: Does Size Matter? defines this very relationship between the need for growing data and the use of machines.
Having a journalistic background—Harkness is a writer, comedian and broadcaster, having written for The Sunday Times, The Telegraph, Wired, etc—she doesn’t delve much into the science of big data, but presents a historical and anecdotal account of the history of data, its evolution to big data and its use by companies.
The book is divided into three sections and starts with a reference to the earliest recording of data on a wolf bone. As Harkness builds her argument, she presents her own definition of the concept.
She uses the word ‘DATA’ as an acronym consisting of four key elements: dimension, automatic, timely and artificial intelligence.
The book takes a historical journey through France, Switzerland and England to present a tell-tale account of data recording, from the birth-death records of churches to the evolution of census.
It also highlights the accounts of statisticians and researchers who have contributed to changes in data collation.
The book goes from defining John Arbuthnot’s works to Pierre-Simon Laplace’s demons, while also accounting for the use of the concept of ‘average man’ by Adolphe Quetelet.
But Harkness doesn’t stop there. She also takes into account the progression of machines from Charles Babbage and Lady Lovelace to the idea of machine intelligence by Alan Turing.
Harkness doesn’t also miss out on the story of IBM and Herman Hollerith’s card-punching invention.
Big Data also delves into the issue of use of data for business, science, politics and society, and that, too, in a big way.
It draws from the experience of professionals working in the fields to define how big data has changed their industries.
The author presents enough anecdotes—from customer intelligence, mosquito tracking and genetic editing to mapping, crime perception and social media democracies—to demonstrate the effects of data on our daily lives.
Ultimately, she tries to define humanity amidst this sea of big data while dealing with the questions of privacy and intrusiveness.
She puts out the limitations of big data—in not thinking big enough to change individual approaches—but also leaves the reader with a pertinent question as to whether we are human beings or data points.
Though the book is a fun read for those who don’t want to embroil themselves in the tech jargon of big data, the anecdotes stretch a bit too far in certain cases, making the book lose its plot at times.
Also, the book focuses too much on the history of data and misses out on certain issues like singularity, the fate of big data and, most importantly, the fate of humans as big data becomes bigger.
But despite its flaws, Harkness keeps you engaged with her wit and knowledge of the field. She leads you into a maze of discoveries and innovations, presenting solutions to certain problems, while also highlighting the ill-effects of a data-driven world.
Harkness says, “My hope is that they provoke you enough to go out, start a conversation and forge your own ideas about big data, and what it could mean for our future.” And she does just that by putting forth the right questions.
Harkness decides that we are human beings and not data points, but in this age of technology where we are connected at all times via our smartphones, smartwatches and fitness bands, there is a distinct possibility to be both.
By deciding to live out our lives on social networks and having the convenience of shopping from home, we have opened our world to machines and their intelligence. Some may fret over the idea of being tracked and analysed, but that is the cost of staying connected.