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Big Data: Does Size Matter?
What is Big Data, and why should you care?Big data knows where you've been and who your friends are. It knows what you like and what makes you angry. It can predict what you'll buy, where you'll be the victim of crime and when you'll have a heart attack. Big data knows you better than you know yourself, or so it claims.But how well do you know big data?You've probably seen the phrase in newspaper headlines, at work in a marketing meeting, or on a fitness-tracking gadget. But can you understand it without being a Silicon Valley nerd who writes computer programs for fun?Yes. Yes, you can.Timandra Harkness writes comedy, not computer code. The only programmes she makes are on the radio. If you can read a newspaper you can read this book.Starting with the basics – what IS data? And what makes it big? – Timandra takes you on a whirlwind tour of how people are using big data from science to smart cities, business to politics, self-quantification to the Internet of Things. Finally, she asks the big questions about where it's taking us; is it too big for its boots, or does it think too small? Are you a data point or a human being? Will this book be full of rhetorical questions? No. It also contains puns, asides, unlikely stories and engaging people, inspiring feats and thought-provoking dilemmas. Leaving you armed and ready to decide what you think about one of the decade's big big data.
321 pages, Kindle Edition
First published August 9, 2016
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Displaying 1 - 30 of 33 reviews
June 6, 2016
I am very wary of books written by people who claim to be taking the wide-eyed outsider's viewpoint, claiming no knowledge of the topic and talking to lots of people in the know - despite the success of Bill Bryson's science book. However, as soon as I came up against Timandra Harkness pointing out that 'data' makes much more sense as a (singular) collective noun for data points, so we should say 'What is data?' rather 'What are data' (something I've been arguing for years), I knew that I was going to enjoy this book.
And despite the rather hard work attempts to be funny in footnotes (especially over number of cups of tea drunk while writing the book), mostly Harkness settles down into telling the story well with a clear amount of knowledge behind her writing (she is, after all, taking a maths degree).
The story she tells is both fascinating and important. It takes in the historical introduction of statistics, Babbage (where she almost manages to talk about Ada King (aka Lovelace) without over-hyping Ada's contribution), the development of computing and most significantly the way dealing with large amounts of data has transformed the way many scientists do their work. Some of the approaches are mind-boggling - for instance the idea of monitoring mosquitos from airships (poor index, by the way - neither mosquitos or airships are in it), detecting the diseases they are spreading and where (and stopping some as they go).
Things start to feel a little more uncomfortable when Harkness takes us onto just how much can be found out about us from our smartphones. While I don't understand her distaste for a husband and wife who can find each other's location with their smartphone - all her reasons why this is bad seem the kind of thing that shouldn't be an issue (and you can always turn your phone off if you really want to be secretive), the systems being trialled that could, for instance, pick up conversations on the street, locate phones and track numberplates really do stray into big brother territory, as do the potential misuses of medical data. Having said that, in the section on misuses, she only interviews activists/people who are suspicious, and has no one giving the positive sides. But it's worth noting when there is so much in the news about the balance between personal secrecy and the attempt to keep on top of terrorists and the like.
Overall, a great mix of plenty of information and views on the potential benefits and dangers of big data. Just occasionally it seems like Harkness is taking the party line - for instance taking the benefits of smart meters for customers for granted, even though they are really far more about making complex tariffs easier to impose for the electricity companies - but overall it's a truly fascinating tour of the data that lies beneath so many of the things we do everyday, from the adverts that pop up on our phones and computers to the customer loyalty cards of supermarkets.
A brilliant guide to our brave new world.
And despite the rather hard work attempts to be funny in footnotes (especially over number of cups of tea drunk while writing the book), mostly Harkness settles down into telling the story well with a clear amount of knowledge behind her writing (she is, after all, taking a maths degree).
The story she tells is both fascinating and important. It takes in the historical introduction of statistics, Babbage (where she almost manages to talk about Ada King (aka Lovelace) without over-hyping Ada's contribution), the development of computing and most significantly the way dealing with large amounts of data has transformed the way many scientists do their work. Some of the approaches are mind-boggling - for instance the idea of monitoring mosquitos from airships (poor index, by the way - neither mosquitos or airships are in it), detecting the diseases they are spreading and where (and stopping some as they go).
Things start to feel a little more uncomfortable when Harkness takes us onto just how much can be found out about us from our smartphones. While I don't understand her distaste for a husband and wife who can find each other's location with their smartphone - all her reasons why this is bad seem the kind of thing that shouldn't be an issue (and you can always turn your phone off if you really want to be secretive), the systems being trialled that could, for instance, pick up conversations on the street, locate phones and track numberplates really do stray into big brother territory, as do the potential misuses of medical data. Having said that, in the section on misuses, she only interviews activists/people who are suspicious, and has no one giving the positive sides. But it's worth noting when there is so much in the news about the balance between personal secrecy and the attempt to keep on top of terrorists and the like.
Overall, a great mix of plenty of information and views on the potential benefits and dangers of big data. Just occasionally it seems like Harkness is taking the party line - for instance taking the benefits of smart meters for customers for granted, even though they are really far more about making complex tariffs easier to impose for the electricity companies - but overall it's a truly fascinating tour of the data that lies beneath so many of the things we do everyday, from the adverts that pop up on our phones and computers to the customer loyalty cards of supermarkets.
A brilliant guide to our brave new world.
February 16, 2017
The humor element (in footnotes) felt very artificial in this book, irritated a lot. Content of maybe 1/5th of this book ended up being of interest to me. Felt the need to finish this reading just because… but was really-really eager to do so.
February 7, 2017
Good - if you want effectively a book length Sunday supplement piece introducing "Big Data" and going through some of the main uses, this is your book. Harkness does the introduction with only a few forays into more 'serious' writing, and I thought it worked well for it. The tone is chatty, with some jokey footnotes (generally wince inducing, gloriously bad, which I liked) The jokes are pared back towards the end, which I think helps. Otherwise, it introduces some of the areas where modern means of harvesting data range from the sci fi to the mundane, and everywhere in between. There may not be much that's revolutionary, but then that's the point - big data is one of those phrases that is bandied around without a lot of wider or detailed understanding. Hint: it's a bit like data, but with more of it.
And, spoiler warning, she does explain how she became Timandra at the end. To my disappointment, it wasn't a portmanteau or her parents, Tim & Andra, or even better, Tim & Ra. And if you don't like that sort of humour, avoid the footnotes...
And, spoiler warning, she does explain how she became Timandra at the end. To my disappointment, it wasn't a portmanteau or her parents, Tim & Andra, or even better, Tim & Ra. And if you don't like that sort of humour, avoid the footnotes...
December 6, 2020
Found this big data to be a tough one to get through. I appreciate the intent to add humor and narrative into an otherwise technical topic, but it just took too long for me to get the key points here. ”Numsense: Data Science for the Laymen” I thought was more effective at giving a high level look into eoffeeent algorithms, but perhaps I just came with the wrong expectations! I wanted a run through of what big data was, a few use cases, some technical jargon about why it’s effective and skills needed to master it, and the future algorithms that may come. This book hits on those no doubt, but it didn’t stick.
September 18, 2016
This is a rather lightweight journalistic introduction to 'big data' but it might be useful to anyone who really has no idea what it is or what it may mean for our society. It probably need not have been so lightweight since Harkness is clearly a sensible, measured and intelligent commentator.
One feels a tentative proposal from someone still learning their way around the field reached a somewhat relaxed and possibly cynical publishing house who wanted to get something 'witty' out into the popular market. It isn't really very witty and the good stuff gets buried by the attempt.
The book does get better from section to section - a weak, over-simple and even obscure history of computerised information (albeit with insights), a central section of case studies that look cobbled together on a travel budget, then some genuinely thoughtful and sensible public policy discussion.
I suspect my mild irritation with the book comes from the lack of helpful editing for Harkness. The attempt to be comedic is largely unfunny, falters and largely disappears after the first section. It is as if she was encouraged to be light hearted when really her intent was more serious than that.
The other irritation is the constant translation of British terms into 'American' for an American audience, betraying straight away the probability that this book quickly became the creature of a publisher intent on American sales. The momentum was lost. It appears to lack authenticity.
Still, these are irritants. Some praise is due as well. Her final section covering surveillance, our identity and our humanity in a big data society is written with intelligence, humanity and a justifiable scepticism about the claims of Big Data and about whether its masters can be trusted.
The point that I take home and readers should take home is that algorithms are not necessarily true reflections of reality and that over-reliance on them can create apparently self-fulfiling prophecies and stereotyping that may create far more problems than they solve in the long run.
My own view for some time now has been that, for all its undoubted beneficial uses, it is a technology, like drones, that contains many dangers and, worse, that the special marketing and governmental interests promoting it are often seeking to manipulate and control us.
Until wise democratic politicians (do they honestly exist any more?) step in and create legislative and regulatory processes that put these special interests back in their box, I would be highly cautious about gifting too much data to a potentially highly manipulative set of actors.
I sense that Harkness, in her reading and work, has come to a similarly cautious view so that it is a shame that the book's rigour and questioning appears so late and that the special interest of a publisher appears to have taken so much control of the narrative. We needed more analysis.
There is a sensible short appendix on how to manage your own privacy which will not say anything startling to the knowledgeable but may assist in what is really required at this time - the political education of the mass of voters about technological change and who owns it.
We are in revolutionary times - new technologies of war and manipulation appear in a population that has become distrustful and cynical. The temptation of elites is to use 'big data' to try and reassert control, failing to realise that their latest wheeze is no more reliable than its input.
The same mindset that once used quantification to try and win wars (we think of Vietnam but also the insane autistic machine logic of the Cold War) is returning with a depressingly adolescent belief in a toy, at least a toy when it comes to describing reality and creating effective policy.
The marketing use of Big Data is relatively more benign but it can be gamed and it operates, like technology in war, as something where the lead lasts only so long unless you throw more and more money at something that offers diminishing returns.
Eventually the mammals (that's us) will take over from the dinosaurs (that's them) ...
November 4, 2016
Both a quite good introduction to the topic of Big Data and describing the potential and risks of said technology. Harkness goes into what it could do (and shouldn't) but also laments that we're just aiming for marginel efficiency increases and not the world-changing ambitions. Furthermore and as a conclusion she insists that we are not just a data point, but "we", or more precisely a you and an I, real humans.
November 16, 2018
First up, I'm a tech and it was really nice to read a relatively non-tech portrayal
It's a rapidly moving subject, but Timandra does well not to get caught up in the very latest buzz, but to use examples to discuss the underlying topics, concerns, challenges etc.
If you're a tech like me, use this to get a perspective from outside of our bubble
If you're not a tech, use this to get a feel for what the hype is all about
It's a rapidly moving subject, but Timandra does well not to get caught up in the very latest buzz, but to use examples to discuss the underlying topics, concerns, challenges etc.
If you're a tech like me, use this to get a perspective from outside of our bubble
If you're not a tech, use this to get a feel for what the hype is all about
November 6, 2016
The balance of humor/comedy and introduction to Big Data fell flat. A few interesting points were raised.
June 15, 2016
I received an advance copy of this for review from NetGalley.com.
Ms. Harkness tackles a huge subject (snark) and handles it well in three parts:
- the history of "big data" ... think census as the biggest driver;
- what it's done for us (or my take might be *to* us) from business and science to ? and politics;
- her own ideas on the future of big data and a prodding to the reader
First, I am impressed with the access she had to some pretty amazing people/places. Large Hadron Collider? How cool! There are more...you'll just have to read the book.
That businesses try to use big data to target customers is no surprise. Big data may shape predictions of trends, or reactions to new marketing, but I really don't know if it can be used to influence individuals (something she addresses in a different context in a later chapter.) Facebook and Amazon seem to use a combination of data mining to achieve their ends. And that particular link is creepy...seconds after looking at something on Amazon, my wife gets the exact item suggested when she switches over to Facebook. I don't because I block ads, and on my devices where I can't, I don't go to Amazon. But I do get offers based on questionable data...I live in Texas. so I must be interested in guns, right? I rant about FoxNews, so I must want to see more of it, right? That would be wrong... Big data may be the masses of searches and purchases, but to truly be effective, there must be a component of small data to tailor correctly to the individual.
Ms. Harkness addresses the biggest dataset, that being human language, in a bit about an artificial intelligence truly understanding language. I agree with her skepticism about a computer understanding the language, but I also thought that communication is not necessarily the same as understanding. A self-learning database and front end can continually ask "I didn't get that...?" and given sufficient storage and processing, someday pass Turing's test. She notes "Irony is one of these things that it's hard for a computer to get." Which is why Ray Kurzweil's singularity is probably a lot farther out than he thinks. Or not. An AI will think differently (it has to) and not likely need the myriad nuances of human language. More on AI, she talks about virtual butlers prompting us to pack for a trip, or tying various activities and predicting something wholly inappropriate that a human assistant would clearly not do. Letting Big Sister plan our lives is too much for me.
On science, she brilliantly distills into commonspeak the processes required to parse an unimaginable amount of data from a nanosecond collision of very high energy particles. The transition from "large data" - collecting lots of a single or limited type of information to be used in the originally envisioned context - to "big data" - collecting all the things that can be thought of and more to determine relationships not anticipated - is one of the key changes in big data in science. inexpensive storage makes it possible to save nearly everything...to be examined later. I was surprised that in the book she only mentions briefly weather prediction. That's a prime example of big data being used to make specific (statistically close, that is) near term predictions, with the goal of extending the window out as more data and analysis become available.
I was fascinated by the chapter on politics, and political parties in Britain identifying individual swing voters and targeting them with personalized letters or messages. I don't know if people here read the crap sent, but I know I don't. (Nor do I listen to specifics said in debates or stump speeches...one must put into context whether whatever is said can even come about...) When she cites a website that urges voters to check out voting records, look at speeches, even ask the representatives direct questions, she asks the question "So can big data help us make properly informed decisions about who to vote for?" That fell flat with me. I think that is small data, because answers must be combined with evaluations of effectiveness.
She also mentions postcodes (zip codes for us USA readers) making it easy to put people into groups according to where they live. Several times, and in several contexts, such as postcodes correlating people to locations with a high incidence of say, lung cancer. That doesn't take into account people moving. Maybe in Britain they don't move as easily or as frequently as in the US. Of course, there are many parochial non-movers here, but it just stood out to me each time she brought it up that to be of any value, people would have to be microchipped or something.
I liked her citing the twisted words big data users (or I note, anybody with an agenda) can spew. The Cancer Research UK said studies showed "those who ate the most processed meat had around a 17 per cent higher risk of bowel cancer." But the risk is relative, as normal bowel cancer rates are 6%, so that increase would only change the risk to 6.5%. I ran across that some years ago when a vendor claimed to decrease inefficiency by 30%, conveniently neglecting to mention that the original efficiency was already a substantial 97%, so that 30% reduction in inefficiency only resulted in an increase of 1% efficiency! One might surmise that I never got a callback after I asked the question.
Ms. Harkness, in addition to being a journalist, is also a comedian, and she infuses humor throughout. She made me laugh when she said big data made better food crops, medicine and even better Guinness. I am of the opinion that Guinness is awful, so...my note was {snort}! And when she was talking about the first American census created as a way to share "out the burden of the War of Independence", she noted that "[b]oth representation and taxation would be allocated according to population."
I did have a few quibbling points... She talks about Laplace's confidence that science and mathematics could (eventually) explain everything - Laplace's Demon - and she quotes Laplace (in English): "We may regard the present state of the universe as the effect of its past and the cause of its future." but goes on to paraphrase "If everything in the future is determined by what happened in the past, that leaves no room for us to make choices." Unless I misunderstand her wording, that isn't what Laplace was saying...he said the *present* state of the universe is a product of its past, not that a future is determined from a past. I don't think Laplace was excluding the human free will, or random factors.
A couple of quibbling notes on the structure and presentation of the book:
- Formatting is different than I've been used to the past fifty years. When quoting someone, Ms. Harkness uses a single quote mark to open the quote...having read British authors, that's not new to me, but what was new was not leading following paragraphs with another quote mark. Instead, the only closing mark is at the end of the quote, sometimes several paragraphs, and even another page away. While it's not hard to break that code, it is more confusing than necessary to keep track of which is her voice and which is her interviewee.
- My copy had no index, but it did have a placeholder. I did not see a list of references or a similar placeholder. While I understand Ms. Harkness is taking a more conversational approach in her narrative (she has many footnotes, but most are slight clarifications/explanations, or humor), she quotes a number of sources without providing references. This is me writing this, and that may not be important to other readers, but I sometimes like to dig deeper. In particular, she quoted an activist in Oakland, on the use of a Domain Awareness Center, referring to a white paper from the "Monterey Naval Academy". The quote was in quote (I'd say "quotes" to mean quotation marks if this were not a UK book...) to indicate that it was a quote, and yet I happen to know, as would most people, that the "Naval Academy" is actually the Naval Postgraduate School. In Monterrey.
- I would have liked to be able to copy text in this review, but the permissions forbade it. As such, I'm reduced to typing quotes and I admit little patience for that.
I liked this nugget:
"How can you take a dataset and repurpose it and do something interesting with it?" Her example was using Major League Baseball data to determine if left-handed people live longer than right-handed. She does note the limitation of the dataset being gender one-sided, but that *is* an interesting take.
Ms. Harkness tackles a huge subject (snark) and handles it well in three parts:
- the history of "big data" ... think census as the biggest driver;
- what it's done for us (or my take might be *to* us) from business and science to ? and politics;
- her own ideas on the future of big data and a prodding to the reader
First, I am impressed with the access she had to some pretty amazing people/places. Large Hadron Collider? How cool! There are more...you'll just have to read the book.
That businesses try to use big data to target customers is no surprise. Big data may shape predictions of trends, or reactions to new marketing, but I really don't know if it can be used to influence individuals (something she addresses in a different context in a later chapter.) Facebook and Amazon seem to use a combination of data mining to achieve their ends. And that particular link is creepy...seconds after looking at something on Amazon, my wife gets the exact item suggested when she switches over to Facebook. I don't because I block ads, and on my devices where I can't, I don't go to Amazon. But I do get offers based on questionable data...I live in Texas. so I must be interested in guns, right? I rant about FoxNews, so I must want to see more of it, right? That would be wrong... Big data may be the masses of searches and purchases, but to truly be effective, there must be a component of small data to tailor correctly to the individual.
Ms. Harkness addresses the biggest dataset, that being human language, in a bit about an artificial intelligence truly understanding language. I agree with her skepticism about a computer understanding the language, but I also thought that communication is not necessarily the same as understanding. A self-learning database and front end can continually ask "I didn't get that...?" and given sufficient storage and processing, someday pass Turing's test. She notes "Irony is one of these things that it's hard for a computer to get." Which is why Ray Kurzweil's singularity is probably a lot farther out than he thinks. Or not. An AI will think differently (it has to) and not likely need the myriad nuances of human language. More on AI, she talks about virtual butlers prompting us to pack for a trip, or tying various activities and predicting something wholly inappropriate that a human assistant would clearly not do. Letting Big Sister plan our lives is too much for me.
On science, she brilliantly distills into commonspeak the processes required to parse an unimaginable amount of data from a nanosecond collision of very high energy particles. The transition from "large data" - collecting lots of a single or limited type of information to be used in the originally envisioned context - to "big data" - collecting all the things that can be thought of and more to determine relationships not anticipated - is one of the key changes in big data in science. inexpensive storage makes it possible to save nearly everything...to be examined later. I was surprised that in the book she only mentions briefly weather prediction. That's a prime example of big data being used to make specific (statistically close, that is) near term predictions, with the goal of extending the window out as more data and analysis become available.
I was fascinated by the chapter on politics, and political parties in Britain identifying individual swing voters and targeting them with personalized letters or messages. I don't know if people here read the crap sent, but I know I don't. (Nor do I listen to specifics said in debates or stump speeches...one must put into context whether whatever is said can even come about...) When she cites a website that urges voters to check out voting records, look at speeches, even ask the representatives direct questions, she asks the question "So can big data help us make properly informed decisions about who to vote for?" That fell flat with me. I think that is small data, because answers must be combined with evaluations of effectiveness.
She also mentions postcodes (zip codes for us USA readers) making it easy to put people into groups according to where they live. Several times, and in several contexts, such as postcodes correlating people to locations with a high incidence of say, lung cancer. That doesn't take into account people moving. Maybe in Britain they don't move as easily or as frequently as in the US. Of course, there are many parochial non-movers here, but it just stood out to me each time she brought it up that to be of any value, people would have to be microchipped or something.
I liked her citing the twisted words big data users (or I note, anybody with an agenda) can spew. The Cancer Research UK said studies showed "those who ate the most processed meat had around a 17 per cent higher risk of bowel cancer." But the risk is relative, as normal bowel cancer rates are 6%, so that increase would only change the risk to 6.5%. I ran across that some years ago when a vendor claimed to decrease inefficiency by 30%, conveniently neglecting to mention that the original efficiency was already a substantial 97%, so that 30% reduction in inefficiency only resulted in an increase of 1% efficiency! One might surmise that I never got a callback after I asked the question.
Ms. Harkness, in addition to being a journalist, is also a comedian, and she infuses humor throughout. She made me laugh when she said big data made better food crops, medicine and even better Guinness. I am of the opinion that Guinness is awful, so...my note was {snort}! And when she was talking about the first American census created as a way to share "out the burden of the War of Independence", she noted that "[b]oth representation and taxation would be allocated according to population."
I did have a few quibbling points... She talks about Laplace's confidence that science and mathematics could (eventually) explain everything - Laplace's Demon - and she quotes Laplace (in English): "We may regard the present state of the universe as the effect of its past and the cause of its future." but goes on to paraphrase "If everything in the future is determined by what happened in the past, that leaves no room for us to make choices." Unless I misunderstand her wording, that isn't what Laplace was saying...he said the *present* state of the universe is a product of its past, not that a future is determined from a past. I don't think Laplace was excluding the human free will, or random factors.
A couple of quibbling notes on the structure and presentation of the book:
- Formatting is different than I've been used to the past fifty years. When quoting someone, Ms. Harkness uses a single quote mark to open the quote...having read British authors, that's not new to me, but what was new was not leading following paragraphs with another quote mark. Instead, the only closing mark is at the end of the quote, sometimes several paragraphs, and even another page away. While it's not hard to break that code, it is more confusing than necessary to keep track of which is her voice and which is her interviewee.
- My copy had no index, but it did have a placeholder. I did not see a list of references or a similar placeholder. While I understand Ms. Harkness is taking a more conversational approach in her narrative (she has many footnotes, but most are slight clarifications/explanations, or humor), she quotes a number of sources without providing references. This is me writing this, and that may not be important to other readers, but I sometimes like to dig deeper. In particular, she quoted an activist in Oakland, on the use of a Domain Awareness Center, referring to a white paper from the "Monterey Naval Academy". The quote was in quote (I'd say "quotes" to mean quotation marks if this were not a UK book...) to indicate that it was a quote, and yet I happen to know, as would most people, that the "Naval Academy" is actually the Naval Postgraduate School. In Monterrey.
- I would have liked to be able to copy text in this review, but the permissions forbade it. As such, I'm reduced to typing quotes and I admit little patience for that.
I liked this nugget:
"How can you take a dataset and repurpose it and do something interesting with it?" Her example was using Major League Baseball data to determine if left-handed people live longer than right-handed. She does note the limitation of the dataset being gender one-sided, but that *is* an interesting take.
February 23, 2020
British humor+a pretty broad though selective introduction to data and big data. I thought that Timandra did a great job (and probably something you don't always find in big data books) looking a little further back at how data has been collected and how it helped. She made the point several times that deducing and inferring causes and predictions seems to be a challenge not only for us today with a lot of data, but even earlier on when looking at the plague in Britain. It's definitely worth reading, especially if you are looking for a light overview of data from small to big.
Fav quotes:
"If everything in the future is determined by what happened in the past, that leaves no room for us to make choices." [in regards to Laplace's Demon, and frequently comes up in the book to make the point that algorithms are only based on historical data - our choices can still produce new and unpredictable things]
"Only an electorate incapable of rational thought, impervious to common sense, context and conflicting arguments could be swayed against its will by online adverts, however well-aimed." [in regards to the use of data in political campaigns]
Fav quotes:
"If everything in the future is determined by what happened in the past, that leaves no room for us to make choices." [in regards to Laplace's Demon, and frequently comes up in the book to make the point that algorithms are only based on historical data - our choices can still produce new and unpredictable things]
"Only an electorate incapable of rational thought, impervious to common sense, context and conflicting arguments could be swayed against its will by online adverts, however well-aimed." [in regards to the use of data in political campaigns]
March 9, 2022
All in all not a very good read. Clusters of facts about data and its collection and its role in society without much of a connecting thread other than that they're all big data related. Many attempts at humour that probably could have stayed in the author's brain. The smattering of interviews through the book feel like a collection of wasted opportunities (the author got to take a look into the belly of the CERN experiment but the main takeaway for her was "lots of data, lots of cables everywhere"). The one positive is that the novel is quite UK-centric so it gives some good background into the overlooked side of data politics and policies in that country. I learned far more and gained far more insight into the complexity and nuance of big data from the book The Alignment Problem: Machine Learning and Human Values, a book which I would strongly strongly suggest over this.
December 25, 2017
I wanted to read a fun introduction to big data before I got started on a course in bioinformatics. This book was very broad, taught me some enjoyable facts (for instance, the idea of using punched cards to program computers came from looms which used punched paper to encode patterns), and covered some of the interesting ethical issues regarding surveillance. The only downside is that the humour in this book sometimes fell flat for me; at one point the author jokes that Alan Turing 'clearly never had children', which seemed in poor taste considering that Turing was chemically castrated for homosexuality, and that this abuse by the state contributed to his death. I'm almost certain this wasn't what the author was thinking when she wrote the joke, but it still made me cringe pretty hard. Overall however, I would recommend this book as an easy-to-read introduction to a fast-moving field.
December 27, 2023
Well written, funny and puts in simple terms what Big Data means to the world, research and an individual personally. Quite interesting glance at history and how the data was collected in the old times. Resonated with the approach which I saw in training for data analysts - "look around and think what data you see" - author really gave a good demonstration on that. And also there are some extremely interesting cases of data collection and usage for innovative technology research, which made me wonder how the world/technology will be shaped by usage of Big Data in couple of years (and its already been happening for decades...). Enjoyed reading it a lot.
September 25, 2019
The noted Israeli historian Y.N. Harari once speculated that humans are merely a sum of their biochemical algorithms & thus life consist of nothing more, or less, than data processing. This is, of course, an anathema to many of us whom subscribe to the belief propagated by the Judaeo-Christianity worldview & unwittingly by our parents in each cuddle ("you're so special, baby!"), that humanity is exceptional in its individual parts. It is safe to say that Timandra Harkness harbors her opinion somewhat quite to the left of this worldview with a dash of humor.
Read
March 9, 2022In a casual writing manner mixed with humorous jokes, the author introduces the purpose of statistics behind all the technology driving the business, science, and social operations of our world. Readers will learn that statistics or algorithms can not be true representations of reality and can serve as more negative influence on decision making when over relying on them. There are also deeper insights on the hype and fascinating uses of these data statistics which young adult readers can learn to appreciate and analyze the potential dangers to society.
July 11, 2017
An interesting book, anyone who listens to 'More or less' on radio 4 would like this. Lots of information about what big data is, who controls it etc. I listened to a lot of it in the car and the sat nav talked over a lot of it which did not help. The author makes what could be a dry subject entertaining.
May 11, 2017
An insightful introductory look at Big Data and what it means for us and our privacy. Useful to get you thinking about issues you might not have thought about before, particularly the darker side of our connected lifestyle. An enjoyable read.
March 20, 2021
‘Big data’ is undoubtedly the landmark of our generation, but as with everything, should be treated with circumspection. Blind trust in data without careful considerations of their underlying assumptions is a recipe for a data-driven downfall.
May 1, 2025
Today people are constantly talking about overhype Generative AI rather than an old technology called “big data”. I think this book helps me gain fundamental knowledge of big data and how it is often used in real-life scenarios.
February 20, 2018
To me, there is nothing in this book. Nothing new. There is no solid idea or claim. I thought it was kind of scientific book, I end up reading something like from online news. Disappointing
May 5, 2018
I enjoyed this book.
June 12, 2018
Quick read. Gives pros and cons of big data.
April 11, 2019
Como já atuo na área achei um pouco básico, mas é um excelente livro para quem quer entender o que podemos conseguir através de big data.
August 26, 2019
Very interesting and pleasant to read... absolutely suggested if you are interested in a non technical introduction to big data
July 10, 2020
A very "pop-Science" approach with a straining "banter".. overall a book that does little justice to the engaging subject this could have been.
August 31, 2020
I had to skip few paragraphs in almost all chapters to complete the book.
July 25, 2023
Can't get past the jovial way the author discussed terrible crimes. The statistics are valid, the tone is, well, utterly tone deaf.
April 30, 2018
A nice light read which opens up the world of big data to people who have little knowledge of it. It starts to provide an explanation of how things work, but with perhaps not enough detail, so the book only confirms people’s suspicions on how they are being tracked rather than fully explain.
The inevitable dystopian future is there in many chapters but I enjoyed sone of other big data use explanations such as the one she opened up with.
A light read, went on a little too long for its lightness, but enjoyable nevertheless
The inevitable dystopian future is there in many chapters but I enjoyed sone of other big data use explanations such as the one she opened up with.
A light read, went on a little too long for its lightness, but enjoyable nevertheless
January 3, 2020
A bit too chatty in style for my liking. Could have cut out the waffle. On the other hand, some interesting stories and points of view about modern automated data collection and processing.
July 9, 2016
First of all, thanks to Bloomsbury India for sending a review copy of the book to me.
If you are a working professional (at a corporate/startup) you must have realized that the term 'Big Data' has almost become ubiquitous. If you aren't in this sector, then too you must have noticed something peculiar- you visit an e-commerce website and very soon you are seeing the ads for the products that your browsed through almost everywhere on internet. Or, you just tweeted a few times about a particular commodity and there you go bombarded with ads regarding that. That's 'Big Data' coming into play!
I was a bit skeptical when I started this book, because it mentions that the author is a comedian! You don't expect a comedian to write on a somewhat technical topic but after a little bit of research on internet I found more about Timandra Harkness and realized that she is 'not just a comedian'
The author has done a commendable research (especially the historical information related to Statistics is just amazing) in putting down this book. One the history of Big data is dealt with, the book delves into how Big Data is changing (or should I say 'has already changed' ?) our day-to-day life. The books talks about how AI (Artifical Intelligence) is nothing but a product of Big Data and also how politicians can actually influence us to vote for them during Elections by getting to know a few details about us accurately.
Whenever we discuss Big Data, the issue of 'Breach of Privacy' is a tacit point of discussion and the author discussed how too much of Data analysis usage can actually act as a "Big Brother" for the common man.
All in all, the book started on an extremely interesting note as far as the historical aspect of Big Dats is concerned, perfect enough for a layman to absorb and understand the concepts. But the author all of a sudden gets too 'technical' in the chapter 'Thinking Machines' which you might find a tough nut to crack (hence, 3 stars). Having said that, the book is still an eye-opener and an enriching account.(I am using the word 'eye-opener' because you will realize how much you are 'watched upon' and how much your activities are being 'measured' and 'quantified')
A good read.
If you are a working professional (at a corporate/startup) you must have realized that the term 'Big Data' has almost become ubiquitous. If you aren't in this sector, then too you must have noticed something peculiar- you visit an e-commerce website and very soon you are seeing the ads for the products that your browsed through almost everywhere on internet. Or, you just tweeted a few times about a particular commodity and there you go bombarded with ads regarding that. That's 'Big Data' coming into play!
I was a bit skeptical when I started this book, because it mentions that the author is a comedian! You don't expect a comedian to write on a somewhat technical topic but after a little bit of research on internet I found more about Timandra Harkness and realized that she is 'not just a comedian'
The author has done a commendable research (especially the historical information related to Statistics is just amazing) in putting down this book. One the history of Big data is dealt with, the book delves into how Big Data is changing (or should I say 'has already changed' ?) our day-to-day life. The books talks about how AI (Artifical Intelligence) is nothing but a product of Big Data and also how politicians can actually influence us to vote for them during Elections by getting to know a few details about us accurately.
Whenever we discuss Big Data, the issue of 'Breach of Privacy' is a tacit point of discussion and the author discussed how too much of Data analysis usage can actually act as a "Big Brother" for the common man.
All in all, the book started on an extremely interesting note as far as the historical aspect of Big Dats is concerned, perfect enough for a layman to absorb and understand the concepts. But the author all of a sudden gets too 'technical' in the chapter 'Thinking Machines' which you might find a tough nut to crack (hence, 3 stars). Having said that, the book is still an eye-opener and an enriching account.(I am using the word 'eye-opener' because you will realize how much you are 'watched upon' and how much your activities are being 'measured' and 'quantified')
A good read.
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