Big Data, Big Dupe: A little book about a big bunch of nonsense

I am a big fan of Stephen and is beautiful visualisations. I think this book serves as a good counterpoint to the amount of marketing disguised as "big data". It raises several critical and important questions organisations should ask themselves before spending millions on the new initiative.I do not however agree that all of Big Data is pure marketing hype. When you strip away the layers there is some significant changes that have happened since the introduction of Hadoop and cloud based storage and processing which Stephen fails to acknowledge. For example:- Cost of storage has plummeted and it has brought analytical horsepower (if not capability) within the reaches of much smaller organisations. Not only those who could afford the "big iron" of the past.- Availability of curated public data-sets has dramatically increased allowing forward thinking organisations to use these in combination with internal data for better "data sense-making" (Stephen's term)- There has been an explosion in interest, tutorials and people willing to learn more - so the marketing hype has helped, though as usual it has over-promised.- One more nuanced area where the "domain expertise" is being challenged in in the deep learning space - to be fair this is still on the cutting edge of science with few organisations having the skill-sets to fully utilise this. Here learning algorithms have surpassed human capabilities in several areas (Go as well as retro games are the better known examples). And these have been driven more by computing power and the "proto-science" of deep learning than necessarily experts in the game.I would recommend it for people who like to have the fully perspective of what topics mean and are able to hold both the promise and cynicism necessary to navigate the world of big data.

I found this book to provide very interesting insights regarding how big data can be used in a useful way in today's world. Big data is not a panacea but rather a good tool, in the same way as data has always been.

The author disagrees with calling Big Data “Big” because there is no consensus on the term and it is, to some degree, marketing hype. That’s pretty much the entirety of the book.

This is a wonderful book that in a sense debunks the whole "big data" catch word. If you are a manager type this is a must read!

Hans Christian Andersen's "The Emperor's New Clothes" tells the story of two weavers who promised to make the emperor a new suit of special clothes, worthy only of an Emperor.They announced that the cloths are so special, that they are completely invisible to those who are unfit, stupid, or incompetent.In fact, there were no clothes at all, and when the emperor went on a public parade in front of his people wearing his new "special clothes", no one dared to challange it, afraid they will be seen as 'unfit, stupid, or incompetent'.It took an innocent child to cry out: "The Emperor is naked!!!" to make everyone realize how stupid they really were.Big data are the Emperor's cloths, and Stephen Few is the child in this story, exposing the falsity of 'big data' for what it really is - a very clever and successful marketing campaign contrived to fill the pockets of technology vendors and their collaborators, robbing organizations of the real value that the huge amounts of money and resources spent on this fad, could have been used for.I am a data professional, with over 25 years of experience in IT.I must confess that I was one of those who kept quiet, knowing that the Emperor is naked.I didn't praise big data, knowing that it was false, but I also didn't fight it.Every time I spoke my mind, I got such vehemently negative responses that I figured the fight isn't worth it.Instead, I just went on with my business, avoiding the subject altogether, hoping the fad will pass away eventually, as it has no real value or substance. Human character has proved me wrong once more.The fad is as strong today, 10 years later, as ever, and has managed to inflict substantial damage.Reading Stephen's well articulated case, made me realize I can't really stand by anymore as this is too important to ignore and push aside.Do yourself and your organization a huge favor - read this book, and buy a few copies to give your data colleagues, executives, or anyone that has some stake in data, and still has some sense left.

At least, not much that you wouldn't already know. Machine Learning is a marketing term that fills people with hope. The machines will tell us how to run our business; machine learning will give us incredible, actionable insights we didn't have; and so on. Alas, it's all about statistics, and having ten million numbers to crunch per second isn't really any better than using randomized samples and calculating confidence intervals--something you could have, and should have, been doing anyway.One way to pick up on the con is to watch for future-tense words, for example, AI 'will' give us actionable insights, machine learning 'will' change everything, experts 'expect' radical progress, and and so on. This means it hasn't happened yet.In my industry, such machine learning would reveal that the busiest times in the clinic would be Thursday afternoons, or the most inpatients would be in January. But we already knew that, and even if not, we wouldn't need to spend millions on deep-diving data software to find out.Like some other reviewers, I found the Trump comments and a few other things distracting. Like good visual design, good writing should never call attention to the author or distract from the message. But overlook that and get this book. If you've been skeptical of all the promises and hyperbole of this new coming golden age of Big Data, you are not alone!

Amen.It's essentially an article. Stephen Few chose to make it short and concise. I think it was a wise move. Make sure you get it and spend the 45 - 60 min it takes to read it.The Emperor's New Clothes.Same, same but different.Sensemaking and evidence-based decisions is what's needed, not empty trends, creating waste.

Hear hear! I agree with all, with one exception: Author Stephen Few's devotion to causation (Chapter 5), which doesn't scan for me. Causation does matter and determining it is indeed the whole point of science in general. But that does not mean that, when a correlation is established, we cannot find value in acting on it. Doing so is generally much easier than also establishing causation. With found data (the majority of "organic" organizational data) we can establish correlations; for causation, we need experimental design: much more costly and challenging.I made light of -- and criticized -- the term "big data" on an episode of The Dr. Data Show. Turns out we had overlapping points (I hadn't read his book yet -- you can find that episode online, if interested).Eric Siegel, Ph.D.Founder, Predictive Analytics WorldAuthor, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

In his latest book, Stephen Few states what few are willing to say out loud - "Big Data" is nothing more than a marketing sham. From the initial chapter highlighting how no one can even adequately define "Big Data", the tone of this book is clear; the emperor has no clothes and we need to wake up. For any of you who work with data sets on a regular basis, this book is a must read. Save your companies millions of dollars by not chasing a fad. Focus on what's real - DATA. Not toys, not tools, not hype. Nothing has changed, data is data is data.I truly enjoyed his highlighting of the contradictory messages other authors and 'data experts' have published. As a data professional myself with over two decades of experience, this book is a treat and a validation. No matter what new buzzwords marketing comes up with, Few reminds us that it's people, human insight, and focus on the right data (regardless of the volume or velocity) that counts.Follow the advice given in this book and free yourself from the hype.For the tl;dr crowd: Read this book and save yourself a ton of headaches!!

I have always enjoyed reading Stephen Few's works, and I hope this short book makes it into the hands of decision-makers everywhere just in time for their budget meetings. Few methodically explains the various claims of Big Data as some new paradigm and demonstrates why the claims (which are largely marketing-based rather than technology-based) are false. I can't imagine the waste of time and money that this buzz word has cost over the past decade. The first four chapters are good at explaining why the emperor "Big Data" has no clothes--badly defined, not really different in its nature from data we've always had and used, hyped by marketing to drive sales, and providing an unfortunate distraction to those who want what the Big Data snake oil sales people promise--actionable insights from data. I've believed as much for the past several years. But it was the last two chapters that got me: chapter five discusses how those on the Big Data bandwagon are in some cases proposing that we take a huge step backwards in how we interpret data--ideas that are not based on science and that could lead to very dangerous outcomes. Chapter 6 discusses the opportunities for misusing the large amounts of personal data that are being gathered by so many agencies in our "gather data now, ask questions later" climate. I have largely ignored "Big Data" claims as merely specious. Those last two chapters suggest that ignoring Big Data claims and not wasting our money on them may not be enough--we need to be on our guard for what Greeks might be hiding inside the Big Trojan Horse that is the Big Data movement.I highly recommend this book for IT decision-makers, not just those in the trenches of "data sensemaking".

Really enjoyed this book and it makes some fantastic points. Really, when you look at things what we are doing today in data analytics are the same things that have always been done in terms of the outcomes desired by business. None of that has changed in 20+ years. But, every so often we come up with some technological "silver bullet" that people claim will solve the worlds problems. It won't. There are no silver bullets as Stephen Few so adroitly demonstrates. I'm happy to say that I've always been incredibly skeptical of "big data" and have always known there was something not right about it. Now, thanks to Stephen, I know that my gut was correct.

This may be the best book ever written on the hype that infects the data industry. Although the title focuses on the current hype of "Big Data", the book itself is a marvelous guide to all data professionals to help us avoid the endless stream of data fads. Stephen properly focus on the quality of data and the skills necessary to do data. A must read.

He nailed it.Big data will eventually be boiled down to pure data (as Gartner is doing now)Risks of usage of Advanced Analytics without adequate education are outlined nicely.Stephen, time is ripe for the next book, this time on AI.

A concentrated dose of sense making, as the author puts it. No golden fish, no magic rod to perform data analytics out of nothing. Hard work, sound subject knowledge cannot be replaced by some software old tricks with a new brand name. True, advertising is the soul of commerce, but what about truth in branding?An exceptional demythization of Big Data. Congratulations, Stephen Few for telling as it is. I enjoyed every page of this little book.

Another gem from Stephen Few. He doesn't mince his words and gets right to the heart of the matter. The book is written in his usual style, easy to read and backed up by evidence. Let me assure you Big Data is alive and well in Australia. Just take a look through the plethora of job vacancies for data analysts. If you go under the covers, they are not recruiting subject matter experts with data sensemaking skills, but rather looking to place people that are employed to play second fiddle to computer algorhythm driven data discovery.