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"The world of Big Data is one of pervasive data collection and aggressive analytics. Some see the future and cheer it on; others rebel. Behind it all lurks a question most of us are asking \u2014 does it really matter? I had a chance to find out recently, as I got to see what Acxiom, a large-scale commercial data aggregator, had collected about me.\nAt least in theory large-scale data collection matters quite a bit. Large data sets can be used to create social network maps and can form the seeds for link analysis of connections between individuals. Some see this as a good thing; others as a bad one \u2014 but whatever your viewpoint, we live in a world which sees increasing power and utility in Big Data\u2019s large-scale data sets.\nOf course, much of the concern is about government collection. But it\u2019s difficult to assess just how useful this sort of data collection by the government is because, of course, most governmental data collection projects are classified. The good news, however, is that we can begin to test the utility of the program in the private sector arena. A useful analog in the private sector just became publicly available and it\u2019s both moderately amusing and instructive to use it as a lens for thinking about Big Data.\nAcxiom is one of the largest commercial, private sector data aggregators around. It collects and sells large data sets about consumers \u2014 sometimes even to the government. And for years it did so quietly, behind the scene \u2014 as one writer put it \u201Cmapping the consumer genome.\u201D Some saw this as rather ominous; others as just curious. But it was, for all of us, mysterious.\nUntil now. In September, the data giant made available to the public a portion of its data set. They created a new website \u2014 Abouthedata.com \u2014 where a consumer could go to see what data the company had collected about them. Of course, in order to access the data about yourself you had to first verify your own identity (I had to send in a photocopy of my driver\u2019s license), but once you had done so, it would be possible to see, in broad terms, what the company thought it knew about you \u2014 and how close that knowledge was to reality.\nI was curious, so I thought I would go explore myself and see what it was they knew and how accurate they were. The results were at times interesting, illuminating and mundane. Here are a few observations:\nTo begin with, the fundamental purpose of the data collection is to sell me things \u2014 that\u2019s what potential sellers want to know about potential buyers and what, say, Amazon might want to know about me. So I first went and looked at a category called \u201CHousehold Purchase Data\u201D \u2014 in other words what I had recently bought.\nIt turns out that I buy \u2026 well \u2026 everything. I buy food, beverages, art, computing equipment, magazines, men\u2019s clothing, stationary, health products, electronic products, sports and leisure products, and so forth. In other words, my purchasing habits were, to Acxiom, just an undifferentiated mass. Save for the notation that I had bought an antique in the past and that I have purchased \u201CHigh Ticket Merchandise,\u201D it seems that almost everything I bought was something that most any moderately well-to-do consumer would buy.\nI do suppose that the wide variety of purchases I made is, itself, the point \u2014 by purchasing so widely I self-identify as a \u201Cgood\u201D consumer. But if that\u2019s the point then the data set seems to miss the mark on \u201Chow good\u201D I really am. Under the category of \u201Ctotal dollars spent,\u201D for example, it said that I had spent just $1,898 in the past two years. Without disclosing too much about my spending habits in this public forum, I think it is fair to say that this is a significant underestimate of my purchasing activity.\nThe next data category of \u201CHousehold Interests\u201D was equally unilluminating. Acxiom correctly said I was interested in computers, arts, cooking, reading and the like. It noted that I was interested in children\u2019s items (for my grandkids) and beauty items and gardening (both my wife\u2019s interest, probably confused with mine). Here, as well, there was little differentiation, and I assume the breadth of my interests is what matters rather that the details. So, as a consumer, examining what was collected about me seemed to disclose only a fairly anodyne level of detail.\n[Though I must object to the suggestion that I am an Apple user J. Anyone who knows me knows I prefer the Windows OS. I assume this was also the result of confusion within the household and a reflection of my wife\u2019s Apple use. As an aside, I was invited throughout to correct any data that was in error. This I chose not to do, as I did not want to validate data for Acxiom \u2013 that\u2019s their job not mine\u2014and I had no real interest in enhancing their ability to sell me to other marketers. On the other hand I also did not take the opportunity they offered to completely opt-out of their data system, on the theory that a moderate amount of data in the world about me may actually lead to being offered some things I want to purchase.]\nThings became a bit more intrusive (and interesting) when I started to look at my \u201CCharacteristic Data\u201D \u2014 that is data about who I am. Some of the mistakes were a bit laughable \u2014 they pegged me as of German ethnicity (because of my last name, naturally) when, with all due respect to my many German friends, that isn\u2019t something I\u2019d ever say about myself. And they got my birthday wrong \u2014 lord knows why.\nBut some of their insights were at least moderately invasive of my privacy, and highly accurate.  Acxiom \u201Cinferred\u201D for example, that I\u2019m married. They identified me accurately as a Republican (but notably not necessarily based on voter registration \u2014 instead it was the party I was \u201Cassociated with by voter registration or as a supporter\u201D). They knew there were no children in my household (all grown up) and that I run a small business and frequently work from home. And they knew which sorts of charities we supported (from surveys, online registrations and purchasing activity). Pretty accurate, I\u2019d say.\nFinally, it was completely unsurprising that the most accurate data about me was closely related to the most easily measurable and widely reported aspect of my life (at least in the digital world) \u2014 namely, my willingness to dive into the digital financial marketplace. Acxiom knew that I had several credit cards and used them regularly. It had a broadly accurate understanding of my household total income range [I\u2019m not saying!].\nThey also knew all about my house \u2014 which makes sense since real estate and liens are all matters of public record. They knew I was a home owner and what the assessed value was. The data showed, accurately, that I had a single family dwelling and that I\u2019d lived there longer than 14 years. It disclosed how old my house was (though with the rather imprecise range of having been built between 1900 and 1940). And, of course, they knew what my mortgage was, and thus had a good estimate of the equity I had in my home.\nSo what did I learn from this exercise?\nIn some ways, very little.  Nothing in the database surprised me, and the level of detail was only somewhat discomfiting. Indeed, I was more struck by how uninformative the database was than how detailed it was \u2014 what, after all, does anyone learn by knowing that I like to read? Perhaps Amazon will push me book ads, but they already know I like to read because I buy directly from them. If they had asserted that I like science fiction novels or romantic comedy movies, that level of detail might have demonstrated a deeper grasp of who I am \u2014 but that I read at all seems pretty trivial information about me.\nI do, of course, understand that Acxiom has not completely lifted the curtains on its data holdings. All we see at About The Data is summary information. You don\u2019t get to look at the underlying data elements. But even so, if that\u2019s the best they can do \u2026.\nIn fact, what struck me most forcefully was (to borrow a phrase from Hannah Arendt) the banality of it all. Some, like me, see great promise in big data analytics as a way of identifying terrorists or tracking disease. Others, with greater privacy concerns, look at big data and see Big Brother. But when I dove into one big data set (albeit only partially), held by one of the largest data aggregators in the world, all I really became was a bit bored.\nMaybe that\u2019s what they wanted as a way of reassuring me. If so, Acxiom succeeded, in spades.\n\n\nImage: Flickr, Barcelona Digital"^^<http://www.w3.org/2001/XMLSchema#string>
<http://mashable.com/2013/10/08/big-data-personal-information/>