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GCN : March 2014
A COUPLE OF RECENT articles about Pandora's and Netflix's use of big data illustrate why government IT managers should not just focus on data management, data collection and even big data processing. Instead, they need to shift the focus from the data producer to the data consumer. A Wall Street Journal article on Pandora describes how it is mining its big data troves to make inferences on its users' political affiliation, demographic groups, paren- tal status and income. It is those inferences that are of value to the music service's advertisers, not the data on the music listened to. Meanwhile, The Atlan- tic magazine looked at Netflix's efforts to extract useful information from its big data. Netflix's creation of micro-genres like "criti- cally acclaimed emotional underdog movies" improves the chances consumers will discover movies that match their tastes and experience based upon past viewing habits. INFO CONSUMERS In both these cases, we see big data is the stepping stone for consumer-centric information production. The Netflix micro-genres are not a trove of big data on movie viewing, or on movie data itself. Instead, it is useful information mined from that data. Likewise, data contain- ing Pandora users' demo- graphics and preferences create a way for advertisers to target buyers. In The Semantic Web, my co-authors and I described how an inference rule allows you to derive conclusions from a set of premises. It is important to understand that those inferences are not the data; they are informa- tion derived from the data. Thus big data is the step- ping stone necessary to derive useful information for consumers (in this case, Pan- dora's advertisers). In other words, in order to make use of big data, we need to shift the focus from the producer to the consumer. This shift can be looked at in terms of push-driven versus pull-driven processes: We must replace uninformed data collection with engag- ing with business managers and line employees to learn what information they need to be productive. After their information requirements are clear, we can engage the information production process by pulling and as- sembling data from multiple data sources. This is the essence of consumer-driven information production. It is a 'pull-driven' process. The phenomenon of brute- force data collection will recur with the hype and rush to big data. But acquiring big data for big data's sake is a fool's quest. Instead, a big data effort should be initiated by a consumer question. A good example is Presi- dent Obama's re-election campaign of 2012. The campaign's fine- grained model of each voter included four scores: the likelihood to vote, the likelihood to be an Obama supporter, likelihood of be- ing an Obama donor (or vol- unteer) and the likelihood of being persuaded by a par- ticular topic. Each of these scores was measured and modified after each interac- tion with the candidate, and that was how the campaign would micro-target voters for promotions. The need to answer these questions drove the big data collection. CONTENT GENOMES One final note of interest is that Pandora's music "ge- nome" of songs and artists and Netflix's movie "ge- nome" of movies and actors/ actresses are pure metadata (the music and movies being the data). Given that, infer- ences on that music genome and the micro-genres of that movie genome are "meta- metadata." Given the proven value of this metadata and now me- ta-metadata, every organiza- tion that does not leverage a metadata catalog should re-examine the issue. I recently reviewed a large government organization's "metadata manifesto" and was pleased to learn IT man- agers felt so strongly about the issue that it warranted the boldness of a manifesto. Does your organization have a metadata manifesto? And in regards to big data, does your organization see big data as an end in itself or as a stepping stone? • --- Michael C. Daconta is vice president of advanced technology at InCadence Strategic Solutions and the former metadata program manager for the Homeland Security Department. BIG DATA: A STEPPING STONE FOR GETTING USEFUL INFO TO INFORMATION CONSUMERS REALITY CHECK BY MICHAEL DACONTA The phenomenon of brute-force data collection will recur with the hype and rush to big data. But acquiring big data for big data's sake is a fool's errand. GCN MARCH 2014 • GCN.COM 13