March 29, 2013
Among the trends hitting the tech world today, big data is not one of the sexiest. If it conjures up any image at all, it’s pages of numbers and text with a vague bearing upon business reality.
Released last Monday, Too Big to Ignore: The Business Case for Big Data by Phil Simon hopes to bring big data to life. Through colorful examples from pothole reporting to flu outbreak prediction, Simon illustrates the real effects of big data and how businesses can use it to get ahead.
Simon is the author of four other management books, including The Age of the Platform. He currently works with companies to optimize their use of technology. Below, he breaks down the big data trend and offers some advice to entrepreneurs.
Tech Cocktail: What does “Big Data” mean?
Phil Simon: You’d think that such a simple term would have a commensurately simple definition, right? It doesn’t. I'll try to simplify as much as I can.
Most people think of data as rows and columns in an Excel spreadsheet or in an Oracle database. To be sure, that structured (and often transactional) data still matters. Think lists of customers, employees, sales, etc.
Big Data represents mostly unstructured data information found in blog posts, customer reviews, call detail records, tweets, YouTube videos, podcasts, emails, and a host of other sources. Increasingly, more data is generated by machines via sensors. Think the Nest Thermostat, smart grids, and the Internet of Things. There’s no shortage of sources of data. If you aggregate them all, you wind up with Big Data.
Tech Cocktail: What is the point of Big Data?
Simon: I’d argue that the point is the same as any other technology or trend: to help businesses grow, reduce costs, innovate faster, garner new insights into consumer behavior, and the like. As I write in the book, Big Data is allowing organizations to do simply amazing things – and not just behemoths like Amazon, Apple, Facebook, and Google. For instance, this weekend, the New York Times ran an interesting piece on how New York City is using Big Data to learn how to govern better. And small companies are using Big Data to power their businesses. In Too Big to Ignore, I write about a few of them, like Explorys and Quantcast.
Tech Cocktail: Why is more data available and interpretable these days?
Simon: Three reasons. First, consumers are generating and consuming more data than ever. Low data storage costs, social networks, mobility, the cloud, and broadband mean that we can consume – and generate – as much content as we like. All of those are necessary conditions for the arrival of Big Data. For example, no one would upload a video to YouTube if it took eight hours to process and was expensive and impossible to watch. Brass tacks: Big Data couldn’t have happened in 2001.
Second, as I mentioned earlier, machines are generating a great deal of information without any direct human interaction. Finally, companies (both established and startups) have seen how Amazon, Apple, Facebook, Netflix, Google, Twitter, and other successful organizations have used Big Data. Many CXOs are wondering how they can leverage Big Data – and attempt to ape their results.
Tech Cocktail: How can startups use data to fuel their decisions? Can you recommend any tools?
Simon: Data can be generated about just about anything these days. Products, websites, and concepts need not be conceptual. Today, it’s never been easier to quantify ideas and results. For instance, sites like Optimizely allow individuals to conduct A/B or split testing. If I were looking for funding for a startup, I would attempt to prove that the business model or product has traction – at least to the extent that I could.
Analyzing Big Data requires new tools, and I list many in the book. NoSQL, Hadoop, NewSQL, and columnar databases are just a few. Many of these are open source, but one should never mistake free speech with free beer. I can download Hadoop right now, that doesn’t mean that I know how to use or configure it to achieve real business results. Remember, that’s the whole point of Big Data.
Finally, for cash-strapped startups without the budget for new on-premise solutions, consider sites like DataSift, Kaggle, TopCoder, and Innocentive. Each offers relatively low-cost ways to leverage Big Data.
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