Over the past month, we’ve heard a lot of talk about big data. Unlike past months, we saw a handful of articles in January focused on the disillusionment surrounding big data. Upon thorough review, this disillusionment falls into one overarching category: big data is not delivering on the hype it created in 2012. Luckily, retailers are now starting to move beyond the hype to drive actionable insights; they are starting to ask the right questions of their data and solution providers. That being said, there is still a lot of ground to cover before we can claim that we have justified the hype.
Here you will find the top articles discussing big data disillusionment. We present them to you with the hope that they will inspire conversations, questions and feedback.
“Q&A: The Technology behind Big Data,” Financial Times – Before diving into our big data discussion, take a moment to read this interview with IBM Fellow, Rod Smith. The interview provides a nice overview of the emergence of big data and the role it’s playing in redefining various sectors. Of particular note, Rod notes that “retail and finance are the two biggest [drivers of big data] today.” Rod explains that the reasons for this are that both sectors are able to collect large amounts of data and that the data is constantly changing. With so much data that is always being updated, it comes as little surprise that disillusionment is taking hold of many.
“Has Big Data Reached Its Moment of Disillusionment?,” AllThingsD – In this article, Arik Hessldahl dives into the big data discussion by providing readers with an overview of what Gartner calls “The Hype Cycle.” In short, The Hype Cycle starts with a new technology that promises to “change everything,” then enters a “trough of disillusionment” phase before finally achieving productivity. So how do we get out of this “trough” and achieve productivity? First and foremost, ask yourself what question you are attempting to answer with your data. Next, break that question into subsets and try to answer them. This is by no means an easy task, but an absolutely necessary one to overcome all the hype.“Why We Need to Kill ‘Big Data’,” TechCrunch – There is little doubt the big data discussion will persist for years to come. But is the term “big data” becoming overused as countless startups define themselves as a “big data solution providers”? According to this article by Leena Rao, that’s exactly what’s happening. But the solution is not to identify a new term. Instead, we must look beyond the big data itself to what function it serves. I tend to agree with Leena on this point. Now that the importance of big data has been thoroughly established, let’s refocus all our conversations on how we can take that data and drive results. If you’re a big data startup, what solution do you provide? What are the actionable outputs? By answering these questions, hopefully we can move beyond the ambiguous “big data” label to drive greater insights.
“Technology and BIG Data are Changing the Retail World,” Forbes – In this contributed article, Marianne Bickle explores how big data and technology are not just aiding retailers, but also bringing new challenges to the forefront. For example, she argues that the “adoption of technology is a two-edge sword.” While big data allows retailers to better predict consumer behavior, new technology “enables consumers to make snap purchase decisions and switch brand and/or company loyalty.” Bickle argues that this leads to a blurring of consumer intentions. I agree that big data brings new challenges along with it. Here at Baynote, our passion is to turn big data into actionable insights that retailers can implement in order to drive sales and increase customer satisfaction. In doing so, we don’t necessarily see new technologies as a challenge. Instead, we view them as an opportunity to improve the analytics we provide.