Top Reads in Big Data: Week of Sept. 9
"Value" is the key word in several of my top picks this week. From saving money to saving lives to saving time in who you follow on Twitter, we're still finding new ways to get value from data.
“What Executives Don’t Understand About Big Data,” by Michael Schrage, Harvard Business Review HBR Blog Network, Sept. 14
In what was surely one of the most cited posts of the week, Schrage urges executives not to be “too impressed – or too intimidated” by big data. It is a tool, albeit one with great potential for value if the C suite exhibits “A commitment to a desired business outcome.” He says the critical success factor is for executives to determine “What value matters most, and what marriage of data and algorithms gets us there?"
“Army Commanders: Let Us Choose Big Data Apps,” by Kevin Fogarty, InformationWeek, Sept. 13
What is more valuable than human life? By combining and monitoring data coming from a variety of remote surveillance sources - aircraft, towers, balloons – the United States and coalition forces in Afghanistan have greatly reduced the number of casualties from IEDs (improvised explosive devices). Previously, the troops relied on human intelligence sources, which proved unreliable. The data from actual observations is extremely valuable for protecting the lives of soldiers.
“How Big Data Became a Big Deal for a Marketer,” by Clint Boulton, Wall Street Journal CIO Journal, Sept. 5
In the rough-and-tumble world of subscription-based TV services, where big promotional offers routinely poach customers from competitors, a high churn rate is anathema. Companies seek any edge in retaining customers. Trident Marketing used predictive analytics to increase sales for DirecTV ten-fold while cutting churn in half.
- Learn more about Trident Marketing’s success
“Big Data’s Management Revolution,” by Erik Brynjolfsson and Andrew McAfee, Harvard Business Review Blog Network, Sept. 11
The duo of bloggers brings us two case studies demonstrating the dramatic effect big data can have on time. In one case, an airline could better predict when an aircraft would arrive at the airport, which allowed them to plan and deploy staff better. In the second example, a major retailer reduced the amount of time needed to roll out “personal recommendations” from eight weeks to less than one.
- See also “Why Static Stinks,” a blog and podcast by Tom Deutsch on why companies need to improve personal recommendations, and how they can do just that.
“What’s Your Data Style?” by Dana Stanley, Research Access, Sept. 6
Do you rely on data too much? Too little? Or are you a top performer who is comfortable with some ambiguity while still able to ask key questions from the data at hand? Stanley’s post deftly summarizes salient points from a Corporate Executive Board study of 600 marketers, which concludes, “As marketers get better access to raw numbers and big data keeps growing, the importance of this filtering ability will only intensify.”
“What data says about us,” by CNN Money, Sept. 10
A series of 13 vignettes illustrates how data helps us understand and improve the world we live in. The photos are stunning, including one composite of 1400 images shot of New York’s Times Square shot over 15 hours.
“Do you really want to get aboard the Big Data train?” by Brad Peters, Forbes, Sept. 6
I saw one tweet that answered the question posed in this article’s title by saying, “Yes, but make sure it’s on the right track.” Ahh, the power of Twitter to convey so much meaning in so few characters. Peters makes a solid case for the benefits of big data, while giving four basic questions you need to be able to answer before boarding the train.
- Also see – “Selecting Your First Big Data Project”
“Big Data: Experts to Follow on Twitter,” Techopedia, Sept. 13
Lots of people are talking on Twitter about big data, but that doesn’t mean they all know what they’re talking about. Techopedia compiled a list of 41 individuals who know their stuff and avoid the fluff. Techopedia confined its list to individual people. Jen Cohen of SAP compiled this list of “Top 50 #BigData Twitter Influencers,” which includes company and brand accounts.
Educational Video – HBase Fundamentals
Tina Chen, Big Data Solution Architect at IBM, goes in-depth on this column-oriented database management system that runs on top of HDFS.
Leave a comment with your favorite item from the big data beat this week – be it one of the above or something I missed entirely.
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