IoT analytics guide: Understanding Internet of Things data
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The 2014 Pacific Northwest BI Summit is taking place in Grants Pass, Oregon, this weekend, with a group of consultants and vendor executives gathering at an inn on the Rogue Rover to discuss business intelligence, analytics and data management trends. The participants include Jill Dyché, a BI and data warehousing consultant who now is vice president of best practices at software vendor SAS Institute Inc. And not surprisingly, the discussion topics include big data technologies and what users are doing with them. In a video interview recorded at last year's summit, Dyché addressed that topic, based on interviews with 20 large companies that she conducted along with author and Babson College professor Thomas Davenport. Their findings were detailed in a report titled Big Data in Big Companies and incorporated into Big Data @ Work, a book by Davenport published in February 2014.
The big data projects in the surveyed companies can generally be placed into two categories, Dyché said in the interview. "The first one," she said, "is the one that everybody talks about, which is, 'What can we do with new data … to support brand-new, innovative business initiatives?' And certainly a lot of the companies that we talked to are doing just that." For example, she cited UPS, which collects sensor data from its package-delivery trucks to help optimize transportation routing. That has enabled the company to reduce fuel costs and improve delivery speeds, according to Dyché.
But, she added, other companies "are starting by simply redoing processes that are already in-house and making them faster and cheaper." Retailer Sears has taken advantage of that approach in a big way, using a Hadoop system to eliminate much of the traditional extract, transform and load (ETL) integration code in its data warehouse environment. In addition to reducing IT costs, the initiative has given the deployment team a test case for demonstrating the value of big data technologies to business executives, Dyché said.
Watch the eight-minute video to hear more of what Dyché said about big data applications at early adopters and the varied roles of data scientists at different companies.