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Phil Simon
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Author, Speaker, and Professor

Phil Simon is a keynote speaker and recognized technology expert. He is the award-winning author of eight management books, most recently Analytics: The Agile Way. His ninth will be Slack For Dummies (April, 2020, Wiley) He consults organizations on matters related to strategy, data, analytics, and technology. His contributions have appeared in The Harvard Business Review, CNN, Wired, The New York Times, and many other sites. He teaches information systems and analytics at Arizona State University's W. P. Carey School of Business.

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Amazon and the future of predictive commerce

Upselling isn't exactly a new creation of capitalism. Whether it's extended warranties at Best Buy or your credit card company offering you some type of enhanced protection when you dial the call center to investigate a charge, most of us have had the experience at one time or another. Consider

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Data lessons from Iron Maiden

"Technology is neither good nor bad; nor is it neutral." –Melvin Kranzberg The quote above is my favorite one of Kranzberg's six laws of technology. The law applies to everything from typewriters to tablets. Think of it as Moore's Law sans limits. I doubt that Kranzberg was a heavy-metal fan, but his

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2013: The rebirth of privacy?

As others have pointed out, 2013 may well go down as the year of Bitcoin, the first "mainstream" form of cryptocurrency. It's easy to dismiss Bitcoin as a fad, but other events from the previous year suggest that privacy is making a comeback. Exhibit A: Temporary photo and message app Snapchat, arguably the

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Big data, data discovery and new tools

While not quite at the level of big data, data discovery is attracting a good bit of attention these days. I explore both topics in The Visual Organization and Too Big to Ignore. It's only fair for people to ask if their legacy reporting tools support big data and data discovery. In short, the

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The data devil: dual data entry

On the old dataroundtable.com site, I railed a few times against the perils and general stupidity of dual data entry. At a high level, barring some type of cataclysm, there's absolutely no reason for anyone to be typing the same data into two disparate systems. And that goes double for anyone

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Managing big data expectations

In this era of big data hype, it's easy to understand the hesitation of many organizations to take the plunge. Finding a signal in noisy petabytes of unstructured data isn't easy. Companies like Netflix, Amazon, Facebook, Twitter and Google that "do" big data well have spent hundreds of millions of dollars (or

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Wearable tech: democratizing data

As I scribe these words, GadgetFEST 2014, aka CES, is in full swing. More than 3,000 vendors have descended upon Sin City to to hawk their wares. Nearly 200,000 people are here, and probably thrice as many internet-enabled devices. There seem to be more car-related exhibits than in years past.

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Hadoop and the future of ETL

I've lived in Las Vegas for two and a half years now. When I decided to move here, I was oblivious to the downtown revitalization taking place as well as the burgeoning tech ecosystem. It turns out that Vegas is an increasingly attractive place for start-ups. Thank 24-7 gambling, low

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Kodak and the provincial data mind-set

Few companies had histories as storied as Eastman Kodak. Although the company developed the first digital camera in 1975, "the product was dropped for fear it would threaten Kodak's photographic film business." [Wikipedia] Well, we all know how that turned out. In September, the company emerged from bankruptcy, but its future is anything

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