Hadoop and connected cars: Why automotive execs should care about data

Did you know: For 13 percent of car buyers a new vehicle without internet access is a no-go? Obviously, no-go means no-buy. Thirteen percent! If I have ever seen a market demand, it is this. For sure, the industry will respond to that. The management consulting company Bain even expects […]

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Tom Davenport on data science, model management and the skills gap

This is the second in my two-part interview with Dr. Tom Davenport, analytics thought leader and author of Big Data @ Work. We caught up in Dublin to talk data science model management and the skills gap. Previously, we discussed big data and the Internet of Things in part one of […]

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Tom Davenport on Hadoop, Big Data and the Internet of Things

I recently caught up with Dr. Tom Davenport, analytics thought-leader and author of Big Data @ Work, in Dublin, where we talked about big data, the Internet of Things and Hadoop. I'll be sharing the conversation here with you in two parts. You'll find part one below, and you can check […]

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Statistics in the era of big data and the data scientist

Depending on whether you are a half-full or a half-empty kind of person, the "big data" revolution is either a tremendous windfall for the career of a statistician, or the makings of a real existential crisis. As with most things, it’s probably a bit of both. On the one hand, […]

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Hadoop: the game-changer in banking

At most banks, data is stored in separate databases and data warehouses. Customer data is stored in marketing databases, fraud analyses are done on transactional data, and risk data is stored in risk data warehouses. Oftentimes even liquidity, credit, market, and operational risk data is stored separately as well. Bringing […]

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Hadoop market growth: Breaking out of the Silicon Valley bubble

In the first installment of this series on Hadoop, I shared a little of Hadoop's genesis, framing it within four phases of connectivity that we are moving through. I also stated my belief that Hadoop has already arrived in the mainstream, and we are currently moving from phases three of connecting people to phase four […]

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Predictive analytics and Hadoop: Challenges and solutions for managing the whole analytics lifecycle

So, you've heard the Hadoop hype and you are looking – or have already invested – into Hadoop. Maybe you have also realized some benefits from the Hadoop ecosystem. But now you want to maximize those benefits by using advanced analytics, or you might have heard about algorithms or machine learning libraries available […]

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Get your house in order to cash in on retail’s omnichannel promise

Would you build a house without a proper foundation? Most of us wouldn’t dare, but that’s exactly what many retail businesses are doing today. When building a house, if you don’t get the foundation right, paint, wallpaper and fixtures won’t matter much. It’s no different in the retail industry. Success […]

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How Hadoop emerged and why it gained mainstream traction

In the world of IT, very few new technologies emerge that are not built on what came before, combined with a new, emerging need or idea. The history of Hadoop is no exception. To understand how Hadoop came to be, we therefore need to understand what went before Hadoop that led to its creation. To understand […]

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When does speed become a trap?

For many years companies have been working to increase their use of predictive analytics and to execute analytic models faster on increasingly granular and growing volumes of data. Recently, there has been a great focus on "faster" from a  technology standpoint, as modelers seek to iterate quickly and fail fast on […]

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