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Hadoop

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Big Data Hadoop Use Cases in the Oil and Gas Industry

June 22, 2015 by Dave Mendle
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While U.S. oil production has begun expanding - so much so that the International Energy Agency predicts that by 2016 the US will surpass Saudi Arabia and Russia - the rest of the world’s oil production has ceased to expand. In an effort to streamline and optimize oil and gas production methods, advances in instrumentation, process automation, collaboration, and data management are being developed.[read more]

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How Big Data Affects Us Through the Internet of Things

June 19, 2015 by Dave Mendle

Although big data is ever-present in our lives, it can be difficult to understand how much it really has changed our day-to-day living. Let’s take a closer look at how big data has weaved its way into the lives of many consumers today, via the Internet of Things (IoT).[read more]

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4 Considerations When Choosing a Hadoop Distribution

June 18, 2015 by Dave Mendle

Choosing the right Hadoop distribution can be a tricky process. Many businesses looking to adopt Hadoop in their data infrastructure have a hard time figuring out what really differentiates one distribution from another. With so many options available, it’s easy to get lost in the choices.[read more]

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The Data Lake: A More Balanced Perspective

June 17, 2015 by Tamara Dull

The Big Data MOPS Series.

The recent data lake debate with my colleague, Anne Buff, may be over, but the discussion in many organizations is just getting started. What we learned during the debate—and you may be discovering in your own organization—is that it forces the larger discussion of managing growing volumes of data in a big data world. With the onslaught of big data technologies in recent years, organizations are having to look once again at the underlying technologies supporting their data collection, processing, storage, and analysis activities. And right now, the Hadoop-based data lake happens to be a very popular option.[read more]

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Is Your Data Big?

June 15, 2015 by Dave Mendle
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So you’ve heard all the buzz about data. It’s big. Apparently, big data is all around us. That’s what they say anyway. Truthfully, it can be difficult as a business owner to identify where you stand in the grand universe of big data. How big is your data? How are you using it? Would you benefit from using the right big data technology? In short, how do you know if your business is part of this big data revolution? Well, let me help you answer that.[read more]

10 Reasons Why Now Is the Time to Get into Big Data

June 12, 2015 by Rick Delgado

Big data is a key that'll explain specifically what your consumers really think about your product. Big data is even being used in medical research for companies that do personalized medicine or companion diagnostics, and need to analyze large amounts of biological data. You'll be able to use your insight to easily get a better picture of your customers based out of different geographic areas and belonging to different demographic groups.[read more]

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Using Recommendation Engines to Reduce Subscription Service Churn

June 12, 2015 by Dave Mendle

Recommendation engines are the digital version of the pot of gold at the end of the Big Data rainbow. Imagine being able to know, in near-time, what your customers really want and when they want it. For a subscription service, the gold is even brighter: You can deliver your customers’ desires directly to them, leading to a dramatic reduction in churn.[read more]

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Redefining Loyalty Programs with Big Data and Hadoop

June 11, 2015 by Dave Mendle

A loyalty program should not be about points, rewards, or status. While these perks may attract consumers, they don’t foster loyalty. The focus of these programs should be to collect useful data that can be used to build relationships that benefit both the consumer and the brand.[read more]

Hadoop Can't Do That

June 2, 2015 by Paige Roberts
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I just got back from a little executive summit conference in Dallas for Chief Data Officers. Frustratingly, I heard a lot of folks telling me what Hadoop CAN’T do. If you asked most people if water could cut through steel, they would probably tell you it can’t. They would be wrong, too.[read more]

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Will You Always Save Money with Hadoop?

May 27, 2015 by Tamara Dull

The Big Data MOPS Series.

If you answered “yes” to the question posed in the title, you’re right. Because if you’re talking about the open source Apache Hadoop project (and any related open source project) , you can download the software for free, take advantage of the free licensing, and run it on low-cost commodity hardware.[read more]

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A Big Data Cheat Sheet: What Executives Want to Know

May 21, 2015 by Tamara Dull
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The Big Data MOPS Series. 

What can Hadoop do that my data warehouse can’t? The short answer is: (1) Store any and all kinds of data more cheaply and (2) process all this data more quickly (and cheaply). The longer answer is: They say that 20% of the data we deal with today is structured data. I also call this traditional, relational data. The other 80% is semi-structured or unstructured data, and this is what I call “big” data.[read more]

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The Data Lake Debate: Conclusion (With Apologies to the Rolling Stones)

April 30, 2015 by Jill Dyché

The Data Lake Debate.

In an homage to the Rolling Stones, I blithely suggested that if you try sometimes, you get what you need—be it more funding, access to third-party data, a more effective executive sponsor, or a Hadoop distribution provider. It’s not an easy decision, but I’d call the data lake debate a draw. After all, when it comes to the verdict on whether or not a data lake is a worthwhile investment, the success stories will start to emerge. In the meantime, I’m happy to watch those stories unfold. Time, after all, is on my side. Yes it is.[read more]

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The Data Lake Debate: Pro Delivers Final Rebuttal and Summary

April 27, 2015 by Tamara Dull

Okay, this is where the rubber meets the road. I have three minutes (or ~450 words) to respond to Anne’s final statement and summarize why I still believe a data lake is essential for any organization to take full advantage of its data. Let’s get started![read more]

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The Data Lake Debate: The Final Word from Negative

April 22, 2015 by Anne Buff
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The Data Lake Debate.

Well, it seems you took the gloves off this time, Tamara. I appreciate the valiant effort and your passionate belief in the Hadoop ecosystem. However, given your revisit to the definition of the data lake and clarifications about Hadoop, I find it important to repeat the resolution we are debating: “a data lake is essential for any organization to take full advantage of its data”. We are not debating whether a data ecosystem is essential – just the data lake.[read more]

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The Data Lake Debate: Pro Delivers First Rebuttal

April 10, 2015 by Tamara Dull

Data Lake Debate.

In my opening argument, I defined the data lake as a storage repository that holds a vast amount of raw data in its native format, including structured, semi-structured, and unstructured data. I also mentioned that a data lake can take on different shapes and sizes, and provided these examples: A single data lake; or a data lake with multiple data ponds—similar in concept to a data warehouse/data mart model; or multiple, decentralized data lakes; or a virtual data lake to reduce data movement.[read more]