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Big Data

Google Launches a Service for Storing Big Data

May 7, 2015 by Sarah Smith

Google has introduced a service for storing large amounts of data online, potentially enabling organizations to execute big data analysis as a cloud service. The offering, called Google Cloud Bigtable, "is based on technology that Google has been running internally for many years, so it is not a brand new thing," said Tom Kershaw, who is Google's director of product management for the Google Cloud Platform.[read more]

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How Restaurants Are Using Big Data

May 6, 2015 by Rick Delgado
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With the rise of big data, many industries have seen just how beneficial using large amounts of information can be in improving their businesses. From retail to healthcare to sports to financial, each industry has found something valuable about big data in enhancing both the big picture and the smaller details.[read more]

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Big Data Anonymous: Ask Data Experts Your Burning Data Questions

May 5, 2015 by MJ Wesner

Ask data experts / shutterstock

We'd like to alert the Smart Data Collective community to a unique opportunity: the chance to ask a panel of internationally renowned data experts all your burning data questions. It's a part of the The Social Shake-Up, which we're hosting in Atlanta this June.[read more]

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Big Data and Advanced Technology Fuel Gamification in the Workplace

May 2, 2015 by Jessica Oaks

Gamification.

There is one common component that needs to happen when it comes to working or playing a game—engagement. As society transitions into a full-blown digitalization era, advanced technology and big data are being leveraged in the workplace to increase employee engagement through gamification.[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]

Do Your Customers Hide Their Data?

April 29, 2015 by Martin Doyle

Hidden data.

Personal data has an image problem. People are increasingly wary of handing over their details to websites – particularly when they have no intention to engage long term. Many marketers set out to obtain email addresses, yet do very little to ensure the email addresses they get are valid. This is the beginning of a vicious circle for the business they’re working for.[read more]

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How the Internet of Things and Big Data Are Changing Our World

April 28, 2015 by Bernard Marr

The Big Data Guru column.

I just bought a new vacuum cleaner that will tell me how many calories I have burnt during cleaning or let me know how much energy I have saved… There are sensors you can buy to turn your home into a smart home, and when attached to apps, they can perform a command or send you a message when certain things happen, like turning on a light when it detects motion at the front door, or sending you a text message when the liquor cabinet is opened.[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]

Taming Big Data

April 25, 2015 by Martyn Jones

Taming big data.

Simply stated, the best application of Big Data is in systems and methods that will significantly reduce the data footprint. Why would we want to reduce the data footprint? Years of knowledge and experience in information management strongly suggests that more data does not necessarily lead to better data.[read more]

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5 Tips for Streamlining the Supply Chain

April 24, 2015 by Glenn Johnson

Supply chain.

Supply chain efficiency helps an organization reduce costs and speed time-to-market. Fifteen years into the new millennium, it is clear to see that advances in technology, increasing globalization and rising customer expectations have made streamlining the supply chain more important than ever.[read more]

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Learn from Carnegie Mellon’s School of Data Management Hard Knocks

April 23, 2015 by Jeff Brown

Big data error.

The school mistakenly sent acceptance emails to hundreds of hopefuls who applied to Carnegie Mellon’s prestigious Master of Science in Computer Science program. A few hours later, an email with a much different tone arrived in their inboxes. A school statement read: “This error was the result of serious mistakes in our process for generating acceptance letters.”[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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Big Data: How Netflix Uses It to Drive Business Success

April 21, 2015 by Bernard Marr

The Big Brand Guru.

Legendary Hollywood screenwriter William Goldman said “Nobody, nobody – not now, not ever – knows the least goddam thing about what is or isn’t going to work at the box office.” He was speaking before the arrival of the internet and Big Data, and since then, the streaming movie and TV service Netflix has based its business model on attempting to prove him wrong.[read more]

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A Better Way to Model Data

April 21, 2015 by Mark Hargraves

Data modeling.

Over 8 years ago, the Spider Schema Data Model was created to provide an easier way to model OLTP data into a supported OLAP data model with the advantages of the OLTP data model. Over the last 8 years this data model has been proven out and is: faster at data processing, uses less storage space, is more flexible, and provides full support for not only OLAP, but OLTP, and Big Data.[read more]

5 Unusual Ways Businesses Are Using Big Data

April 17, 2015 by MIKE20 Governance Association
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Parking lot.

Big data is where it’s at. At least, that’s what we’ve been told. So it should come as no surprise that businesses are busy imagining ways they can take advantage of big data analytics to grow their companies. Many of these uses are fairly well documented, like improving marketing efforts, or gaining a better understanding of their customers, or even figuring out better ways to detect and prevent fraud.[read more]