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Open Source

Any software free to use and extend

Managing Big Data Integration and Security with Hadoop

September 2, 2015 by Jason Parms
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An open-source framework like Hadoop offers endless possibilities for development, and with a strong management group like Apache Systems behind it, one can expect increasing numbers of modules and technologies to integrate with Hadoop to enable your business to achieve its Big Data goals – and maybe even go significantly beyond what you can envision today.[read more]

Migrate from Proprietary Software to Linux to Create Cost Savings

August 28, 2015 by Simon Mitchell

Amongst the top IT trends of the moment is the development of Linux Containers. Financial and technical investors, Linuxsoftware programmers and customers believe that Linux Containers will transform the way organisations manage their Linux environments from deployment to maintenance.[read more]

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A Day Late and Big Data Architecture Short

June 29, 2015 by Paul Barsch

In the mad-dash to “do something” in big data without a strategy, IT managers and business users alike seem to continuously jump on the latest technology (today it’s Spark) and thus become inevitable case studies for Gartner’s well documented hype cycle.[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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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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Why Returning $1 Trillion to Shareholders is a Bad Idea

May 4, 2015 by Paul Barsch

Risky Business column.

With creaking IT infrastructures and under-investment in other areas such as plants, equipment, employee training and more, excessive share buybacks aren't just a flawed strategy; they are a dangerous one for the future health of companies across the globe.[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]

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The Data Lake Debate: Pro Cross-Examines Con

April 6, 2015 by Tamara Dull

The Data Lake Debate.

As to be expected, Anne, your arguments against building a data lake are both persuasive and passionate. You’ve made some great points, my friend, but you’re making this way too easy for me. Before I jump into my rebuttal [my next post], I’d like to clarify a few things that you brought up. I’ve boiled it down to three questions. What say you?[read more]

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Data Lakes and Network Optimization: What’s Next for Telecommunications and Big Data

March 31, 2015 by Sameer Nori

Telecommunication. 

Relational data warehouses served communications service providers well in the past, but it’s time to start thinking beyond columns and rows. Unstructured data will be the fuel that powers risk management and decision-making in the near future. And to use all sorts of data to its fullest potential, we need new ways of storing, accessing and analyzing that data.[read more]

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Hygienic Hadoop Data Lakes Not Just Happenstance

February 23, 2015 by Paul Barsch

Risky Business column.

If you work with Hadoop on a daily basis you already know that data cannot simply be dumped into Hadoop’s file system and be of high value to rank and file business users. To be sure, data management is crucial if you’re planning on Hadoop serving as a true lake or “hub” for all your organization’s data.[read more]

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Is Your IT Architecture Ready for Big Data?

January 6, 2015 by Paul Barsch

Risky Business column.

Companies desperately need to assess their current situation and future business needs, and then design and deliver on a IT architecture that will deliver insights from all data types.[read more]

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5 Ways Hadoop Can Help Healthcare Organizations and You

November 23, 2014 by Sameer Nori

Hadoop and healthcare

There are many different use cases for Hadoop in healthcare. Some of them include helping doctors, patients, and healthcare organizations include personalized treatment planning, assisted diagnosis, fraud detection, and monitoring patient vital signs. Learn how Hadoop is being implemented in each of these use cases.[read more]

Spotlight on SiSense: BI Without the Bandwidth

October 9, 2014 by Shawn Gordon

Spotlight on SiSense.

I was at DataWeek/API World in mid-September 2014 (last week at the time of this writing) and saw some interesting things, almost entirely around Big Data. The two items that stood out for me, were the Graph DataBase system Neo4j (which I wish I had time and a reason to dig into more), and SiSense, who absolutely blew my mind.[read more]

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Fine-Tuning Manufacturing Operations with Big Data and Hadoop

October 6, 2014 by Sameer Nori

Manufacturing pperations and Hadoop.

Your organization is a lean, mean Six Sigma machine. The corporate culture is centered on continuous improvement, with everyone well versed in Kaizen. Your supply chain is well oiled, which should provide assurance about product quality. And yet you wonder: is it possible to improve operations even further?[read more]