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Tag Archives: Big Data

Decentralized Analytics for a Complex World

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In 2015, General Stan McChrystal published Team of Teams, New Rules of Engagement For a Complex World. It was the culmination of his experience in adapting to a world that had changed faster than the organization that he was responsible to lead. When he assumed command for the Joint Special Operations Task Force in 2003, he recognized that their typical ...

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Cassandra: The Foundation Big Data Building Block

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As Chief Technology Officer and co-founder at Instaclustr, Ben sets the technical direction for the company, identifying new features and capability. Ben is located in our Redwood City office and he was recognized as an Apache Cassandra MVP at the Cassandra Summit in 2015. Ben is active in the community often speaking at local meetups and presenting at related conferences. ...

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The Essential Guide to Streaming-first Processing with Apache Flink

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Editor’s note: This is a post by Apache Flink PMC members Fabian Hueske and Kostas Tzoumas. Fabian and Kostas are also co-founders of data Artisans.  A very large part of today’s data processing is done on data that is continuously produced, e.g., data from user activity logs, web logs, machines, sensors, and database transactions. Until now, data streaming technology was lacking in several ...

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Bet Super Bowl 50 Like A Boss with Apache Spark

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This time, it’s personal. Super Bowl 50 is being played at Levi’s Stadium in Santa Clara – within sight of many of the world’s most innovative technology companies, including MapR. It’s the Silicon Valley Super Bowl* so it only makes sense that this will be the most over-analyzed event in history (at least until the next big game). Big events ...

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Streaming in the Extreme

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Are you ready to start streaming all the events in your business? What happens to your streaming solution when you outgrow your single data center? What happens when you are at a company that is already running multiple data centers and you need to implement streaming across data centers? What about when you need to scale to a trillion events ...

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Qualitative Data: The Context that Gives Meaning to Your Big Data

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Someone once said “if you can’t measure something, you can’t understand it.” Another version of this belief says: “If you can’t measure it, it doesn’t exist.” This is a false way of thinking – a fallacy – in fact it is sometimes called the McNamara fallacy. This mindset can have dire consequences in national affairs as well as in personal ...

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Top 10 Big Data Trends in 2016 for Financial Services

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2015 was a groundbreaking year for banking and financial markets firms, as they continue to learn how big data can help transform their processes and organizations. Now, with an eye towards what lies ahead for 2016, we see that financial services organizations are still at various stages of their activity with big data in terms of how they’re changing their ...

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MapReduce Design Patterns Implemented in Apache Spark

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This blog is a first in a series that discusses some design patterns from the book MapReduce design patterns and shows how these patterns can be implemented in Apache Spark(R). When writing MapReduce or Spark programs, it is useful to think about the data flows to perform a job. Even if Pig, Hive, Apache Drill and Spark Dataframes make it ...

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Introduction to Apache Spark with Examples and Use Cases

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I first heard of Spark in late 2013 when I became interested in Scala, the language in which Spark is written. Some time later, I did a fun data science project trying to predict survival on the Titanic. This turned out to be a great way to get further introduced to Spark concepts and programming. I highly recommend it for ...

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