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Apache Hadoop has been the driving force behind the growth of the big data industry.You will hear it mentioned often, along with associated technologies such as Hive and Pig. But what does it do, and why do you need all its strangely-named friends, such as Oozie, Zookeeper and Flume?
Hadoop brings the ability to cheaply process large amounts of data,regardless of its structure.By large,we mean from 10-100 gigabytes and above. How is this different from what went before?
Existing enterprise data warehouses and relational databases excel at processing structured data and can store massive amounts of data, though at a cost: This requirement for structure restricts the kinds of data that can be processed, and it imposes an inertia that makes data warehouses unsuited for agile exploration of massive heterogenous data. The amount of effort required to warehouse data often means that valuable data sources in organizations are never mined. This is where Hadoop can make a big difference.Big Data Training Chennai | Work on Production Level Cloud Server Access | Work on Proof of Concept Projects
Big Data startups are building viable products that target real-world pain points, and most of these Big Data new ventures are well-funded with solid management teams. Here are 10 Big Data startups to watch.
The Big Data market is heating up, and unlike some overhyped trends (social media), it's pretty easy to pinpoint ROI with these tools.
At its core, Hadoop is an open source Mapeduce implementation. Funded by Yahoo, it emerged in 2006 and, according to its creator Doug Cutting, reached “web scale” capability in early 2008.
As the Hadoop project matured, it acquired further components to enhance its usability and functionality. The name “Hadoop” has come to represent this entire ecosystem. There are parallels with the emergence of Linux: The name refers strictly to the Linux kernel, but it has gained acceptance as referring to a complete operating system.Big Data Hadoop Architect Weekend Classroom Training
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