Big data Hadoop Training

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Hadoop is a highly scalable storage platform, because it can store and distribute very large data sets across hundreds of inexpensive servers that operate in parallel. Unlike traditional relational database systems that can't scale to process large amounts of data, Hadoop enables businesses to run applications on thousands of nodes involving thousands of terabytes of data.

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Benefits of Big data Hadoop:

Benefits of Big data Hadoop Let’s Get Started!

Benefits:

Benefits Scalable: Hadoop is a highly scalable storage platform, because it can store and distribute very large data sets across hundreds of inexpensive servers that operate in parallel. Unlike traditional relational database systems that can't scale to process large amounts of data, Hadoop enables businesses to run applications on thousands of nodes involving thousands of terabytes of data.

Benefits:

Benefits Cost effective: Hadoop provides a cost effective storage solution for businesses' exploding data sets. The problem with traditional relational database management systems is that it is extremely cost prohibitive to scale to such a degree in order to process such massive volumes of data. In an effort to reduce costs, many companies in the past would have had to down-sample data and classify it based on certain assumptions as to which data was the most valuable.

Benefits:

Benefits Flexible: Hadoop enables businesses to easily access new data sources and tap into different types of data (both structured and unstructured) to generate value from that data. This means businesses can use Hadoop to derive valuable business insights from data sources such as social media, email conversations or clickstream data.

Benefits:

Benefits Run a commodity: Some of the tasks that Hadoop is being used for today were formerly run by MPCC and other specialty, expensive computer systems. Hadoop commonly runs on commodity hardware. Because it is the de facto big data standard, it is supported by a large and competitive solution provider community, which protects customers from vendor lock-in.

Benefits:

Benefits Fast: The unique storage method of Hadoop is based on a distributed file system that basically 'maps' data wherever it is located on a cluster. The tools for data processing are often on the same servers where the data is located, resulting in much faster data processing. If you're dealing with large volumes of unstructured data, Hadoop is able to efficiently process terabytes of data in just minutes, and petabytes in hours.

Benefits :

Benefits Advanced data analysis can be done in-house: Hadoop makes it practical to work with large data sets and customize the outcome without having to outsource the task to specialist service providers. Keeping operations in-house helps organizations are more agile, while also avoiding the ongoing operational expense of outsourcing.

Benefits:

Benefits Companies can fully leverage their data: One alternative to not using Hadoop is simply not to use all the data and inputs that are available to support business activity. With Hadoop organizations can take full advantage of all their data – structured and unstructured, real-time and historical.

Benefits:

Benefits Resistant to failure: A key benefit of using Hadoop is its fault tolerance. When data is transferred to an individual node, that data is also replicated to other nodes in the cluster, which infers that in the event of failure, there is another copy available for use.

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