Wednesday, July 26, 2017

What is Hadoop Ecosystem * Hadoop Training Online

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Monday, July 24, 2017

Learn Big Data and Hadoop Tutorial Basic

Big Data & Hadoop Training Online

Hadoop Tutorials for Beginners

To most people big data is a question like is it a tool or a product? Or is big data only for big business?

So what is Big Data? In simple terms it means to make sense of too much Data OR to use so much Data effectively OR make sense of all the garbage data.

Today data which organization handles have reached unbelievable levels that traditional process and tools fails to process. Big Data (the amount of data) is ever growing and cannot be determined with respect to its size. Big Data can analyze Tera bytes of structured and unstructured data.

With our Hadoop online training, you will learn Hadoop to answer at-least the questions below and much more:

How HDFS data warehouse stores all the multi-structured data and processed data at a pita bytes scale? Understand and master the concepts of the Hadoop framework and its deployment in a cluster environment. How to write complex MapReduce programs? Describe how to manipulate data using Sqoop and Flume? Learn best practices of high volume (Big Data) of structured and unstructured data storage in Hadoop and how to handle it? Explain how to model structured data as tables with impala and hive? Explain the difference between Hadoop MapReduce versus Pig Versus Hive?

Hadoop is a framework that allows distributed processing of large data sets across clusters of commodity computers using simple programming models it is inspired by a technical document published by Google.

Learn Hadoop to addresses the challenges of distributed systems such as, high chances of system failure (if any one system fails in distributed system it might impact the time), limit of bandwidth (internet and other challenges), and high programming complexities

With our Hadoop online training, you will learn to find solutions to above challenges.

Learn Hadoop to understand out of its many characteristics, how to implement and use the 4 key characteristics which are 1. Economical (any ordinary computers can be used to process high quantity of data in distributed frameworks with Hadoop) 2. Reliable (Since we will have copies of data on different machines and can handle system failures) 3. Scalable (a few extra nodes can help in scaling up the framework) 4. Flexible -we can store as much as structured and unstructured data as we need and decide to use them later as per our requirement

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Check our Blog on key components of Hadoop Ecosystem