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Major Avantages of Hadoop

 Career with Hadoop:

 According to a Forbes report of 2015, about 90% of global organizations report medium to high levels of investment in big  data analytics, and about a third call their investments “very significant.” Most importantly, about two-thirds of respondents  report that big data and analytics initiatives have had a significant, measurable impact on revenues.

Hadoop is a software framework for storing and processing Big Data. It is an open-source tool build on java platform and focuses on improved performance in terms of data processing on clusters of commodity hardware.

• Hadoop conceptually different from Relational databases and can process the high volume, high velocity and high variety of data to generate value

• Hadoop comprises of multiple concepts and modules like HDFS, Map-Reduce, HBASE, PIG, HIVE, SQOOP and ZOOKEEPER to perform the easy and fast processing of huge data

Hadoop skills are in demand – this is an undeniable fact! Hence, there is an urgent need for IT professionals to keep themselves in  trend with Hadoop and Big Data technologies.

Apache Hadoop provides you with means to ramp up your career and gives you the following advantages:

• Accelerated career growth.
• Increased pay package due to Hadoop skill.

It is no rocket science that a career in Hadoop is very rewarding. Do want to have a accelerated and rewarding career in Hadoop? Click here to kick start your career in Hadoop.

1. 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 (RDBMS) 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.

2. Cost effective

Hadoop also offers 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. The raw data would be deleted, as it would be too cost-prohibitive to keep. While this approach may have worked in the short term, this meant that when business priorities changed, the complete raw data set was not available, as it was too expensive to store. Hadoop, on the other hand, is designed as a scale-out architecture that can affordably store all of a company’s data for later use. The cost savings are staggering: instead of costing thousands to tens of thousands of pounds per terabyte, Hadoop offers computing and storage capabilities for hundreds of pounds per terabyte.

3. 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. In addition, Hadoop can be used for a wide variety of purposes, such as log processing, recommendation systems, data warehousing, market campaign analysis and fraud detection.

4. Fast

Hadoop’s unique storage method 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.

5. Resilient to failure

A key advantage of using Hadoop is its fault tolerance. When data is sent to an individual node, that data is also replicated to other nodes in the cluster, which means that in the event of failure, there is another copy available for use.

The MapR distribution goes beyond that by eliminating the NameNode and replacing it with a distributed No NameNode architecture that provides true high availability. Our architecture provides protection from both single and multiple failures.

When it comes to handling large data sets in a safe and cost-effective manner, Hadoop has the advantage over relational database management systems, and its value for any size business will continue to increase as unstructured data continues to grow.

Career Opportunities:

Software Engineers, who are into ETL/Programming and exploring for great job opportunities in hadoop. 
- Managers, who are looking for the latest technologies to be implemented in their organization, to meet the current & upcoming challenges of data management. 
- Any Graduate/Post-Graduate, who is aspiring a great career towards the cutting edge technologies​ in IT​.

 Companies like Google, EMC Corporation, Yahoo, Apple, HortonWorks, Oracle, Amazon, Cloudera, IBM, Cisco, Microsoft and many more have opened their doors for hadoop professionals. Various positions like product managers, hadoop developers, software testers, database administrators, senior hadoop developers and alike are open. Companies are searching for experienced candidates as well as freshers