What are the Big Data Hadoop Challenges

What is Big Data Hadoop?

Big Data Hadoop means is a collection of large datasets that cannot be processed by using traditional computing techniques. It not merely a data has become a complete subject by involves various tools technique and frameworks. Big Data Hadoop has been defined in four ways:

•Volume: The amount of data volume indicates more data in granular nature of the data unique. Big data process high volumes of low density and task to convert big data to convert Hadoop data into such valuable information for some organizations might be ten terabytes.Get in touch with OnlineITGuru for mastering the Big data Hadoop Online Course.

•Variety: New unstructured data types and semi-structured data types such as text, audio, and video required the additional process for both derive meaning and supporting metadata whereas structured data has summarization, audibility, and privacy. Real-time changes in both transaction and analytical environments.

•Velocity: Fast rate data is received and acted upon. The highest velocity data normally streams directly into memory written to disk. Some internet applications have safety and health that require real time. For example e-commerce applications used to combine mobile device location and personal preferences to make time sensitive.

•Value: Data has intrinsic value discovered by the range of quantitative and investigation techniques to derive value from data. The technological break is the cost of data storage and the computer has exponentially decreased providing the abundance of data from statistical analysis.

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Big Data Hadoop Architecture:

Big Data Hadoop Architecture support for Analytics solution using open source Apache Hadoop framework. In Big Data Hadoop architecture is big volumes, variety, and velocity of data are collected from online and stored in HDFS file system. Hadoop architecture also provides RDBMS such as databases like HBase for storing big data in the traditional format and useful particularly to beginners and new users on Big Data Architectures. Not to mention for example, the big data landing zone is set up on Hadoop cluster to collect big data is stored in HDFS file system.

By using Map Reduce programming is online marketing analysts and various algorithms in Hadoop cluster to perform Big data analysts and core java programming language is implemented for Algorithms. Some cases implemented on Big Data Hadoop Architecture deriving Analytics as shown in the same example using Map Reduce programming method.

Keyword Research:

A number of counting in content occurs and search on hundreds of keywords across data collection into Hadoop and stored in HDFS. The algorithm used to help for identify top keywords by volume and the long hundreds of keyword searched by the users.

Content Classifications/Themes: Content user generate the wed content into specific themes and huge processing capabilities in Big Data Hadoop Architecture large volumes of content processed and classified into dozens of major themes.

User Segmentation: User individual behavior available in click stream and data combined with online user generates content combined with user targeted content produced in web content management systems.


What comes to Big Data Hadoop?

Generally Big data introduced different devices produced by data and applications. Some of them given below

Black Box Data: Component of airplanes, helicopter, and jets capture voices of the flight crew, earphones, recording of microphones and the performance information of aircraft.

Search Engine Data: It retrieves lots of information from different databases by a search engine.

Transport Data: Transport data added capacity, model, distance and availability of a vehicle.

Social Media Data: social media such as twitter and facebook hold information and views posted by millions of people across the world.

Power Grid Data: Power grid information holds consumed by a particular node respect to with base station.

Stock Exchange Data:  However the stock exchange data information about ‘buy’ and ‘sell’ decisions made by share of several companies made by the customers.

What are the Big Data Hadoop Challenges?

The major Big Data Challenges associated with as follows:

• Capturing data
• Storage
• Curation
• Sharing
• Searching
• Transfer
• Analysis
• Presentation

To fulfill the all above challenges organizations take help of enterprise servers.
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What are the benefits of Big Data Hadoop?

Consequently Big data is critical to our life and emerging one of the most important technologies in the modern world. some are the few benefits below:

• Generally Using the information in the social network like Facebook and the marketing agencies is learning about the response to their promotions, campaigns, and several advertising mediums.

• By using the data regarding the previous medical history of patients also providing better and However we get quick service from hospitals

• As a matter of fact, by Using the information on social media like preferences and product perception of their consumers and product companies with retail organizations are planning their production.

Who can learn Big Data Hadoop?

Especially Big Data is the mathematics of progress for probability is the math and arithmetic of adequacy total information. In the same fashion at a big scale and it does not work at small scale before learning Big Data should have basic knowledge of mathematics and aptitude.

• According to framework directories can form some java aptitude and additionally cloud administration’s abilities. In fact to start working with Big Data Hadoop operations

• For instance DBAS and ETL architects information also can know Apache Pig and related advantages to creating, streamline, and Simultaneously work with massive information streams

• Especially BI analysts and SQL can learn on data analysts such as like HIVE. In fact Python to wrangle, examine, and R gathered information inside Big Data Hadoop

The scope of Big Data Hadoop

In market huge demand for Business Analytics professionals in the technology and financial services industries growth shown in below


Generally Big Data Hadoop analysis is used in several ways and there a lot of opportunities. At the same time to select the particular domain for the job which interested in for career growth.

The different job titles are below:

• BI Analytics Consultant
• Analytics Associate
• Big Data Analyst
• Solution Architect
• Architect
• Engineer
• Business consultant

Big Data Analytics Job Titles and Salaries

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• Most Important,  frequently and widely used framework to manage massive data. As a matter of fact From a number of computing platforms and servers in every industry.

• In the mean time, it is One of the most optimized and efficient computational frameworks for big data analytics.

• Therefore Several significant and advanced big data platforms such as like Map Reduce, Yarn, setup .H base, Multi-node setup.


• In order to start learning Big Data has no prior requirement to have knowledge on any technology. Required to learn Big Data Hadoop and also need to have some basic knowledge on java concept.

• You must have good knowledge on OOPS Concept in any language supported. With Hadoop and also should understand about basic Linux/Unix command.
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