Sep 15, 2016

Big Data: An overview of big data technologies learning and its importance (Need of hour technologies)

Do You Want to Become a Big Data Hadoop Expert?

Hadoop is one of the most sought-after skills today. Big data professionals are asked to prove their skills with tools and techniques of Hadoop stack. It has been observed by the market analyzers that though there are many Hadoop professionals in the market, still a huge number of skilled and trained professionals are required.

We are living in the world of Big Data revolution and every organization relies on collecting, analyzing, organizing and synthesizing a huge amount of data in order to survive in the competitive market. Every organization either government or private uses Big data to manage their products and services to attract new customers. In this blog, let’s know more about the career path of a Hadoop Expert.

Introduction to Big Data
The Big Data term is basically used to manage dataset collections, especially those that are complex and large. The sets that cannot be processed and stored with the help of traditional data management tools use Hadoop technology to process them. The main challenges of data processing that are observed include searching, sharing, curating, capturing, analyzing and transferring of stored data.

Following Listed 5 Vs Characterize The Data Processing Challenges:
1.     Volume: Volume refers to the huge amount of data, which keeps on growing day by day and becomes huge to process

2.     Variety: Presence of various data sources contributing to Big data can be from old databases or social media. Data can also be structured or unstructured.

3.     Velocity: The pace with which various data sources contribute to big data by generating traffic may be different. Big data has the power to manage the traffic and massive amount of data.

4.     Veracity: Sometimes data can be present or not so the uncertainty of data availability refers to data inconsistency and incompleteness refers to data veracity.

5.     Value: Though the massive amount of data is available throughout the data sources all of them is not valuable, so turning it to valuable data which can benefit the organization is important and done by Big data Hadoop.

Hadoop and It’s Architecture

Hadoop and its architecture consist mainly of two components that are NameNode and DataNode. Both are described below:

NameNode
NameNode is the master daemon that is responsible to manage several files, clusters, file permission, hierarchy and every change made to the file system. As soon as a change in any file is made like if a file will be deleted then it will be immediately reflected in EditLog. Edit log basically receives a block report and heartbeat from all data nodes to make sure that data nodes are live.

DataNode
DataNodes are daemon slave nodes, that run on slave machines. Actual data is stored on datanode and they are responsible to read and write client requests. As per NameNode decisions the data nodes can delete or replicate the blocks. For this YARN or Yet Another Resource Manager tool is used.

YARN Resource Manager
ResourceManager works at cluster level and runs on the master machine. Resource management and application scheduling are two of the main responsibilities of ResourceManager. Through YARN ResourceManager both of these tasks are managed.

YARN Node Manager
NodeManager component of YARN is Nodelevel and runs on every slave machine. Main responsibilities of NodeManager includes managing and monitoring of containers, it also manages logs and keeps track of node health. NodeManager continuously communicates with ResourceManager.

MapReduce
MapReduce is a core Hadoop component and provides processing logic. This software framework helps in writing applications that can process large data sets by using parallel and distributed algorithms in Hadoop environment. Functions like grouping, sorting, and filtering are performed by the map function and aggregation, summarization and result production are two of the main responsibilities of the map-reduce component.

Career Path  of a Hadoop Developer

There can be many challenges while starting a career as Hadoop developer. Here we have summarized some key factors for the path of Hadoop professionals, which will help you in shaping the career as a successful professional.

Required Educational and Technical Skill
The course can also be joined by non-technical candidates from the backgrounds like graduates of Statistics, Electronics, Physics, Mathematics, Business Analytics and Material Processing. As far as experience is concerned then newbies or less experienced professionals having 1-2 years of experience can become Hadoop developers. Mainly employers judge the candidates based on their knowledge and their zeal to learn the new concepts.

For technical experience technical knowledge of java concepts are required. Though for Hadoop you may not require possessing advance Java concept knowledge. Professionals from other streams also learn Hadoop and switch their career to this most in-demand platform.

Hadoop Certifications and Learning Path
One of the commonly seen questions among Hadoop developers is that “what is the value of certification for this profession?” With the certification, the candidate’s candidature can be judged or even verified. There are various Hadoop certifications available for Hadoop developers like of IBM, EMC, MapR and many more. One can apply and get certified in the technology easily.

As far as learning path for the developers is concerned then the candidates who fulfill the basic educational requirements either with or without relevant experience can apply for the position of Hadoop developer.

There are a number of companies that hire Hadoop professionals and are offered best salary packages. As the demand for Hadoop professionals is higher than availability so it has become the most sought-after skill among Hadoop professionals.

The research shows that a Hortonwork Hadoop professional can earn around $170,472, while Walmart is offering an average package of the $128K package to the Hadoop professionals in California. In the countries like the USA, Hadoop professionals are getting on an average $145K salary package. So you can sense the sensation of Hadoop profession these days.

Final Words

Those who have a passion for data analytics and statistics, Hadoop is one of the great choices for you. You can deep dive into the technology and it can prove as a lucrative career option for you. Good Luck!!


About Author
Manchun Pandit loves pursuing excellence through writing and have a passion for technology. he has successfully managed and run personal technology magazines and websites. he currently writes for JanBaskTraining.com, a global training company that provides e-learning and professional certification training.


Location: Bengaluru, Karnataka, India