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Demand for Analyzing Big Data with Hadoop

At the crux of data analysis is the ability to decipher raw data, process it and arrive at meaningful and actionable insights that can shape business strategies. According to the latest research, nearly 2.5 quintillion bytes of data is created every day, and the number is slowly edging upwards. The storage and processing power needed to handle these large volumes of data cannot be handled in an efficient manner with traditional frameworks and platforms. So, there arose a need to explore distributed storages and parallel processing operations in order to understand and make sense of these large volumes of data or big data. Hadoop by Apache provides the much-needed power that is required to manage such situations to handle Big Data. Based on data produced by Wanted analytics it was found out that the top five industries hiring Big Data related expertise include Professional, Scientific and Technical Services (25%), Information Technology (17%), Manufacturing (15%), Finance and Insurance (9%) and Retail Trade (8%). 

Simply put, big data would be the problem and Hadoop would be one of the solutions leveraged to make sense of it. With the inclusion of a much needed HDFS component, the distributed storage problem is taken care of while the MapReduce component optimizes parallel data processing. According to Gartner data, nearly 26% of the analysts are leveraging Hadoop in their daily tasks which makes it imperative to learn the platform and stay ahead of the curve. In addition to its ability to handle concurrent tasks, Hadoop is scalable and cost-effective as well, making the lives of analysts much easier than before.

Benefits of earning Hadoop skills in Big Data Analysis

With most businesses facing a data deluge, the Hadoop platform helps in processing these large volumes of data in a rapid manner, thereby offering numerous benefits at both the organization and individual level.


Individual Benefits:

Undergoing training in Hadoop and big data is quite advantageous to the individual in this data-driven world:

  • Enhance your career opportunities as more organizations work with big data
  • Professionals with good knowledge and skills in Hadoop are in demand across various industries
  • Improve your salary with a new skill-set. According to ZipRecruiter, a Hadoop professional earns an average of $133,296 per annum
  • Secure a position with leading companies like Google, Microsoft, and Cisco with skills in Hadoop and big data

Organizational Benefits:

Training in Big Data and Hadoop has certain organizational benefits as well:

  • Relative to other traditional solutions, Hadoop is quite cost-effective because of its seamless scaling capabilities across large volumes of data
  • Expedited access to new data sources which allows an organization to reach its full potential
  • Boosts the security of your system as Hadoop boasts of a feature called HBase security
  • Hadoop enables organizations to run applications on thousands of nodes

Given the ease with which it allows you to make sense of huge volumes of data and leverage frameworks to transform the same into actionable insights, training and certification courses for Hadoop & Big Data are in great demand in the field of data science.

WHAT YOU WILL LEARN

1. Learn the fundamentals

Understand what Big Data is and gain in-depth knowledge of Big Data Analytics concepts and tools.

2. Efficient data extraction

Learn to Process large data sets with Big Data tools to extract information from disparate sources.

3. MapReduce

Learn about MapReduce, Hadoop Distributed File System (HDFS), YARN, and how to write MapReduce code.

4. Debugging techniques

Learn best practices and considerations for Hadoop development as well as debugging techniques.

5. Hadoop frameworks

Learn how to use Hadoop frameworks like ApachePig™, ApacheHive™, Sqoop, Flume, among other projects.

6. Real-world analytics

Perform real-world analytics by learning advanced Hadoop API topics with an e-courseware.

6. Real-world analytics

Perform real-world analytics by learning advanced Hadoop API topics with an e-courseware.

1. Learn the fundamentals

Understand what Big Data is and gain in-depth knowledge of Big Data Analytics concepts and tools.

2. Efficient data extraction

Learn to Process large data sets with Big Data tools to extract information from disparate sources.

3. MapReduce

Learn about MapReduce, Hadoop Distributed File System (HDFS), YARN, and how to write MapReduce code.

4. Debugging techniques

Learn best practices and considerations for Hadoop development as well as debugging techniques.

5. Hadoop frameworks

Learn how to use Hadoop frameworks like ApachePig™, ApacheHive™, Sqoop, Flume, among other projects.

6. Real-world analytics

Perform real-world analytics by learning advanced Hadoop API topics with an e-courseware.

1. Learn the fundamentals

Understand what Big Data is and gain in-depth knowledge of Big Data Analytics concepts and tools.

Prerequisites

Before undertaking a Big Data and Hadoop course, a candidate is recommended to have a basic knowledge of programming languages like Python, Scala, Java and a better understanding of SQL and RDBMS.