Choosing a career in the field of big data and Hadoop must just be the type of role that you have been trying to find to meet your career expectations. Graspskills will be every ready to find you a path for your great future. Even those who are at entry level will find high salaries. As more and more companies realize the need for specialists in big data & Hadoop. The number of these jobs will continue to grow. This course builds an essential fundamental understanding of big data & Hadoop as a soln.

1. Understanding of Big data problems with easy to understand.

2. History & advent of Hadoop right from when Hadoop was not even named Hadoop.

3. What is Hadoop magic which makes it so unique and powerful?

4. Understanding diff b/w data science and data engineering which is one of the big confusion in selecting a carrier or understanding a job role.

5. Most importantly demystifying Hadoop vendors like Cloudera, MapR & Horton works by understanding about them.

What one learn

*To build fundamental knowledge of Big data & Hadoop.
*To build essential understanding about Big data & Hadoop.

Requirements

Interest in the new technical field of Big data.
Interest in new technology: Hadoop.
Target audience?
Big data & Hadoop enthusiast
Non-greeks & anyone who wants to know about Big data.

      Hadoop is an open source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data enormous processing power & the ability to handle virtually limitless concurrent tasks or jobs. Big data is nothing but a concept which facilitates handling of a large number of data sets. Hadoop is just a single frame workout of dozens of tools. Hadoop is primarily used for batch processing.

Limitations of existing testing practices

Current day engineers are being limited by their knowledge of solving Bigdata problems. The standard data matching techniques at their disposal fail to work with very large volumes of data. Here big data tools help engineers adopt unique tools that are immensely useful for testing complex data sets or trapping the opportunities in allied fields.

Ease of shift

For Java experts, with prior knowledge open-sourced, java based coding frameworks, it’s easy to shift to big data scripts and analytics. This does not necessarily mean that non-java experts are in for tougher times ahead; Hadoop presents an array of tools for them too. Hadoop tools like pig, Hive & sqoop rely on SQL and have little to do with java.

Application platforms and shared skills

The roles of a testing professional and Hadoop expert are not mutually exclusive. Though the idea of adopting the new domains like Big data/Hadoop may seem overwhelming to begin with, there are many platforms that can be aligned together for gaining knowledge. For instance, sharp analytical skills a great attitude, result –oriented technical skills, willingness to learn, and orientation to details are the common traits required for testing engineers to move to Hadoop.

The aid of Big data for software development

Generally, machines are automated for analyzing a large volume of codes extract the parts that software developer needs to know. These bits relate to the common patterns that offer insights into how other test engineers or developers may have solved similar problems in the past. The advantage of Big data is that it not only points out the solution but underlying problems too. For instance, this data technology recognizes characteristic patterns that relate to bugs in the lines of codes and throws them back to the developer for timely corrections.

So, if you are a testing engineer or software developer struggling to catch on to the fast pace of Big data & Hadoop deluges, then adapt to latest technologies in Graspkills which provide and trains you in the correct way with proper knowledge & advance education.

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