What are the pre-requisites for big data hadoop?

Working directly with Java APIs can be tedious and error prone. It also restricts usage of Hadoop to Java programmers. Hadoop offers two solutions for making Hadoop programming easier.

Pig is a programming language that simplifies the common tasks of working with Hadoop: loading data, expressing transformations on the data, and storing the final results. Pig’s built-in operations can make sense of semi-structured data, such as log files, and the language is extensible using Java to add support for custom data types and transformations.

Hive enables Hadoop to operate as a data warehouse. It superimposes structure on data in HDFS and then permits queries over the data using a familiar SQL-like syntax. As with Pig, Hive’s core capabilities are extensible.
Choosing between Hive and Pig can be confusing. Hive is more suitable for data warehousing tasks, with predominantly static structure and the need for frequent analysis. Hive’s closeness to SQL makes it an ideal point of integration between Hadoop and other business intelligence tools.

What skills are required?

So we realize that Big Data is enormous, no quip proposed. We realize that it is driving employment development.

What do you have to know and what aptitude would it be advisable for you to have in the event that you need to seek after a Big Data vocation?

Big Data jobs ordinarily oblige an expansive reach of aptitudes. The uplifting news for tech-adroit force clients and business-clients is that a considerable lots of the employments don’t oblige in-your-face programming abilities but instead oblige business or other jobs particular information, solid systematic aptitudes, and learning of analytic tools.