Fluke Infotech - Big Data Hadoop

This Big Data Hadoop training lets you master the concepts of the Hadoop framework and prepares you for Cloud era Big data . With our online Hadoop training, you’ll learn how the components of the Hadoop ecosystem, such as Hadoop 2.7, Yarn, Map Reduce, HDFS, Pig, Impala, HBase, Flume, Apache Spark, etc. fit in with the Big Data processing lifecycle. Implement real-life projects in banking, telecommunication, social media, insurance, and e-commerce on Cloud Lab.

 

Course description

Why Learn Big Data and Hadoop ?

The world is getting increasingly digital, and this means big data is here to stay. In fact, the importance of big data and data analytics is going to continue growing in the coming years. Choosing a career in the field of big data and analytics might just be the type of role that you have been trying to find to meet your career expectations. Professionals who are working in this field can expect an impressive salary, with the median salary for data scientists being $116,000. Even those who are at the entry level will find high salaries, with average earnings of $92,000. As more and more companies realize the need for specialists in big data and analytics, the number of these jobs will continue to grow. Close to 80% of data scientists say there is currently a shortage of professionals working in the field.

Big Data Hadoop training course lets you master the concepts of the Hadoop framework and prepares you for Cloud era’s. With our Hadoop training, you’ll learn how the components of the Hadoop ecosystem, such as Hadoop 2.7, Yarn, Map Reduce, HDFS, Pig, Impala, HBase, Flume, Apache Spark, etc. fit in with the Big Data processing lifecycle. Implement real life projects in banking, telecommunication, social media, insurance, and e-commerce on Cloud Lab.

Key features of the course-

·         40 hours of instructor-led training

·         real-life industry projects examples using Hadoop and Spark

·         Hands-on practice

·         Training on Yarn, MapReduce, Pig, Hive, Impala, HBase, and Apache Spark.