Audience Course Hadoop for Big Data
The course Hadoop for Big Data is intended for developers, data analysts and others who want to learn how to process data with Hadoop.
Prerequisites training Hadoop for Big Data
To participate in this course prior knowledge of programming in Java and databases is beneficial for the understanding. Prior knowledge of Java or Hadoop is not necessary.
Realization Course Hadoop for Big Data
The theory is treated on the basis of presentations. Illustrative demos are used to clarify the covered concepts. There is ample opportunity to practice and theory and practice are interchanged. The course times are from 9.30 to 16.30.
Official Certificate Course Hadoop for Big Data
Participants receive an official certificate Hadoop for Big Data after successful completion of the course.
Course Hadoop for Big Data
In the course Hadoop for Big Data participants learn how to use Apache Hadoop for the storage and processing of large amounts of data. Hadoop uses a simple programming model in a distributed environment over a cluster of computers. The architecture of Hadoop is explained in depth. The Hadoop Distributed File System (HDFS) is used as file system within a Hadoop cluster. HDFS is a horizontal scalable file system that is stored on a cluster of servers. The data is stored in a distributed manner and the file system automatically ensures replication of data over the cluster. An important algorithm for the processing of data is the MapReduce algorithm and this is given extensive attention. Finally attention is paid to tools and utilities that are often used in combination with Hadoop such as Zookeeper, Scoop, Ozie and Pig.