Objectives

• Candidates will be introduced to Big Data architectures, infrastructures, as well as tools and techniques for data analysis. They will explore issues relating to Big Data management and develop specialist knowledge and understanding relating to the storage, data and programming interface models used for Big Data.

Outcomes

Learn how to manage Hadoop clusters with YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie Publish data to your Hadoop cluster with Kafka, Sqoop, and Flume Consume data streams with Spark Streaming, Flink, and Storm

Course Contents

- Big Data Enabling Technologies- Hadoop Stack for Big Data- Hadoop Distributed File System (HDFS)- Hadoop MapReduce- Parallel Programming with Spark- Spark Built-in Libraries- Data Placement Strategies- Design of Zookeeper- CQL (Cassandra Query Language)- Design of HBase- Spark Streaming and Sliding Window Analytics- Kafka

Description

Data will be available soon!