AICouncil certified Training and certification program will let you understand Big Data Hadoop and Spark with around 15 real-time industry oriented project development. This course has been designed with MapReduce, Hive, Pig, Sqoop, Oozie and Flume and work with Amazon EC2 for cluster setup, Spark framework and RDD, Scala and Spark SQL, Machine Learning using Spark, Spark Streaming, etc. It’s a training which is designed by industry experts to let you prepared for Cloudera CCA Spark and Hadoop Developer Certification (CCA175) and current job requirements. Your certificate will be industry recognized as Hadoop developer, Hadoop administrator, Hadoop testing and analytics with Apache Spark.
Use the data of airlines services in India in terms of routes covered and operational airports to analyse list of operating airports in India with maximum stops and minimum stops. As well as finding out the territory with highest number of airports and active airlines in cross ponding territory. This analysis will lead to match the demand of airline service requirement in a particular area.
Here you will use IMDB movie rating data set to analyse top rated movies using MapReduce program. Main highlight of the program is the use of Apache PIG and Apache Hive with Mapreduce for analysing, warehousing and querying the data.
This project will be implemented with Hive table data partitioning to ensure right partitioning helps to read the data, deploy it on the HDFS and run the MapReduce jobs at a much faster rate. You can do Data partition in multiple ways to deploy single SQL execution in Dynamic partition and bucketing of data.
In this project you will connect Pentaho with Hadoop ecosystem which works well with HDFS, HBase, Oozie and ZooKeeper. You will connect the Hadoop cluster with Pentaho data integration, analytics, Pentaho server and report designer. This project will develop an experience with Working knowledge of ETL and Business Intelligence along with Configuring Pentaho to work with Hadoop distribution.
In this project you will have hands on experience with bringing daily data into Hadoop Distributed File system. We have transaction data which is daily recorded/stored in the RDBMS. Now this data is transferred everyday into HDFS for further Big Data Analytics. You will work on live Hadoop YARN cluster which is a part of the Hadoop ecosystem that lets Hadoop to decouple from MapReduce and deploy more competitive processing and wider array of applications.
With this project you will know how to work on real world Hadoop multi-node cluster setup in a distributed environment. You will get a complete demonstration of working with various Hadoop cluster master and slave nodes, installing Java as a prerequisite for running Hadoop, installation of Hadoop and mapping the nodes in the Hadoop cluster. You will be mostly focused over multimode clustering on Amazon EC2 and deployment of MapReduce job on Hadoop cluster.
In this project you will be focused over making sense of all web log data to derive meaning full insights from it. Here you need to work with loading server data which includes various URLs visited, cookie data, user demographics, location, date and time of web service access, etc into Hadoop cluster using various techniques. you will transport the data using Apache Flume or Kafka, workflow and data cleansing using MapReduce, Pig or Spark. The insight thus derived can be used for analyzing customer behavior and predict buying patterns.
This project will let you use Spark SQL tool for analysing the WikiPedia Data with hands on experience in integrating Spark SQL for various applications like batch analysis, Machine Learning, visualizing and processing of data and ETL processes, along with real-time analysis of data.
There is no such prerequisite if you are enrolling for Master’s Course as everything will start from scratch. Whether you are a working IT professional or a fresher you will find a course well planned and designed to incorporate trainee from various professional backgrounds.