Big Data Course Highlights:
- The Big Data course will start with the basics of Linux which are required to get started with Big Data and then slowly progress from some of the basics of Hadoop/Big Data (like a Word Count program) to some of the advanced concepts around Hadoop/Big Data (like writing triggers/stored procedures to HBase).
- The main focus of the course will be on how to use the Big Data tools, but we will also focus on how to install and configure some of the Big Data related frameworks on in-premise and cloud based infrastructure.
- Because of the hype Hadoop is the news all the time. But, there are a lot of frameworks supporting Hadoop (like Pig/Hive) and a lot of frameworks which are alternatives to Hadoop (like Twitter Storm and LinkedIn Samza) to address the limitations of the MapReduce model. Some of these frameworks will also be discussed during the course to give a big picture of what Big Data is about.
- Also, time will be spent on NoSQL databases. Starting with why NoSQL instead of RDBMS databases to some of advanced concepts like importing data in bulk from a RDBMS to a NoSQL database. Different NoSQL databases will be compared and HBase will be discussed in much more detail.
- A VM (Virtual Machine) will be provided for all the participants with Big Data frameworks (Hadoop etc.) installed and configured on CentOS with data sets and code to process the same. The VM helps in making the Big Data learning experience less steeper.
- The training will help the participant get through the Cloudera Certified Developer for Apache Hadoop (CCDH) certification with minimal effort.
- Knowledge of Java is a definitive plus to get started with Big Data, but not mandatory. Hadoop provides streaming which allows programming MapReduce in non-Java languages like Perl, Python and there are also higher level abstracts like Hive/Pig which provides SQL like procedure type interface.
- Similarly knowledge of Linux would be a definitive plus but the basics of Linux just enough to get started with the different Big data frameworks.
- A laptop/desktop with minimum of 3GB RAM, 10 GB free HARD Disk and with a decent processor. These specifications would be enough to run the Big Data VM and the framework smoothly.
Who should Plan on joining this program
This course is designed for anyone who is
- Any Developer with skills in other technologies interested in getting into the emerging Big Data field.
- Any Data Analyst who would like to enhance/transfer their existing knowledge to the Big Data space.
- Any Architect who would like to design application in conjunction to Big Data or Big Data applications itself.
- Anyone involved in Software Quality Assurance (Testing). Knowledge of Hadoop will help them to test the application better and will also help them to move into the development cycle.
Core topics of BIG DATA - HADOOP Online Course
- Understanding Big Data
- HDFS (The Hadoop Distributed File System)
>> HDFS Overview and Architecture
>> How HDFS addresses fault tolerance?
>> HDFS Interfaces
>> Advanced HDFS features
- MapReduce – 1
>> MapReduce Overview
>> MapReduce Architecture
- MapReduce – 2
>> Developing, debugging and deploying MR programs
>> MR API
>> Optimizing techniques
>> MR algorithms
- NoSQL Databases
Watch BIG DATA - HADOOP Demo Video