Master Big Data Hadoop

In this course we will explore what Big Data is? What Hadoop is? and everything that comes under in Big Data in minimum time. The main goal of this course is to help you understand the Complex Architectures of Hadoop and its components. 

It covers everything what you need to master Big Data. You will learn about Big Data market, Big data systems life cycle, Commercial Hadoop distributions, use of Big Data in Business, technology trends, HDFS, Hadoop Ecosystem, Hive,  and Pig. In this course, we will see how as a beginner one should start with Hadoop. We will understand with a lot of hands-on examples which will help you to learn Hadoop quickly.

Become an EXPERT and learn what & how Big Data is changing the world.

The course focuses on-

• What Big data is? 
• In-memory technology 

  
  

  • What is In-memory database (IMDB)? 
    • Hardware technology advances adopted for In-memory system
      • Software technology advances adopted for In-memory systems 

1.  Data compression 
   
2. No aggregate tables 
   
3. Insert-only tables 
   
4. Column, row, and hybrid storage 
   
5. Partitioning 
   

• What are NoSQL databases? 

  
  

  • Benefits of NoSQL
• Data visualization
  • Data visualization application 
• Data science

HADOOP ECOSYSTEMS

• Big data Hadoop ecosystems 

  Inbuilt tools and capabilities in Hadoop ecosystem 
  

Big data clusters 

• Usage of Hadoop big data cluster 

• High availability 

• Load balancing 

• High availability and load balancing 

• Distributed processing and parallel processing 

• Hadoop big data cluster nodes 
  • Types of nodes and their roles
• Commercial Hadoop distributions 
  • Hadoop Cloudera enterprise distribution  
  • A Hadoop Hortonworks framework
  • A Hadoop MapR framework
  • Pivotal Hadoop platform HD Enterprise 
  • A Hadoop ecosystem on IBM big data 
  • A Hadoop ecosystem on AWS
  • Microsoft Hadoop platform is HDInsight hosted on Microsoft Azure
• Capacity planning for systems 

  
  

  • Guideline for estimating and capacity planning 
  • Cluster-level sizing estimates

Comming Soon:

 Building Big Data Applications