Course Introduction

As a part of the big data developer, you will be required to execute real-life industry-based projects in the domains of banking, telecommunication, social media, insurance, and e-commerce. Keeping that as reference this Big Data Hadoop training course will prepare you for the Cloudera Certified Data Engineer and HADOOP DEVELOPERS PROFICIENT IN PIG, HIVE, SQOOP AND FLUME certification

What is Big Data?extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.


This program presents a unique opportunity to create a long term career in one of the fastest growing industries in the country.


Big data platform is a type of IT solution that combines.It is an enterprise class IT platform that enables organization in developing, deploying, operating and managing a big data infrastructure


Introduction

  • Big Data Overview
  • What is Big Data Analytics
  • Necessity for Big Data Analytics
  • Role of a Data Analyst
  • What is Data Science
  • Necessity for Data Science
  • Role of Data Scientist

Use Cases

  • Finance
  • Retail
  • Advertising
  • Defense and Intelligence
  • Telecommunications and Utilities
  • Healthcare and Pharmaceuticals

Data Analytics Proces

  • Preparation
  • PreProcessing
  • Analysis
  • Post Processing

Data Preparation

  • Planning
  • Data Collection
  • Data Selection

Data Preparation – Import/Export

  • Sqoop
  • Flume
  • Hands on Exercise : Usage of Tools

PreProcessing

  • Data Cleaning
  • Data Filtering
  • Data Completion
  • Data Correction
  • Data Standardization
  • Data Transformation
  • Tools for Data PreProcessing
  • Data Preprocessing using Pig
  • Writing Pig Latin scripts and processing data
  • Data Preprocessing using Hive
  • Writing Hive Scripts and processing data
  • Hands on Exercise : Pig and Hive

Data Analysis Introduction

  • Recommendation
  • Classification
  • Clustering
  • Mahout

Recommendataion

  • Introduction to Recommendations
  • Making recommendations, various techniques
  • Hands on Exercise for Recommendations

Classification

  • Classification System Overview
  • Classification process
  • Naive Bayes Classifier
  • Descision Trees
  • Examples of Classification
  • Clustering
  • Clustering basics
  • Hierarchical clustering
  • K-Means clustering
  • Running clustering example
  • Exploring distance measures

Data Visualization using R

  • Language basics
  • Data Frames
  • Vectorized operations on Data Frames
  • Selection
  • Projection
  • Transformation

 

 

 

 

 

 

 

 

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