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BigData

Big Data Training In Noida

Big Data Training Modules-

Big Data Analytics with Data Science Course Content

  • 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 Process

  • Preparation
  • PreProcessing
  • Analysis
  • Post Processing

Data Preparation

  • Planning
  • Data Collection
  • Data Selection

Tools for Data Preparation

  • Introduction to SQL DB’s
  • Introduction to NoSql DB’s
  • Key / Value pair
  • MongoDB
  • Cassandra
  • Graph DB’s (Neo4j)
  • Hands on Exercise : Using SQL and NoSql DB’s

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

Security & Access

  • Create & Manager Users
  • Set organization-wide defaults
  • Learn about record accessed
  • Create the role hierarchy
  • Learn about role transfer & mass Transfer functionality
  • Profiles, Login History

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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