Big Data training course content and Syllabus in chennai


Big data is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process using traditional data processing applications.

What is Big Data?

Every day, we create 2.5 quintillion bytes of data - so much that 90% of the data in the world today has been created in the last two years alone.

Gartner defines Big Data as high volume, velocity and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.

According to IBM, 80% of data captured today is unstructured, from sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals, to name a few. All of this unstructured data is Big Data.

Big data spans three dimensions: Volume, Velocity and Variety. Volume: Enterprises are awash with ever-growing data of all types, easily amassing terabytes - even petabytes - of information.

Turn 12 terabytes of Tweets created each day into improved product sentiment analysis Convert 350 billion annual meter readings to better predict power consumption Velocity: Sometimes 2 minutes is too late. For time-sensitive processes such as catching fraud, big data must be used as it streams into your enterprise in order to maximize its value.

Scrutinize 5 million trade events created each day to identify potential fraud Analyze 500 million daily call detail records in real-time to predict customer churn faster Variety: Big data is any type of data - structured and unstructured data such as text, sensor data, audio, video, click streams, log files and more. New insights are found when analyzing these data types together.

Monitor 100's of live video feeds from surveillance cameras to target points of interest Exploit the 80% data growth in images, video and documents to improve customer satisfaction

About Trainer

He is having 10+ year of experience big data.He accept any challenge that comes my way with an open attitude and reinforce my belief that being versatile is the way to success and growth of self and organization.

Introduction to Big Data

  • Big Data
  • What is Big Data?
  • Why all industries are talking about Big Data?
  • What are the issues in Big Data?
  • Storage
  • What are the challenges for storing big data?
  • Processing
  • What are the challenges for processing big data?
  • What are the technologies support big data?
  • Hadoop
  • Data Bases
  • Traditional
  • NO SQL
  • 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
  • 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
  • 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
  • Course Features & Benefits:-

  • Experienced Corporate Trainer
  • Additional Practice sessions
  • Learning day to day operations.
  • Lowest Fee
  • Full Course covering every advanced topic
  • Individual attention
  • VKV Training Benefits

  • Training by Real Time Professionals
  • Project Oriented Training
  • Running Notes
  • Flexible Timings
  • Excellent Lab Facility
  • Small Training Batch
  • Certification Support
  • About Us Small Desc of VKV

    VKV technologies(p) ltd has been founded in 2012 with a vision of providing quality training in Oracle related technologies. Our mission of is to continuously honne the skills of industrial workforces for higher productivity. Bridging the gap between academics and industries for suitable placement in technical field.

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