Big Data Training by Experts

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Our Training Process

Big Data - Syllabus, Fees & Duration

MODULE 1: Introduction to Big Data and Hadoop

  • Types of Digital Data
  • Introduction to Big Data
  • Big Data Analytics
  • History of Hadoop
  • Apache Hadoop
  • Analysing Data with Unix tools
  • Analysing Data with Hadoop
  • Hadoop Streaming
  • Hadoop Echo System
  • IBM Big Data Strategy
  • Introduction to Infosphere BigInsights
  • Big Sheets

MODULE 2: HDFS (Hadoop Distributed File System)

  • The Design of HDFS
  • HDFS Concepts
  • Command Line Interface
  • Hadoop file system interfaces
  • Data flow
  • Data Ingest with Flume and Scoop and Hadoop archives
  • Hadoop I/O: Compression
  • Serialization
  • Avro and File-Based Data structures

MODULE 3: Map Reduce

  • Anatomy of a Map Reduce Job Run
  • Failures, Job Scheduling
  • Shuffle and Sort
  • Task Execution
  • Map Reduce Types and Formats
  • Map Reduce Features

MODULE 4: Hadoop Eco System

  • Pig : Introduction to PIG
  • Execution Modes of Pig
  • Comparison of Pig with Databases
  • Grunt, Pig Latin
  • User Defined Functions
  • Data Processing operators
  • Hive : Hive Shell
  • Hive Services
  • Hive Metastore
  • Comparison with Traditional Databases
  • HiveQL
  • Tables
  • Querying Data and User Defined Functions
  • Hbase: HBasics
  • Concepts
  • Clients
  • Hbase Versus RDBMS
  • Big SQL: Introduction

MODULE 5: Data Analytics with R

  • Machine Learning: Introduction
  • Supervised Learning
  • Unsupervised Learning
  • Collaborative Filtering
  • Big Data Analytics with BigR.
  • Download Syllabus - Big Data
    This syllabus is not final and can be customized as per needs/updates
 
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Big Data Jobs in Bangalore

Enjoy the demand

Find jobs related to Big Data in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Bangalore, chennai and europe countries. You can find many jobs for freshers related to the job positions in Bangalore.

  • MIS Reporting Executive
  • Business Analyst
  • Data Analyst
  • Statistician
  • Data Scientist
  • Data Engineer
  • Data Architect
  • Machine Learning Engineer
  • Big Data Engineer
  • Big Data Solution Architect

Big Data Internship/Course Details

Big Data internship jobs in Bangalore
Big Data When evaluating all of the tools accessible in information technology today, Big Data is one of the most promising disciplines. The NESTSOFT Big Data course covers a wide range of topics in big data, including data generation, storage, management, and transfer, as well as analytics, with a focus on cutting-edge technologies, tools, architectures, and systems that make up big-data computing solutions in high-performance networks. Real-life As an illustration of the event, execution, and deployment of an enormous range of new big-data solutions, Big Data applications and workflows in many fields are provided as use cases. When it comes to seeking for the best jobs, having the Big Data certification can put you in a different group. Big Data is the newest and most promising technology for processing large amounts of data and performing data analytics. The advantages of Big Data include that it aids in the advancement of science and research, it enhances public health and healthcare through the availability of patient records, it aids in financial trading, and it is a single platform that can carry a limitless amount of data. You can land your dream positions like Data Engineer, Big Data Lead, Technical Program Manager, Big Data Developer, and Product Engineer by completing a Big Data certification course from location. Big data refers to methods for analysing, methodically extracting information from, or generally dealing with data collections that are too large or complicated for typical data-processing application software to handle. NESTSOFT Big Data Training is designed to turn you become a certified Big Data specialist by providing you with extensive hands-on experience. Python, JavaScript, and Java are among the languages utilised.

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