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Big data and Hadoop framework
Rating: 4.0 out of 5(512 ratings)
18,394 students

Big data and Hadoop framework

Big data applications, Hadoop Architecture , Data lake, data science and scientist, Demo
Created byKaushik Vadali
Last updated 6/2018
English

What you'll learn

  • Understand Big data technologies, Data analytics and Hadoop framework

Course content

2 sections • 14 lectures • 1h 12m total length

  • Big data Introduction5:33

    Explore the big data landscape, its huge volume, high velocity, and varied formats, and see how analytics, data storage, and predictive analytics enable smarter decisions across industries.

  • 1.2 Big data history5:33

    Trace the history of big data—from defining high volume, velocity, variety, and veracity to evolving architectures like map reduce and Hadoop that enable real-time, distributed data processing.

  • 1.3 Big data technologies3:14

    Explore the big data technologies and ecosystem, including machine learning, natural language processing, business intelligence, cloud computing, and distributed databases, to enable accurate analysis and better decision making.

  • 1.4 Big data characteristics5:33

    Explore the five big data characteristics—volume, velocity, variety, veracity, and value—and how cognitive big data, advanced analytics, and cloud computing enable real-time, contextual insights.

  • 1.5 Big data Applications5:46

    Explore how big data applications drive cost savings, productivity, and innovation across manufacturing, healthcare, education, and media, enabling predictive tools and personalized medication for future planning.

  • 1.6 Data Lake4:43

    Discover how a data lake acts as a centralized, scalable store for all data types, enabling dashboards, analytics, and machine learning with Hadoop and Spark.

  • 1.7 Data science and Data scientist7:39

    Explore data science as an interdisciplinary field applying statistics, machine learning, and data mining to collect, clean, analyze data, and build predictive models for big data decisions.

Requirements

  • Basic computer knowledge, a bit of Java, database concepts and Linux operating system.

Description

This course is focusing on Big data and Hadoop technologies, hands on demos, 

Section 1 - Big data 

 1.1 Big data introduction

1.2 Big data history

1.3 Big data technologies

1.4 Big data characteristics

1.5 Big data Applications

1.6 Data Lake

1.7 Data Science and Data scientist

Section 2 - Hadoop

2.1 - Hadoop introduction

2.2 - HDFS-Overview

2.3 - Hadoop Architecture

2.3a - Hadoop Architecture - assumptions and goals   

2.4 - Demo-Hadoop install - sw download verify integrity   

2.5 - Demo-Hadoop install - Java ssh configure   

2.6 - Demo hadoop access by browser

Who this course is for:

  • Anyone who is interested in learning Big data, Data analytics and Hadoop Framework

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