Introduction To Big Data

Introduction To Big Data, available at $54.99, with 14 lectures.

You will learn about Introduction To Big Data Understand the History and background of Big data and Hadoop Describe the Big Data landscape including examples of real world big data problems Explain the 5 V’s of Big Data (volume, velocity, variety, veracity, and value Understand the foundational principles that have made Big Data so successful This course is ideal for individuals who are This course is designed for anyone willing to develop a foundation for Big Data. It is particularly useful for This course is designed for anyone willing to develop a foundation for Big Data.

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Summary

Title: Introduction To Big Data

Price: $54.99

Number of Lectures: 14

Number of Published Lectures: 14

Number of Curriculum Items: 14

Number of Published Curriculum Objects: 14

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

Introduction To Big Data

Understand the History and background of Big data and Hadoop

Describe the Big Data landscape including examples of real world big data problems

Explain the 5 V’s of Big Data (volume, velocity, variety, veracity, and value

Understand the foundational principles that have made Big Data so successful

Who Should Attend

This course is designed for anyone willing to develop a foundation for Big Data.

Target Audiences

This course is designed for anyone willing to develop a foundation for Big Data.

Overview :The Introduction to Big Data course is the first stop in the Big Data curriculum series coming up at Stanford. It will help you get started with the background and introduction of the history of the Big Data.

Description:

The ‘Introduction to Big Data’ course is your gateway to the dynamic world of Big Data and Spark. Dive into the history and fundamentals of Big Data, gaining insights into Big Data Ecosystem technologies, including HDFS, MapReduce, Sqoop, Flume, Hive, Pig, Mahout for Machine Learning, R Connector, Ambari, Zookeeper, Oozie, and No-SQL tools like HBase. This course offers an in-depth understanding of the Big Data ecosystem, both pre and post Apache Spark era. Learn the core fundamentals and architecture of Spark and put your knowledge into practice on the Apache Spark Databricks Cloud. Get started on your Big Data journey.

Learning Outcome : In this Course you’ll get an introduction to working with Big Data Ecosystem technologies (HDFS, MapReduce, Sqoop, Flume, Hive, Pig, Mahout (Machine Learning), R Connector, Ambari, Zookeeper, Oozie and No-SQL like HBase) for Big Data scenarios.

Understand the History and background of Big data and Hadoop

Describe the Big Data landscape including examples of real world big data problems

Explain the 5 V’s of Big Data (volume, velocity, variety, veracity, and value)

Course Curriculum

Chapter 1: Introduction

Lecture 1: Data Types

Lecture 2: V Views of Big Data

Lecture 3: History of Hadoop

Lecture 4: What is Hadoop

Lecture 5: Hadoop Eco System & Hadoop Components

Lecture 6: Big Data Ecosystem

Lecture 7: Big Data Storage

Lecture 8: Big Data Flavor

Lecture 9: Big Data on Cloud

Lecture 10: Spark EssentialIn (Challenges with Mapreduce)

Lecture 11: What is Apache Spark

Lecture 12: Big Data after Spark Ecosystem

Lecture 13: Spark Feature & Spark Components

Lecture 14: Spark Landscape (Spark in Databricks)

Instructors

Big Data Trunk
All about Big Data and Hadoop

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Frequently Asked Questions

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