Fundamentals Of Big Data
- Created By raju2006
- Last Updated December 21st, 2023
- Overview
- Prerequisites
- Audience
- Audience
- Curriculum
Description:
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.
Long Description:
Unleash the potential of Big Data Ecosystem technologies with our comprehensive training course. Gain a solid introduction to HDFS, MapReduce, Sqoop, Flume, Hive, Pig, Mahout for Machine Learning, R Connector, Ambari, Zookeeper, Oozie, and No-SQL solutions like HBase, essential for Big Data scenarios. This course offers an in-depth understanding of the Big Data ecosystem both before and after the Apache Spark era. Dive into Spark's core fundamentals and architecture, and set up an account on Apache Spark Databricks Cloud for hands-on big data analysis exercises. Equip yourself with the skills to thrive in the world of Big Data and Apache Spark, where opportunities for data-driven innovation abound
Course Code/Duration:
BDT29 / 1 Day
Learning Objectives:
After this course, you will be able to:
- 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.
- Provide an explanation of the ecosystem components like HDFS, MapReduce, Sqoop, Flume, Hive, Pig, Mahout (Machine Learning), R Connector, Ambari, Zookeeper, Oozie and No-SQL like HBase.
- Understand the various offerings like Cloudera, Hortonworks, MapR, Amazon EMR and Microsoft Azure HDInsight in the industry around Big data on cloud and on Premise.
- Understand the impact and value of Apache Spark in the Big Data Ecosystem.
- Understand the Apache Spark Architecture and the various libraries to perform various use cases like Streaming, Machine & Deep Learning, GraphX etc.
- Setup Account on Apache Spark Databricks Cloud.
- Perform hands-on activity on Big Data Ecosystem.
- Basic Programming knowledge, SQL and Data knowledge preferred
- Data Analyst, SQL Developers,Database Administrator, Database Developers, Aspiring Data Warehouse Professionals
- Data Analyst, SQL Developers,Database Administrator, Database Developers, Aspiring Data Warehouse Professionals
Course Outline:
- Course Introduction
- History and background of Big Data and Hadoop
- 5 V’s of Big Data
- Secret Sauce of Big Data Hadoop
- Big Data Distributions in Industry
- Big Data Ecosystem before Apache Spark
- Big Data Ecosystem after Apache Spark
- Comparison of MapReduce Vs Apache Spark
- Big Data Ecosystem after Apache Spark
- Understand Apache Architecture and Libraries like Streaming, Machine & Deep Learning, GraphX etc.
- Hands-on exercise 1 – Setup Account on Apache Spark Databricks Cloud.
- Hands-on exercise 2 – First Spark Program
- Hands-on exercise 3 – Spark RDD Transformation & Actions
- Hands-on exercise 4 – Spark RDD Advanced Transformation & Actions
- References and Next steps
Structured Activity/Exercises/Case Studies:
- Exercise 1 – Setup Account on Apache Spark Databricks Cloud.
- Exercise 2 – First Spark Program
- Exercise 3 – Spark RDD Transformation & Actions
- Exercise 4 – Spark RDD Advanced Transformation & Actions
Training material provided:
Yes (Digital format)
