Introduction To Big Data
Introduction To Big Data
Big Data is a collection of data that is huge in volume, yet growing exponentially with time. It is a data with so large size and complexity
Reedem
What you'll 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
Requirements
- Basic Programming knowledge, SQL and Data knowledge preferred
- Description
- 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)
Who this course is for:
- This course is designed for anyone willing to develop a foundation for Big Data.
