The Ultimate Hands-On Hadoop - Tame your Big Data!
Learn to design distributed systems that manage "big data" using Hadoop and related technologies. Master HDFS and MapReduce for storing and analyzing data at scale. Create scripts to process data on a Hadoop cluster using Pig and Spark. Analyze relational data using Hive and MySQL, and non-relational data using HBase, Cassandra, and MongoDB. Query data interactively with Drill, Phoenix, and Presto. Choose the right data storage technology for your application. Understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie. Publish data to your Hadoop cluster using Kafka, Sqoop, and Flume. Consume streaming data using Spark Streaming, Flink, and Storm. Take the ultimate hands-on Hadoop course and tame your big data! ▼
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Course Feature
Cost:
Paid
Provider:
Udemy
Certificate:
No Information
Language:
English
Start Date:
Self Paced
Course Overview
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Updated in [June 30th, 2023]
This course provides an in-depth overview of Hadoop and related technologies. Participants will learn how to design distributed systems that manage "big data" using Hadoop and related technologies. Topics covered include HDFS and MapReduce for storing and analyzing data at scale, Pig and Spark for creating scripts to process data on a Hadoop cluster in more complex ways, and Hive and MySQL for analyzing relational data. Additionally, participants will learn how to analyze non-relational data using HBase, Cassandra, and MongoDB, query data interactively with Drill, Phoenix, and Presto, choose an appropriate data storage technology for their application, and understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie. Finally, participants will learn how to publish data to their Hadoop cluster using Kafka, Sqoop, and Flume, and consume streaming data using Spark Streaming, Flink, and Storm.
[Applications]
After this course, participants can apply their knowledge of Hadoop and related technologies to design distributed systems that manage "big data". They can use HDFS and MapReduce for storing and analyzing data at scale, Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways, and Hive and MySQL to analyze relational data. Participants can also analyze non-relational data using HBase, Cassandra, and MongoDB, query data interactively with Drill, Phoenix, and Presto, and choose an appropriate data storage technology for their application. Additionally, participants can understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie, and publish data to their Hadoop cluster using Kafka, Sqoop, and Flume. Finally, they can consume streaming data using Spark Streaming, Flink, and Storm.
[Career Path]
One job position path that is recommended for learners of this course is a Hadoop Developer. A Hadoop Developer is responsible for designing, developing, and maintaining distributed systems that manage "big data" using Hadoop and related technologies. They must be able to use HDFS and MapReduce for storing and analyzing data at scale, as well as use Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways. They must also be able to analyze relational data using Hive and MySQL, analyze non-relational data using HBase, Cassandra, and MongoDB, query data interactively with Drill, Phoenix, and Presto, choose an appropriate data storage technology for an application, understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie, publish data to a Hadoop cluster using Kafka, Sqoop, and Flume, and consume streaming data using Spark Streaming, Flink, and Storm.
The development trend for Hadoop Developers is that they will be increasingly in demand as the need for big data solutions grows. Companies are increasingly looking for ways to store, process, and analyze large amounts of data, and Hadoop Developers are the ones who can provide these solutions. As such, the demand for Hadoop Developers is expected to continue to grow in the coming years.
[Education Path]
The recommended educational path for learners of this course is to pursue a Bachelor's degree in Computer Science with a specialization in Big Data. This degree will provide learners with the necessary skills and knowledge to design, develop, and manage distributed systems that manage large amounts of data. Learners will gain an understanding of the various technologies used in Big Data, such as HDFS, MapReduce, Pig, Spark, Hive, MySQL, HBase, Cassandra, MongoDB, Drill, Phoenix, Presto, YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, Oozie, Kafka, Sqoop, and Flume. They will also learn how to query data interactively and publish data to a Hadoop cluster.
The development trend of this degree is to focus on the use of artificial intelligence and machine learning to analyze and process large amounts of data. Learners will gain an understanding of the various algorithms used in AI and ML, as well as the tools and technologies used to implement them. They will also learn how to use AI and ML to create predictive models and make decisions based on the data. Additionally, learners will gain an understanding of the ethical implications of using AI and ML in Big Data.
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