Requirements
-
Basic understanding of Programming Language
-
Basic understanding of Apache Hadoop
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Basic understanding of Apache Spark
Description
- In many data centers, different type of servers generate large amount of data(events, Event in this case is status of the server in the data center) in real-time.
- There is always a need to process these data in real-time and generate insights which will be used by the server/data center monitoring people and they have to track these server’s status regularly and find the resolution in case of issues occurring, for better server stability.
- Since the data is huge and coming in real-time, we need to choose the right architecture with scalable storage and computation frameworks/technologies.
- Hence we want to build the Real Time Data Pipeline Using Apache Kafka, Apache Spark, Hadoop, PostgreSQL, Django and Flexmonster on Docker to generate insights out of this data.
- The Spark Project/Data Pipeline is built using Apache Spark with Scala and PySpark on Apache Hadoop Cluster which is on top of Docker.
- Data Visualization is built using Django Web Framework and Flexmonster.
Who this course is for:
- Beginners who want to learn Apache Spark/Big Data Project Development Process and Architecture
- Beginners who want to learn Real Time Streaming Data Pipeline Development Process and Architecture
- Entry/Intermediate level Data Engineers and Data Scientist
- Data Engineering and Data Science Aspirants
- Data Enthusiast who want to learn, how to develop and run Spark Application on Docker
- Anyone who is really willingness to become Big Data/Spark Developer
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