Videos
Each project comes with 2-5 hours of micro-videos explaining the solution.
Code & Dataset
Get access to 50+ solved projects with iPython notebooks and datasets.
Project Experience
Add project experience to your Linkedin/Github profiles.
Each project comes with 2-5 hours of micro-videos explaining the solution.
Get access to 50+ solved projects with iPython notebooks and datasets.
Add project experience to your Linkedin/Github profiles.
Lately, the phrase "ETL is dead" has become more popular. But that statement is flatly false. It should rather have been "Batch ETL is growing unpopular". Companies now believe not only in the power of data but also in the power of current-ness of data. This means that a dashboard that reveals sales pattern for yesterday is less correct than one that shows sales pattern in the last 30 minutes.
Kafka is a scalable and distributed streaming and messaging platform is a great choice for building today's ETL pipeline.
In this big data kafka project, we will see this in theory as well as implementation. We will see how data ingestion and loading is done with Kafka connect APIs while transformation will be done with Kafka Streaming API. But this is not all.
In this project, we will show how to build an ETL pipeline on streaming datasets using Kafka.
In this hadoop project, you will be using a sample application log file from an application server to a demonstrated scaled-down server log processing pipeline.
Hadoop Projects for Beginners -Learn data ingestion from a source using Apache Flume and Kafka to make a real-time decision on incoming data.