In this video, you will be building a real-time data streaming pipeline, covering each phase from data ingestion to processing and finally storage. We'll utilize a powerful stack of tools and technologies, including Apache Airflow, Python, Apache Kafka, Apache Zookeeper, Apache Spark, and Cassandra—all neatly containerized using Docker.

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📚 What You'll Learn:
👉 Setting up a data pipeline with Apache Airflow
👉 Streaming data with Kafka and Kafka Connect
👉 Using Zookeeper for distributed synchronization
👉 Data processing with Apache Spark
👉 Data storage solutions with Cassandra and PostgreSQL
👉 Containerizing your data engineering environment with Docker

✨ Timestamps: ✨
0:00 Introduction
0:53 System architecture
3:47 Getting data from API with Airflow
17:10 Docker Compose for the architecture
26:09 Streaming data into Kafka
44:29 Apache Spark and Cassandra setup
49:33 Streaming data into cassandra
1:27:05 Outro

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🔗 Useful Links and Resources:
✅ Code: https://github.com/airscholar/e2e-dat...
✅ Medium Article:   / realtime-data-engineering-project-with-air...  
✅ Docker Compose Documentation: https://docs.docker.com/compose/
✅ Apache Kafka Official Site: https://kafka.apache.org/
✅ Apache Spark Official Site: https://spark.apache.org/
✅ Apache Airflow Official Site: https://airflow.apache.org/
✅ Cassandra: https://cassandra.apache.org/
✅ Confluent Docs: https://docs.confluent.io/home/overvi...


✨ Tags ✨
Data Engineering, Apache Airflow, Kafka, Apache Spark, Cassandra, PostgreSQL, Zookeeper, Docker, Docker Compose, ETL Pipeline, Data Pipeline, Big Data, Streaming Data, Real-time Analytics, Kafka Connect, Spark Master, Spark Worker, Schema Registry, Control Center, Data Streaming

✨ Hashtags ✨
#confluent #DataEngineering #ApacheAirflow #Kafka #ApacheSpark #Cassandra #PostgreSQL #Docker #ETLPipeline #DataPipeline #StreamingData #RealTimeAnalytics