Building a Real-Time Data Streaming Pipeline | End to End Project with Kafka Spark and Elasticsearch

Technologies Featured:

#ConfluentKafka #Elasticsearch #MongoDB #ApacheSpark #HuggingFace #DataFlow

Overview:

In this video, you’ll learn how to construct a real-time data streaming pipeline using a dataset of 7 million records . We’ll harness a robust stack of tools and technologies, including Apache Spark, MongoDB Atlas, HuggingFace's DistilBERT Text-Classification Model, Confluent Kafka, Elasticsearch, and Kibana.

What You'll Learn:

How to set up and configure a Kafka topic for seamless data transmission in Kaggle Notebooks.
Streaming data from Kafka topics using Apache Spark.
Performing real-time sentiment analysis with HuggingFace models.
Establishing Kafka for efficient real-time data ingestion and distribution.
Utilizing Elasticsearch for enhanced data indexing and search capabilities.

Resources:

GitHub Repository: https://github.com/akarce/real-time-d...
Yelp Dataset: https://www.kaggle.com/datasets/yelp-...
LinkedIn:   / akarce  
Medium:   / akarce  
GitHub: https://github.com/akarce
Twitter: https://x.com/akarcey

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Tags:

Data Engineering, Kafka, Apache Spark, ETL Pipeline, Data Pipeline, Big Data, Streaming Data, Real-Time Analytics, Kafka Connectors, Schema Registry, Control Center, Machine Learning Integration, Data Visualization, Stream Processing.

Hashtags:

#Confluent #DataEngineering #Kafka #ApacheSpark #ETLPipeline #DataPipeline #DataStreaming #HuggingFace #Elasticsearch #RealTimeData #BigData #TechTutorial #StreamingAnalytics #MachineLearning #DataFlow #SparkStreaming #DataScience #AIIntegration #RealTimeAnalytics #StreamingData #RealTimeStreaming