### 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:* [ Ссылка ]
- *Yelp Dataset:* [ Ссылка ]
- *LinkedIn:* [ Ссылка ]
- *Medium:* [ Ссылка ]
- *GitHub:* [ Ссылка ]
- *Twitter:* [ Ссылка ]
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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
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