🌟 Session Overview 🌟
Session Name: Sentiment Analysis in Action: Building Your Real-time Pipeline
Speaker: Olena Kutsenko
Session Description: Monitoring and interpreting the sentiment of data records is important for a variety of use cases. However, traditional human-based methods fall short in handling huge volumes of information with the required speed and efficiency. AI, however, can address this challenge.
AI is only part of the solution. We need to build a data pipeline that ingests data from various channels, processes it using AI-driven sentiment analysis models to classify the sentiment of each individual record, and prepares it to be consumed by applications for aggregation and analysis.
In this session, we'll build a system using open-source technologies Apache Kafka and Apache Flink with AI models to obtain real-time sentiment from social media data. Apache Kafka's scalability ensures that no record is left behind, making it a reliable foundation for sentiment analysis. Apache Flink, with its adaptability to fluctuations in data volume and velocity, will enable the analysis of a continuous data stream using an AI model.
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