
During March 2025, 21pt38@psgtech.ac.in developed the initial streaming pipeline for the TCS-2021/Data-Mining-Project, focusing on weather data ingestion. They established a Kafka-based architecture using Python, implementing a fully functional consumer that reads messages from a designated topic. The producer scaffold was designed to fetch weather data from an external API and prepare it for future message publishing, currently outputting data as a placeholder. This work laid the architectural foundation for near real-time analytics and downstream model updates. The effort emphasized modular pipeline design, API integration, and basic observability, setting the stage for robust data-driven decision making in subsequent sprints.

2025-03 monthly summary for TCS-2021/Data-Mining-Project: Delivered the initial streaming pipeline scaffolding for weather data ingestion. The Kafka consumer is fully functional and reads messages from a topic. A producer scaffold fetches weather data from an external API and prepares it for publishing; the current producer prints data as a placeholder for actual message production. This work establishes end-to-end streaming groundwork enabling near real-time analytics and faster iteration, with the next sprint focusing on integrating a full publish path and error handling. No major defects fixed this month; the focus was on architecture, stability, and scaffolding. The effort lays the foundation for downstream analytics, model updates, and data-driven decision making. Technologies demonstrated include Kafka streaming patterns, API integration, modular pipeline design, and basic observability scaffolding.
2025-03 monthly summary for TCS-2021/Data-Mining-Project: Delivered the initial streaming pipeline scaffolding for weather data ingestion. The Kafka consumer is fully functional and reads messages from a topic. A producer scaffold fetches weather data from an external API and prepares it for publishing; the current producer prints data as a placeholder for actual message production. This work establishes end-to-end streaming groundwork enabling near real-time analytics and faster iteration, with the next sprint focusing on integrating a full publish path and error handling. No major defects fixed this month; the focus was on architecture, stability, and scaffolding. The effort lays the foundation for downstream analytics, model updates, and data-driven decision making. Technologies demonstrated include Kafka streaming patterns, API integration, modular pipeline design, and basic observability scaffolding.
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