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Processes for merging data files and filtering fields to reduce memory footprint before database ingestion.
Distinct from Dataset Preparation Scripts: Focuses on memory optimization and field filtering for analysis, whereas Dataset Preparation Scripts focus on downloading and organizing public datasets.
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This project is a collection of big data frameworks and pipelines, including an Apache Hive analysis framework, a behavioral data analytics platform, a predictive analytics engine, and real-time data pipelines. It provides the infrastructure for building Extract, Transform, Load (ETL) workflows to process large datasets for distributed storage and SQL-based analysis. The system supports diverse analytical implementations, such as a predictive engine using linear regression for value forecasting and a real-time architecture that moves data through message brokers for immediate reporting. It in
Includes processes to merge data files and filter fields to optimize memory usage before loading into databases.