GitHub - Lazeeez/ETL-Batch-Processing: Today, big data is generated from many sources and there is a huge demand for storing, managing, processing, and querying on big data. The Map Reduce model and its counterpart open source implementation Hadoop, has proven itself as the solution to big data processing. Hadoop is inherently designed for batch and high throughput processing jobs. The term ETL which stands for Extraction, Transformation, and Loading is a batch or scheduled data integration process that includes extracting data from their operational or external data sources, transforming the data into an appropriate format, and loading the data into a data warehouse repository and Oracle data warehouse to reduce an execution time and to remove the mismanagement of metadata in an existing ETL process

This repository was archived by the owner on Sep 21, 2021. It is now read-only.

Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
AHS_2012-13_source_data_new.csv		AHS_2012-13_source_data_new.csv
Data Import.png		Data Import.png
Data.png		Data.png
EDI Report.docx		EDI Report.docx
ETL and Batch Processing towards real time.docx		ETL and Batch Processing towards real time.docx
Presentation.pptx		Presentation.pptx
PuTTY.png		PuTTY.png
Software Requirements Specification.docx		Software Requirements Specification.docx
Statement of Work.docx		Statement of Work.docx
readme		readme

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This is a long-term Project. that's it, lmao.

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Today, big data is generated from many sources and there is a huge demand for storing, managing, processing, and querying on big data. The Map Reduce model and its counterpart open source implementation Hadoop, has proven itself as the solution to big data processing. Hadoop is inherently designed for batch and high throughput processing jobs. T…

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