Data Pipeline for Banking Sector to Analyze Mortgage Reports

Overview

Details about the mortgage data of the loan buyers. This data is from the end-user who got a mortgage loan from the bank. Since the data files are huge and have micro-level data, it was not possible to take the report of the loan details and processing.

Solution Overview

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Downloaded end-user loan details using a scheduled job using SQL Runner Scripts tool.

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Built a pipeline to extract the downloaded file and upload it into multiple tables. Uploaded data files are moved to an archive folder.

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Designed Dimensions, HUB, and SAT tables using the liquibase tool.

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Data uploaded to base tables are aggregated and validated using AWS Lambda functions.

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Build and deploy changes using AWS Code Commit and Code pipeline.

Impact

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The mortage Bank Data team could analyze the loan data of the end-user and generate the required reports based on the data stored in the Postgres DB.

Technology

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