Objective

A US-based buy-side-firm wanted to track deposit rates of various banks and harvest deposit rates of US and Australia based banks.

Challenges
 

• Large volumes of structured and unstructured data.
• Manual tracking of data was taxing on firm resources.
  
  

Approach
 

• Scraped and consolidated web data using Python.
  
• Performed data cleansing, pattern recognition and structuring operations to ensure data quality.
  
• Stored data using Google Cloud and Excel.
  
• Connected to Tableau for visualizations and reporting.
  

Impact
 

• Developed a dynamic visualization tool to efficiently summarize and analyze large data sets.
  
• Automated data processing to ensure limited manual intervention and enhance accuracy.
  

Questions

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