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Coding An End-To-End Credit Card Spend Pipeline In 1 Weekend

Visualizing 48 Months Of Credit Card Spending With PyPDF, SQL & Looker (Part II).

Zach Quinn
Pipeline: Your Data Engineering Resource
8 min readJan 20, 2025

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Since the last installment of “Zach does way too much work to fix a vendor’s minor shortcoming” focused heavily on rationale, problem context and the act of processing PDFs, I want to dedicate this piece to taking all the pieces of pt I to create an actionable dashboard.

In popular terms, this edition will “make it [execution] make sense.”

Fun fact: The end product of this dashboard is what drove my wife and I to have a retrospective discussion about spending in 2024, something we’ve never done before because we weren’t equipped with the tools to examine our credit cards as a whole entity.

But before combining everything, it’s necessary to take all the raw totals and the few instances where I’m using a SUM() of transaction data and build the sources for the dash.

Brown wallet with multiple credit cards.
Photo by Stephen Phillips - Hostreviews.co.uk on Unsplash

Aggregating Credit Card Data Into 1 View

Since this was really a “quick and dirty” exercise over a holiday break, I didn’t think too deeply about design for source data. I used four separate tables for each card:

  • Chase
  • American Express

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Pipeline: Your Data Engineering Resource
Pipeline: Your Data Engineering Resource

Published in Pipeline: Your Data Engineering Resource

Your one-stop-shop to learn data engineering fundamentals, absorb career advice and get inspired by creative data-driven projects — all with the goal of helping you gain the proficiency and confidence to land your first job.

Zach Quinn
Zach Quinn

Written by Zach Quinn

Journalist—>Sr. Data Engineer; new stories weekly.

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