Navigating Scope Creep in Data Projects
I just completed my first BI Sprint Series project, and one of the things that stood out was how scope […]
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Report: Investigating Churn at Staffwise
In earlier stages of this project, I defined StaffWise’s revenue leakage problem and outlined key metrics for analysis. The previous
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Documenting the Analysis Process
This phase of the project focused on executing the actual analysis. While I had already done significant prep work in
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The Location Table That Had Nowhere to Go
As part of my Subscription Churn project for StaffWise, I decided to use simulated data to practice creating a clean
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Why Is It So Hard to Make SQL Shine in a Portfolio?
If you’re on the journey to becoming a data analyst (or already in the field), you’ve probably heard this a
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Data Cleaning Progress Update
Clean data isn’t just about tidy spreadsheets; it’s what ensures that insights are reliable and decisions are well-informed. This stage
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Free vs Paid Tools: How Far Can You Really Go When Building Your Portfolio?
You’ve probably heard it before – maybe from mentors, online forums, or blogs: “You don’t need to spend a cent
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Top 6 Tips for Simulating Realistic Data with ChatGPT and Python
I recently set out to create a mock dataset for a BI Sprint Series project I’m working on. I figured
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What Happened to My Location Table?
I asked Python to create random cities, states, and countries – and it did, separately. Now I’ve got Nairobi in
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Simulating Realistic Subscription Data for Business Intelligence
One of the biggest hurdles in building a business intelligence (BI) pipeline is… well, getting the data. But what happens
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