Blog
Notes on applied ML systems—APIs, batch jobs, and retrieval—plus practical data work (reporting, cleaning, workflows) when that is what the problem needs.
For runnable examples, see Portfolio. For scoped work, see Services.
/ Marketing, Data Analysis
Why Your Marketing Data Is a Mess (And How to Fix It)
Inconsistent naming, duplicate sources, and missing context—here's why marketing data gets messy and how to clean it up.
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/ Data Cleaning, Analysis
Data Cleaning Basics: What to Do Before You Analyse
Analysis is only as good as the data you put in. Here are the essential cleaning steps before you run any numbers.
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/ Data Cleaning, Spreadsheets
Cleaning Spreadsheet Data: A Practical Guide for Small Teams
Your team's spreadsheets are full of inconsistencies. Here's a practical, step-by-step approach to cleaning them without losing your mind.
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/ Automation, Spreadsheets
5 Repetitive Tasks You Should Automate in Your Spreadsheets
Stop doing the same spreadsheet tasks every week. Here are five that are ripe for automation.
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/ Automation, Reporting
From Manual to Automated: Reporting Workflows That Save Time
Moving from manual to automated reporting doesn't have to be a big project. Here's how to do it step by step.
Read more / Data Integration, Reporting
Connecting the Dots: When to Integrate Your Data Sources
Data lives in many places. Here's when it makes sense to connect them—and when it doesn't.
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