I’m not the person you asked, but here are some random, assorted examples of “structured data you want to learn something about”:
- data you’ve pulled from an API, such as stock history or weather data,
- banking records you want to analyze for patterns, trends, unauthorized transactions, etc
- your personal fitness data, such as workouts, distance, pace, etc
- your personal sleep patterns (data retrieved from a sleep tracking device),
- data you’ve pulled from an enterprise database at work — could be financial data, transactions, inventory, transit times, or anything else stored there that you might need to pull and analyze.
Here’s a personal example: I recently downloaded a publicly available dataset that came in the form of a 30 MB csv file. But instead of using commas to separate fields, it used the pipe character (‘|’). I used DuckDB to quickly read the data from the file. I could have actually queried the file directly using DuckDB SQL, but in my case I saved it to a local DuckDB database and queried it from there.
- data you’ve pulled from an API, such as stock history or weather data,
- banking records you want to analyze for patterns, trends, unauthorized transactions, etc
- your personal fitness data, such as workouts, distance, pace, etc
- your personal sleep patterns (data retrieved from a sleep tracking device),
- data you’ve pulled from an enterprise database at work — could be financial data, transactions, inventory, transit times, or anything else stored there that you might need to pull and analyze.
Here’s a personal example: I recently downloaded a publicly available dataset that came in the form of a 30 MB csv file. But instead of using commas to separate fields, it used the pipe character (‘|’). I used DuckDB to quickly read the data from the file. I could have actually queried the file directly using DuckDB SQL, but in my case I saved it to a local DuckDB database and queried it from there.
Hope that helps.