Data Science for the Curious and Confused: An Introduction for Non-Techies

A Non-Techie’s Guide to Understanding Data Science

Photo by Luke Chesser on Unsplash

Pretend you’re a detective unraveling a mystery. But instead of solving crimes, you’re solving puzzles about people, businesses, or the universe — with data as your only clue. Data Science is all about:

• Collecting data (like Sherlock noting footprints).
• Cleaning it (because it’s usually messier than your teenager’s room).
• Analyzing it (the “aha!” moment).
• Predicting the future with it (Think Nostradamus, but with data to back up your claim instead of relying on retrofitting).

What is Data?

Data is just fancy talk for facts and figures. Examples:

• Numbers (your bank balance…or lack thereof).
• Text (your Tweets that scream bad decisions).
• Images (all those selfies stored on your phone — yes, that counts too).

So, if life were a game, data is the scorecard.

Tools of the Trade

Picture this: Data Scientists have their own version of a utility belt. Instead of grappling hooks, they use:

• Excel: Baby’s first data tool. Great for small stuff. Not recommended for tremendous amount of data.
• Python: The Swiss Army knife of coding.
• R: Another programming tool, beloved by statisticians. Basically, Python’s nerdy cousin.
• SQL: Pronounced “sequel” or “ess-cue-ell” (don’t fight me on this). It’s the language of databases, where data lives.

The Data Process

Here’s what a Data Scientist does, in meme-friendly steps:

Collect the Data: Like mining for gold, but instead of gold, you find spreadsheets full of typos.

• Example: Scraping websites, downloading reports, or asking Karen from HR to send over the sales data (again).

Clean the Data: Because 70% of the time, it’s garbage. Imagine having to manually erase stains from a cookbook.

• Example: Fixing…