# Data science

> Using statistics, code and business sense to answer questions with data.

- Level: Basic
- Topics: Data, AI
- URL: https://tidbit.legios.com.ar/data-science/
- In Spanish: [Ciencia de datos](https://tidbit.legios.com.ar/es/data-science/)

**Data science** is the work of getting useful answers out of data. It mixes three skills: **statistics**, to know what the numbers really say and how sure you can be; **programming**, usually in Python, R and SQL, to handle data too big for a spreadsheet; and **domain knowledge**, to ask questions that matter for a business, a hospital or a lab.

A typical project starts with a question, like "which customers are about to cancel?". The **data scientist** gathers data from databases and files, then cleans it: fixing typos, filling or removing gaps, merging sources that disagree. That step famously takes most of the time. Then comes exploring with charts, building a **model** that finds patterns or makes predictions, and finally explaining the result to people who will act on it, often in a notebook, a dashboard or a short presentation.

It overlaps with neighbors. **Machine learning** is one of its main tools, used when the goal is prediction; **business intelligence** focuses more on reporting what already happened; **data engineering** builds the pipelines that bring the data in. The role grew in the 2010s as companies collected more data than they knew what to do with, and it remains central now that AI models are trained and evaluated with the same methods.

## An analogy

Like being a detective with spreadsheets. Most of the job is gathering and checking evidence, the dramatic deduction takes an afternoon, and then you still have to convince the jury.

## Keep in mind

- Combines statistics, programming and knowledge of the field.
- Cleaning and preparing data takes most of the time.
- Ends with communication: an answer nobody understands changes nothing.
- Machine learning is a core tool, but not the whole job.

## Go deeper

- [What is data science? (AWS)](https://aws.amazon.com/what-is/data-science/)
- [Data science on Wikipedia](https://en.wikipedia.org/wiki/Data_science)

## Related terms

- [Python](https://tidbit.legios.com.ar/python/): A popular programming language known for being easy to read and quick to write.
- [SQL](https://tidbit.legios.com.ar/sql/): The language you use to ask a database questions.
- [Spreadsheet vs database](https://tidbit.legios.com.ar/spreadsheet-vs-database/): Why a company that runs on Excel eventually needs a real database.
- [Database](https://tidbit.legios.com.ar/database/): An organized store of data that programs can search and update safely.
- [Machine learning](https://tidbit.legios.com.ar/machine-learning/): Teaching computers by showing them examples instead of writing every rule.
- [Business intelligence](https://tidbit.legios.com.ar/business-intelligence/): Turning a company's data into reports and dashboards people use to decide.
- [Artificial intelligence](https://tidbit.legios.com.ar/artificial-intelligence/): Getting computers to do things that, until recently, only people could do.