> ## Documentation Index
> Fetch the complete documentation index at: https://docs.textql.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Meet Ana

> Think of Ana as a skilled analyst who sits next to you, has already studied your company’s data, and is available 24/7. The core idea of self-service analytics: you bring the bu…

Think of Ana as a skilled analyst who sits next to you, has already studied your company's data, and is available 24/7. The core idea of self-service analytics: **you bring the business question; Ana brings the SQL, the statistics, and the charts.**

## What Ana does with your question

* **Figures out what you mean.** She knows your company's definitions — what counts as a "sale," when your fiscal quarter starts, which system is the source of truth.
* **Does the analyst work.** She finds the right data, writes and runs the technical queries, and double-checks the result — narrating her steps as she goes.
* **Answers in plain English.** You get the number, the context, often a chart — plus the full detail of *how* she got it, whenever you want to look.

## Why her answers are consistent

Behind the scenes, your organization maintains an **ontology** — think of it as **your company's official dictionary for data**. It records exactly what "revenue" means, how "active customer" is calculated, and which numbers are the governed, agreed-upon versions. Because Ana answers from that dictionary:

* You and a colleague asking the same question get **the same answer**.
* The answer matches what finance or analytics would have produced by hand.
* When a definition changes, it changes in one place — and everyone's answers update with it.

You'll verify this yourself in **Module 2**, and in **Module 6** you'll add to the dictionary.

## Three habits that make this easy

<table>
  <tr><th>Habit</th><th>Why it helps</th></tr>
  <tr><td>**Ask like you'd ask a person.**</td><td>Full, natural questions beat keyword fragments. "Which products grew fastest this year?" beats "product growth."</td></tr>
  <tr><td>**It's a conversation, not a search box.**</td><td>Don't craft one perfect question. Ask, look, then refine: "now just the West region," "compare to last year."</td></tr>
  <tr><td>**When unsure, ask about the data itself.**</td><td>"What data do you have about customers?" is a perfectly good question — and the best way to discover what's possible.</td></tr>
</table>