---
title: "Level 1. Data Basics"
id: "1783"
type: "page"
slug: "data-basics"
published_at: "2026-09-20T21:35:45+00:00"
modified_at: "2026-09-20T21:42:56+00:00"
url: "https://xedant.com/agents/analytics/docs/templates/data-basics"
markdown_url: "https://xedant.com/agents/analytics/docs/templates/data-basics.md"
excerpt: "The first level of the course is for people just starting to work with data…"
---

# Level 1. Data Basics

[https://xedant.com/agents/analytics/docs/templates/data-basics.md](https://xedant.com/agents/analytics/docs/templates/data-basics.md)

The first level of the course is for people just starting to work with data — or who have counted things by eye their whole life. In eight short lessons you build a foundation: what a table is and why files break, how to find what you need, roll numbers into totals, and tell an honest number from a misleading one. No formulas — just a skill that stays with you in any work with numbers.

Every lesson is a template with demo data: ten minutes to complete, one skill that stays. Open it in the Templates section of Analytics Agent and press “Use this template” to take the lesson on your own data.

### What Data Is: Rows and Columns

**Shows:** 30 coffee-shop purchases laid out in a table: a row is one event, a column is one property, and every column has its own type. After this lesson, any export turns into a picture you can read.

**You get:** the first step from “numbers floating around” to data you can count — the foundation for every lesson that follows.

### Your First Table: Loading a File

**Shows:** loading a file and checking its “calling card”: how many rows, what period, what total. Three typical breakages show how a blank row, a foreign date format, and “money stored as text” quietly change the answer.

**You get:** the habit of checking incoming data in the first minutes — instead of catching distorted totals a week later.

### Sorting and Filtering

**Shows:** sorting answers “bigger or smaller”, a filter answers “only these” — and neither changes the data, only your view of it: the top 10, the worst five, one category out of two hundred receipts — in a couple of moves.

**You get:** any ranking and any “how much X do we have” no longer requires asking someone else to count.

### Your First Pivot Table

**Shows:** the four zones of any pivot — rows, columns, values, filters — and a totals matrix that checks itself: 524 rows compress into 12 sums with nothing lost.

**You get:** a skill that transfers to any tool, from spreadsheets to Analytics Agent — manual summaries are no longer needed.

### Clean Data: Duplicates, Blanks and Typos

**Shows:** on a dirty file you see that duplicates and typos cost 7.8% of the money; the lesson shows how to remove duplicates, flag blanks, and unify spellings, keeping a log of every fix.

**You get:** you stop trusting numbers from a dirty export, you know how to clean it up — and you never count the same money twice.

### Sum, Average, Minimum, Maximum

**Shows:** five simple counters — sum, count, average, minimum, maximum — and their trap: an average without “out of how many” misleads. A manager example shows why the best by deals can be the worst by average check.

**You get:** every “on average” now reads honestly to you — with an explicit base, not a magic number.

### Average or Median: Why the “Average Salary” Lies

**Shows:** the difference between the mean (“all the money ÷ people”) and the median (“the person in the middle”): one outlier swings the mean 2.8× while the median holds still. The rule: money, time on site, waiting times are skewed data — they need the median.

**You get:** you no longer fall for the “average salary on the market” and can honestly assess your own business.

### Shares and Percentages

**Shows:** “share” (a part of a whole) vs “growth in percent” vs “percentage points” — plus the tiny-base trap, where “it doubled!” is really 2.7 points of revenue. It also shows the quiet decline that one grand total hides.

**You get:** you always name the base of every percentage — what it was counted from and in which parts — so loud percentages stop being taken at face value.

[← Templates library](/agents/analytics/docs/templates)
 · [Training course section](/agents/analytics/docs/templates#wp-block-themeisle-blocks-advanced-heading-aaat3)