**Introduction**To aggregate is to summarize. Most times this comes in the form of a question:

- How many _______________ are there?
- What does _______________ add up to?
- Who has the most number of _______________ ?
- Who has the least number of _______________ ?
- What is the average of _______________ ?

As you'll notice from the questions above, aggregating data is what you'll likely be out to do most often in your data work: counting things, summing data to get a total, identifying high and low points of a dataset, calculating the average, etc.

**Spreadsheet**

We'll introduce the **Status Bar Summary** feature in Google Sheets, which allows you to easily view an aggregate measure. In addition, we'll introduce how to build custom aggregation formulas by use of the following Google Sheet functions:

**COUNT**/**COUNTA**/**COUNTIF**/**COUNTUNIQUE**/**COUNTBLANK****AVERAGE****SUM****MAX****MIN**

**Database and SQL**

The SQL operators introduced in this lesson include:

**COUNT**/**COUNT DISTINCT****AVG****SUM****MAX****MIN**

**BI Software**This lesson will introduce the concept of

**Measures**in Looker, and how they're built in the backend using Looker's proprietary LookML language. In addition, we'll revisit the use of

**Custom Calculations**to build aggregations on the fly.