Metrics

∑ What is a Metric?

On Presight, a Metric—or business metric—is a foundational concept that provides a summarized view about an aspect of your business overtime, using your data.

The most powerful thing about a metric is that it allows you to explore trends, seasonal variations, and changes in your data, where meaningful insights and comparisons relevant to your business timeline might surface.

Common examples include Revenue, Number of Customers, Cost, and Profit.

📊 Components of a Metric

Metrics on Presight combine data columns, aggregation functions, and time context from your data tables and turn them into concise and meaningful information.

Take an example Orders table below. In this table—similarly to Excel—you can extract metric Sales from column Amount simply by summing all values from it; or create metric Orders by counting how many rows are there.

From this simple table, you can create at least 3 useful metrics.

The Column to Aggregate

Metrics start with a data column that you want to analyze. While many metrics are derived from columns with numerical values (like Amount or Quantity), they can also be created from non-numerical columns. For example, counting all Order ID provides meaningful metrics such as Number of Orders.

The Aggregation Function

The chosen column is then processed through an aggregation function that determines how to combine or sumarize the data. Common functions include:

  • SUM: Adds up all values in the selected column, giving you a total.

  • AVG (Average): Calculates the average of all values.

  • COUNT: Counts all entries (including duplicates) in the column.

  • COUNTD (Count Distinct): Counts only unique entries, ignoring duplicates.

...and many more.

Read more about Presight Metric Formulas

Metric Formulas

Time Context for Aggregation

Metrics often need to be evaluated within a specific time context—so that trends and patterns can emerge for insights. This context helps you see how your business is performing over different intervals or in relation to specific dates or time periods.

For example, when you have column Amount aggregated by each Order Date, this means Presight will sum up all values in the Amount column where the order occurred within that day. Similarly, you could look at metrics for specific months, weeks, years or even custom date ranges.

Without a time context, your numbers lose a lot of insight value

🛠️ Metrics in Action

Below are a few example of metrics that you'll see a lot on Presight

Metrics used in charts
Metrics in a table
Your metric library on Presight

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