# Dimensions

Dimensions describe how your data is organised in Phocas. A **dimension** is a way of grouping the data in a database, so you can view, filter, and analyse it. In some modules, such as [Financial Statements](https://app.gitbook.com/s/KhoFIsurMPEjkuBz9YkN/getting-started/overview-of-the-link-between-financial-statements-and-dimensions) and [Budgets & Forecasts](https://app.gitbook.com/s/aNH5UMuZXBHuAbFF7nI2/getting-started/overview-of-key-terms-and-concepts/dimensions), dimensions control how data is structured, not just analysed.

### Dimension entities

Each dimension contains a list of items, called **dimension entities**. 

In other words, a dimension is the “group by” field and a dimension entity is one item in that list.

{% hint style="info" %}
**Dimension entities are not business or trading entities**

Finance teams often use the terms *business entity* or *trading entity*. These are not the same as a *dimension entity*. 

A trading entity represents an actual business or company that records transactions. 

In a multi-entity organisation, you might have a dimension called Trading Entity that contains a list of your individual businesses. Each business appears as a dimension entity in Phocas, even though it represents a trading entity in your source system. 
{% endhint %}

### Examples of dimensions and their entities

Most organisations use similar types of dimensions, even if the names differ. Here are some common examples:

<table><thead><tr><th width="132">Dimension</th><th width="232">What it represents</th><th width="201">Dimension entities</th><th>Example </th></tr></thead><tbody><tr><td>Customer</td><td>Who you sell to</td><td>Customer names and/or codes</td><td>ASAP Metals USA</td></tr><tr><td>Product</td><td>What you sell</td><td>Product names and/or codes</td><td>Widget A</td></tr><tr><td>Sales rep</td><td>Who made the sale</td><td>Sales rep (employees) names and/or codes</td><td>Andrew Wood</td></tr><tr><td>Location or Branch</td><td>Where the sale occurred</td><td>Countries, cities, states, territories, or branch names and/or codes</td><td>USA</td></tr><tr><td>Account</td><td>How values are categorised in the general ledger</td><td>Account names and codes</td><td>4010 Sales revenue</td></tr></tbody></table>

Your organisation might also have other dimensions that are specific to how you operate.

### Dimension groups

Some dimensions are organised into **dimension groups**. A dimension group is a set of related dimensions that work together.

Each dimension group has:

* One **primary dimension**. This is the main way the data is grouped. The transactions are mapped to this dimension. Some people call this the *parent dimension*.
* One or more **sub-dimensions** that belong to the primary dimension. They add extra detail to that same data. Some people describe these as *child dimensions* or *properties* of the primary dimension.

Think of the primary dimension as the main label, and sub-dimensions as additional attributes that describe it.&#x20;

For example, in the following extract of a dimension panel in Flex Modes, you can see two dimension groups, one for customers (Ship To) and another for products.

<div align="left"><figure><img src="https://900295827-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F7pj8v25BOyqZTdG5mdD1%2Fuploads%2FNDs7oHLU9pp3kUaVvkeF%2Fimage.png?alt=media&#x26;token=10c70757-d912-4a96-bf2f-cffdabe621bb" alt="" width="211"><figcaption></figcaption></figure></div>

These groups are created in the underlying database, where administrators can view them in the Designer module.

<div align="left"><figure><img src="https://900295827-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F7pj8v25BOyqZTdG5mdD1%2Fuploads%2FavgOiYZ0RvnD6ZsBHDNm%2Fimage.png?alt=media&#x26;token=80e968ee-064c-4244-8bca-7a8509cc8285" alt="" width="247"><figcaption></figcaption></figure></div>

### Using dimensions in Phocas

Think of dimensions as the categories you use to break data into meaningful parts, such as who you sold to, what you sold, or where the sale happened.&#x20;

You interact with dimensions throughout Phocas, even if you don't always notice them. For example, you use dimensions when you:

* Use the grid to analyze the data, and build reports, charts, and dashboards.
* Filter data to focus on specific items.
* Drill down from a summary value to see the detail behind it.
* Create financial statements, budgets, and rebate rules (where applicable).

#### Dimensions panel

In Analytics, Flex Modes, and Financial Statements, the dimensions panel on the left of the grid shows the dimensions available from the underlying database. For example:

* In a Sales database, you might have dimensions such as Customers, Products, Sales Reps, Regions, Vendors, and so on.
* In an Inventory database, you might have dimensions such as Supplier, Warehouse, Country, and so on.&#x20;
* In a Financial database, you'll always have the account dimension and others such as Category or Classification.

In Flex Modes and Financial Statements, you can hide (collapse) the dimension panel (including the **Summary**, **Focus**, and **Reset** buttons) to see more of the grid, which is useful on smaller screens. Click the **Hide dimensions** at the button of the panel. Click it again to show the panel.

<figure><img src="https://900295827-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F7pj8v25BOyqZTdG5mdD1%2Fuploads%2FYswqOXAs7n31DJE9yM8J%2Fimage.png?alt=media&#x26;token=5a4427b0-a07b-4a75-8f9e-fd43a4f05ca2" alt=""><figcaption></figcaption></figure>

#### Different views of the data

When you look at data in the Phocas grids, you're usually looking at a measure (number), such as sales or quantity, broken down by one or more dimensions. For example, in the following Flex Modes grid, you can see the total sales value, firstly broken down by Customer and then by Product, giving you two perspectives of the data.

<div align="left"><figure><img src="https://900295827-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F7pj8v25BOyqZTdG5mdD1%2Fuploads%2FDuS205voYYxXGmCWbQfG%2Fimage.png?alt=media&#x26;token=ec9424aa-ff36-4c0c-a016-943fa922ba1f" alt=""><figcaption></figcaption></figure></div>

### Dimensions versus periods versus measures

The **period** (date) isn't a dimension, but it acts like one because you also use it to group, filter, and compare data over time.

**Measures** are the numbers you analyse. Examples include sales value, margin, quantity, and costs.

A simple way to think about it is:

* Dimensions answer questions like who, what and where.
* The period tells you when.
* Measures answer questions like how much or how many.

In Phocas grids, most of the time, dimension entities appear as rows, the period appears as columns, and the measures appear in the cells. For example, the sales value of customer ASAP Metallising USA in February 2025 was almost 50,000.

<figure><img src="https://900295827-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F7pj8v25BOyqZTdG5mdD1%2Fuploads%2Fnesgtxx7GfDpHNuBB3zq%2Fimage.png?alt=media&#x26;token=252faf80-cb3b-4426-87a6-6d7d6f86a09d" alt=""><figcaption></figcaption></figure>

### Why dimensions matter

Dimensions control how flexible and meaningful your analysis can be. Well-defined dimensions make it easier to:

* Answer business questions quickly.
* Compare performance across different parts of the business.
* Keep reports, budgets, and forecasts consistent.

If dimensions change, such as adding a new customer or product, those changes can flow through to reports, budgets, and forecasts, depending on how they are set up.

If you are unsure which dimensions are available in your environment, contact your Phocas administrator.