# Profiling

Profiling helps you understand the shape, quality, and uniqueness of your data before creating checks or metric monitors.

With profiling, you can explore metadata about your dataset, such as **column names, data types, distinct counts, null counts, and summary statistics**. You can also quickly search for specific columns to focus on the attributes that matter most to your analysis.

Profiling is useful for:

* **Business teams**: Gain a fast understanding of what’s inside a dataset, its completeness, and potential anomalies.
* **Data teams**: Validate schema, data types, and distributions before writing quality tests or transformations.
* **Data owners**: Quickly identify unexpected values, nulls, or structural changes in a dataset.

### Key features

* **Dataset overview**: Displays a structured view of all columns, their types, and counts.
* **Interactive navigation**: Scroll through the dataset structure or jump directly to a column of interest.
* **Search and filter**: Quickly locate a column by name to review its profiling details.
* **Column-level insights**:
  * **Statistics**
    * Column name
    * Column data type
    * Number of distinct values
    * Number of missing (null) values
    * Minimum, maximum, mean (for numeric columns)
    * Length, patterns, or categories (for text columns)
  * **Histogram** for numeric columns
  * **Frequent values**
  * **Extreme values**, for numeric columns
  * **Data checks** that exist for this column

<figure><img src="/files/4ty8QggkMPN3aXryBxxP" alt=""><figcaption></figcaption></figure>

***

## Enable & configure Profiling

### 1. Enable Profiling

You can enable Profiling during [dataset onboarding](/onboard-data-sources-and-datasets/onboard-datasets-on-soda-cloud.md).

If you want to enable Profiling on an existing dataset, follow the next steps:

1. Click on **Datasets** > The dataset of your choosing
2. Navigate to the **Columns** tab in the dataset view
3. Click on **Update Profiling Configuration**

   <figure><img src="/files/URogDEfIsB8MTHJLYxrE" alt=""><figcaption></figcaption></figure>
4. Toggle on **Enable Profiling**

   <figure><img src="/files/uYzPZl2gszXym61VdXCd" alt=""><figcaption></figcaption></figure>

{% hint style="info" %}
When Profiling is enabled **during** [**onboarding**](/onboard-data-sources-and-datasets/onboard-datasets-on-soda-cloud.md), an automatic scan for Profiling will be executed **regardless of manual or scheduled execution**.
{% endhint %}

### 2. Configure Profiling

Once Profiling has been enabled, you can configure it to adapt to your organization's needs.

1\. Choose a **Profiling schedule**

Profiling happens every 24 hours. **Choose a UTC time** from the dropdown menu to pick a specific hour when the scan will be scheduled.

<figure><img src="/files/w5NhmjHODwebG96ulYOg" alt="" width="563"><figcaption></figcaption></figure>

2. Choose a **Profiling strategy**
   * **Use sampling:** To perform Profiling, Soda will use a **sample of up to 1 million rows** from the dataset.
   * **Use a time window:** To perform Profiling, Soda will use data present in a **30-day time window**, based on the dataset time-partition column.

{% hint style="info" %}
The **time-partition column** is specified **above the columns table**, on the **Columns** tab of any given dataset.
{% endhint %}

<figure><img src="/files/q6oi8j44uGvhRKGkZA6D" alt=""><figcaption><p>In the Bus Breakdown and Delays dataset, the time-partition column is Last_Updated_On</p></figcaption></figure>

3. Click on **Finish**

Now, Profiling will be scheduled.

### Disable Profiling

#### Disable column profiling at the organization level <a href="#disable-column-profiling-at-the-organization-level" id="disable-column-profiling-at-the-organization-level"></a>

If you wish to disable column profiling at the organization level, you must possess **Admin privileges** in your Soda Cloud account. Once confirmed, follow these steps:

1. Navigate to your avatar.
2. Click on **Organization settings**.
3. Uncheck the box labeled **Allow Soda to collect column profile information**.

***

### How it works

When you open Profiling for a dataset:

1. Soda runs a lightweight scan of the dataset’s metadata and a sample of the data (depending on configuration).
2. It calculates summary statistics for each column.
3. Results are displayed in the Profiling view for exploration.

#### Key considerations

* Soda can only profile columns that contain `NUMBERS` or `TEXT` type data; it cannot profile columns that contain `TIMESTAMP` data except to create a freshness check for the anomaly dashboard.
* Soda performs the Discover datasets and Profile datasets actions independently, relative to each other. If you define `exclude` or `include` rules in the Discover tab, the Profile configuration does not inherit the Discover rules. For example, if, for Discover, you exclude all datasets that begin with `staging_`, then configure Profile to include all datasets, Soda discovers and profiles all datasets.

***

## Next Steps

After reviewing profiling results, you can:

* Create **tests** based on profiling insights (e.g., "column should not have nulls").
* Set up **monitors** to track data quality over time.
* Export profiling information to support documentation and governance processes.

<br>

***

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