# 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
***
## Enable & configure Profiling
### 1. Enable Profiling
You can enable Profiling during [dataset onboarding](https://docs.soda.io/onboard-data-sources-and-datasets/onboard-datasets-on-soda-cloud).
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**
4. Toggle on **Enable Profiling**
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When Profiling is enabled **during** [**onboarding**](https://docs.soda.io/onboard-data-sources-and-datasets/onboard-datasets-on-soda-cloud), 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.
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.
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The **time-partition column** is specified **above the columns table**, on the **Columns** tab of any given dataset.
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In the Bus Breakdown and Delays dataset, the time-partition column is Last_Updated_On
3. Click on **Finish**
Now, Profiling will be scheduled.
### Disable Profiling
#### Disable column profiling at the organization level
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.
***
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