# List of icons and their actions

Below is a concise reference guide for each icon found above the data pipeline.

<figure><img src="https://977923713-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FJHwf1QFuv1BRPzfSnL2Z%2Fuploads%2FDI7oxgXxP0p7HbnXLHmm%2Fimage.png?alt=media&#x26;token=30d4118f-1010-4f36-83f2-7cb03c1b2374" alt="" width="563"><figcaption><p>List of icons</p></figcaption></figure>

### 1. Undo

Reverts your latest pipeline change (e.g., removing a column, adding a step).&#x20;

### 2. Redo

If you used **Undo** but decide to keep that action, click **Redo**. The undone step reappears.

### 3. Revert to Original Version

Discards all pipeline changes and rolls back the entire dataset to its original, pre-transformation state.&#x20;

### 4. Export

Displays options to export or write back the current dataset to a target (e.g., CSV, HDFS, Snowflake). For more details, check out [this](https://help.tellius.com/tellius-documentation/data/preparing-your-datasets/writeback-window) page.

### 5. Functions

Performs advanced formula-based transformations, subdivided into **Indicators** and **Signatures**. For more details, check out [this](https://app.gitbook.com/o/S3VKMrzMgXbC36NqGRj8/s/JHwf1QFuv1BRPzfSnL2Z/~/changes/159/data/preparing-your-datasets/list-of-icons-and-their-actions/functions) page.

### 6. SQL

Allows you to write or apply raw SQL transformations in the data pipeline. Ideal for complex joins, subqueries, and pushdown operations that merge multiple datasets or apply advanced filtering/aggregations directly within the database’s query engine. For more details, check out [this](https://help.tellius.com/tellius-documentation/data/preparing-your-datasets/list-of-icons-and-their-actions/sql-transform) page.

### 7. Python

Allows you to write or apply Python script-based transformations (via PySpark or Pandas) in the data pipeline. For example, sophisticated data wrangling, machine learning feature prep, or text processing. Use **PySpark** for large-scale distributed data or **Pandas** for smaller local data. For more details, check out [this](https://help.tellius.com/tellius-documentation/data/preparing-your-datasets/list-of-icons-and-their-actions/python-transform) page.

### 8. Aggregate

Summarize or group data by performing aggregations (COUNT, SUM, AVERAGE, etc.). It has the following tabs:

* **Standard**: Basic grouping by field, plus a date/time column if needed.
* **Time-Series**: Specifically for date/time-based grouping (with “Resolution” like daily, weekly).
* **Pivot**: Create a pivot table by selecting row/column dimensions and an aggregation measure.

### 9. Advanced Filter

<figure><img src="https://977923713-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FJHwf1QFuv1BRPzfSnL2Z%2Fuploads%2FPEgzzgLLpF7sKPnY4y4g%2Fimage.png?alt=media&#x26;token=08ae1caa-1af7-4212-a027-e84fb1917226" alt="" width="563"><figcaption><p>Advanced filters window</p></figcaption></figure>

Build complex multi-condition filters for the dataset pipeline. Choose the required column and the action to be applied. Use "+" to chain multiple conditions for more nuanced data curation. Once the filters are applied, only rows matching these conditions will remain in your pipeline.

### 10. Hierarchies

Defines hierarchical relationships and lets you organize **dimension columns** into logical levels, such as **Country → State → City.** For more details, check out [this](https://help.tellius.com/tellius-documentation/data/preparing-your-datasets/list-of-icons-and-their-actions/creating-hierarchies) page.