# Introduction to Dataprep

Astera Dataprep streamlines data cleansing, transformation, and preparation within the Astera platform. With an intuitive interface and data previews, it simplifies complex tasks like data ingestion, cleaning, transformation, and consolidation.

With the AI-powered chat interface, users can describe data preparation tasks in plain language, and the system automatically applies the right transformations and filters, reducing the learning curve and accelerating the process.

 Astera Dataprep is essential for optimizing data processes, ensuring clean, transformed, and integrated data is ready for analysis.

### Key Features of Astera Dataprep:

* **AI-powered Chat:** Interact with a smart assistant to perform data preparation tasks through natural language commands. Just type what you want, for example, "*filter out records where contact title is "Sales Manager"* and the AI agent will apply the required transformation instantly.

<figure><img src="/files/71G10MgJnOI46FNESotF" alt=""><figcaption></figcaption></figure>

* **Point and Click Recipe Actions:** Easily accomplish data preparation tasks through intuitive point and click operations. The Dataprep Recipe panel provides a visual representation of all the Dataprep tasks applied to a dataset.

<figure><img src="/files/MHpJ5fN5QWhfAJqQNWrB" alt=""><figcaption></figcaption></figure>

* **Rich Set of Transformations:** Perform a variety of transformations such as Join, Union, Lookup, Calculation, Aggregation, Filter, Sort, Distinct, and more.

<figure><img src="/files/ziBiiwkBDKe1Uk17BsrH" alt=""><figcaption></figcaption></figure>

* **Active Profiling and Profile Browser with Data Quality Rules:** Real-time data health assists in data cleaning and transforming while validating data to provide a comprehensive view of its cleanliness, uniqueness, and completeness. The Profile Browser, displayed as a side window, offers a comprehensive view of the data through graphs, charts, and field-level profile tables, helping you assess data health, detect issues, and gain valuable insights.

<p align="center"> <img src="/files/rzNkocQueWpvVPpWbqWZ" alt=""><img src="/files/Wwe6QOKyd0aKgEH3403V" alt=""></p>

* **Preview-Centric Grid and Grid View:** An Excel-like, dynamic, and interactive grid updates in real time, displaying transformed data after each operation. It offers an instant preview and feedback on data quality, ensuring accuracy and integrity.

<figure><img src="/files/cti0wkg1Ex1pP3rFNOhI" alt=""><figcaption></figcaption></figure>

* **Data Source Browser:** A centralized location that houses file sources, catalog sources, and project sources, providing a seamless way to import these sources into the Dataprep artifact.

<figure><img src="/files/j70RwYbZCToaa4kSGFxU" alt=""><figcaption></figcaption></figure>

### Limitations of Astera Dataprep

#### **1. Supported Data Types**

* Only flat (tabular) data structures are supported.
* Hierarchical data formats such as nested JSON or XML with multiple levels are not supported.

**2. Data Size Constraints**

* Large files may experience performance delays when previewing or applying multiple transformations. Extremely large datasets should be processed in smaller chunks.

**3. Export Destinations**

* Direct exports are currently limited to CSV and Excel formats.

**4. Dataprep AI Chat**

* The Dataprep Agent only works with metadata and cannot answer questions about the actual data values. You can paste a sample into the chat window so it can assist you.
* The Agent cannot respond to queries outside the scope of Astera Dataprep.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://documentation.astera.com/dataprep/introduction-to-dataprep.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.