> For the complete documentation index, see [llms.txt](https://docs.bdb.ai/pre-sales/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bdb.ai/pre-sales/manufacturing-use-case/technical-requirements/data-preparation.md).
# Data Preparation
* [x] **Requirement**: Ease of self-service data Preparation capability with no scripting or programming required and no additional license cost.
* [x] **BDB Response**: BDB self-service Data Preparation helps in instant cleansing of data with its user-friendly UI.
* [x] **Requirement**: Ability to support data preparation activities which is built in feature. BDB self-service Data Preparation helps in instant cleansing of data with its excel-like UI.
* [x] **BDB Response:** Interactive Excel like Interface for Visual profiling & transformation as offered by BDB Preparation enables non-technical users to access over 60+ in-built data transformations. It can be integrated with Data Pipeline module so that the transformed data can be extracted in a Pipeline Workflow.
### Features of the Data Preparation
* Data gets displayed in the familiar grid format & basic anomaly detection as soon as data is uploaded.
* 60+ data transformations for basic as well as advanced data cleansing.
* Smart features like history tracking of operations for redo/undo/ replay.
* Extract clean data.
* Option to view sample data (10 K) in a paginated grid.
* Option to get a statistical profile of the data.
* A quality bar to indicate the percent of valid, invalid, and blank rows.
* Ability to view the changes in data, after each transform.
* Ability to undo/redo the transforms if changes are not acceptable.
* Option to write nested transforms using SQL transform.
* Option to view the list of transforms performed on the current data.
* Option to filter data by clicking on the profiling charts.
* Option to perform transforms on the filtered data.
* Option to export the steps to Pipeline so that it can be performed on full data.
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