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Data preparation is a key feature of the YiDA low-code platform. It helps enterprise users clean, integrate, and transform raw data before running data analysis or building apps. This article explains how to create a data preparation. Data preparation uses a no-code ETL (Extraction, Transformation, Loading) solution to process data from YiDA apps, external enterprise databases, file-based data, and official DingTalk data sources (including Roster, OA, Smart HR, Attendance, and more). By building data processing workflows, it consolidates scattered data into standardized datasets that support visual analysis and data-driven decisions.

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Procedure

  1. Sign in to the YiDA workbench and open the app settings page.
  2. Click Data Factory > Data Preparation.
  3. Click Create Data Preparation to open the data preparation designer.
  4. Drag an Input node onto the canvas and configure the input source.
Set the input data to a dataset or a Data Source.
  1. At the bottom of the page, configure the field types.
Supported data types include string, number, float, date, and array.
1

Drag a data processing node onto the canvas and connect it to the input node

For details about configuring data processing nodes, see Node overview.
2

Drag an Output node onto the canvas and connect it to the preceding data processing node

  1. After configuration is complete, click Test in the upper-right corner.
  2. Once the test passes, click Publish to finish the configuration.