Data Transformation
TapData's Data Transformation capabilities enable you to build sophisticated data processing pipelines that go beyond simple replication. Whether you're creating real-time materialized views, merging multiple data sources, or applying complex business logic, our transformation tools provide the flexibility and performance you need.
Getting Started
- Data Processing Tasks Create comprehensive data transformation pipelines with processing nodes for filtering, field modifications, data type conversions, and custom business logic. Perfect for ETL workflows and data preparation.
- Incremental Materialized Views (IMV) Build real-time, high-performance views that automatically update as source data changes. Combine data from multiple sources to accelerate insights and decision-making.
For organizations seeking structured data platform governance, explore TapData's Operational Data Hub (ODH) framework. ODH provides a layered architecture approach with dedicated zones for data ingestion (FDM), transformation (MDM), and delivery (ADM), offering proven patterns for enterprise data management and team collaboration.
📄️ Create a Data Transformation Task
In TapData, data transformation tasks provide the capability to incorporate processing nodes between source and target data nodes. These processing nodes serve as valuable tools for efficiently carrying out data processing tasks, such as merging multiple tables, splitting data, and adding or removing fields.
📄️ Supported Processing Node
TapData supports the addition of processing nodes to data transformation tasks, providing the flexibility to incorporate data filtering, field adjustments, and other processing operations as needed. This allows users to customize and enhance their data replication workflows based on specific requirements.
🗃️ Create Incremental Materialized Views
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📄️ Monitor Data Transformation Task
Once the data transformation task is started, the page will automatically redirect to the task monitoring page. From there, you can monitor the task's operation details, such as the status of the Agent, data synchronization progress, task progress, alert settings, and other relevant information.
📄️ Manage Data Transformation Task
Once the data transformation task is created, you can manage it in the task list.