Big Data Middle Platform
Short Description:
It breaks down information silos, unleashes the value of data, and helps clients build unified, intelligent data asset management capabilities.
Detailed solution introduction:
Challenges and Issues
Development Goals
Implementation Process
Product Components
Features — Data Ingestion
Features — Data Governance
Features — Data Storage
Features — Data Security
Features — Analytics & Modeling
1、Model Change
Structural changes, business field changes.
Example: Field length, field type.
2、Impact Analysis
Determine the scope of impact based on metadata changes.
(Analysis based on: Chinese name, English name, data type, length, valid values…)
3、Define Impact Scope
Scope both inside and outside the data warehouse, within the big data environment.
Example: ODS (Operational Data Store), Core Layer, Risk Data Mart.
4、Process Triggering
Trigger notifications across the data pipeline.
Via SMS, WeChat, etc.
5、Modification Confirmation Process
Confirm and execute the relevant data modification procedures…
Example: Immediate modification, deferred modification, no modification (with reasoning and alternative handling methods).
Features — Data Services
System screenshots:
