Data Quality - Cycle Overview
About
A typical use of data quality follow the cycle of :
- Quality Assessment. Part of the process of refining data quality rules for proactive monitoring deals with establishing the relationship between recognized data flaws and business impacts.
- Quality Design to detect the anomalies
- Quality Transformation to correct (or not) the anomalies
- Quality Monitoring to measure the data quality
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Oracle Warehouse Builder Implementation
Specifically, the steps performed in Warehouse Builder to insure data quality are:
- Starting at the 12 o’clock position, the metadata about data sources is captured.
- Next, the data sources are profiled.
- The data rules are then derived from data profiling or existing data rules are imported or entered manually.
- Data flows (mappings) are designed utilizing name and address and match-merge operators
- Data flows are combined in process flows, adding data auditors that measure data quality at any given point in the process
- The processes are deployed and executed, transforming raw data into quality information
- Information quality is, as a final step, continuously monitored in the operational environment by Warehouse Builder’s data auditor programs