Data quality analysis is a data exploration stage in which the quality of the customer master data is analyzed in the datasets associated with schemas and potential deficiencies, errors, and issues are determined.
These items need to be resolved before analyzing the data further or leveraging the data to its full potential.
In Pretectum data analysis is simplified by an analysis of the dataset at the time of creation or change. The data is checked against the schema configuration to determine if any anomalies are present such as missing values where the column/attribute is mandatory; Inconsistent values where business area data is used to populate picklists; wrong information due to data errors such as out of range values or mis-typed data.
