The goals of data security practices is to protect information assets in alignment with privacy and confidentiality regulations, contractual agreements and business requirements. These requirements come from:
A catastrophic system failure due to processing attachments that are too large may
be solved by:
To build models, data modellers heavily rely on previous analysis and modelling work.
The most important reason to implement operational data quality measurements is to inform data consumers about levels of data effectiveness.
Data profiling is a form of data analysis used to inspect data and assess quality.
Data quality rules and standards are a critical form of Metadata. Ti be effective they need to be managed as Metadata. Rules include: