Unit 8: Database Management

Data quality ManagementData Integrity• Data integrity is a fundamental component of information

security. In its broadest use, “data integrity” refers to the accuracy and consistency of data stored in a database, data warehouse, data mart or other construct.

• “data integrity” refers to the accuracy and consistency of data stored in a database, data warehouse, data mart or other construct. formation security.

• The term – Data Integrity - can be used to describe a state, a process or a function – and is often used as a proxy for “data quality”. 

• Data with “integrity” is said to have a complete or whole structure. Data values are standardized according to a data model and/or data type. 

• All characteristics of the data must be correct – including business rules, relations, dates, definitions and lineage – for data to be complete. 

• Data integrity is imposed within a database when it is designed and is authenticated through the ongoing use of error checking and validation routines.

• Data Integrity is a measure of the validity and fidelity of a data object. As a function related to security, a data integrity service maintains information exactly as it was inputted, and is auditable to affirm its reliability.

•  As a simple example, to maintain data integrity numeric columns/cells should not accept alphabetic data.

Data quality

• Data quality refers to the level of quality of data. There are many definitions ofdata quality but data are generally considered high quality if "they are fit for their intended uses in operations, decision making and planning."

• Data quality is a perception or an assessment of data's fitness to serve its purpose in a given context. 

Aspects of data quality include: • Accuracy (शुदध्ता )• Completeness ( पूर्ण�ता )• Update status ( सुधार पूर्ण� )• Relevance (सान्दर्भि��कता)• Consistency (स्थि�रता)• Reliability ( वि�स्�ासपूर्ण� )• Appropriate presentation ( उपयुक्त प्रस्तुवित )• Accessibility ( उपलब्धता )

• Within an organization, acceptable data quality is crucial to operational and transactional processes and to the reliability of business analytics (BA) / business intelligence (BI) reporting. Data quality is affected by the way data is entered, stored and managed. Data quality assurance (DQA) is the process of verifying the reliability and effectiveness of data.