Databases Reference
In-Depth Information
D
ATABASE
INTEGRITY
REFERS
TO
THE
CORRECTNESS
OF
THE
DATA
.
STORED
IN
THE
DATABASE
STRUCTURE
OR
COLLECTION
OF
STRUCTURES
Data values at the atomic level must be correct, as must data values related
to other data values (e.g., referential integrity). Data can be corrupted by
many events; for example, by users accessing data or as the result of a
failed operation that does not have an accurate transaction rollback proce-
dure. External factors such as disasters, viruses, and hackers can also cor-
rupt data. Maintaining the integrity of a database requires an end-to-end
approach within an organization. Quality is an ongoing process that assists
in ensuring database integrity. It can be a set of procedures or checks that
are followed to develop a database and to manage ongoing operations.
Database intergrity and quality are clearly important to the value of a
database and in some cases may overshadow other features. This section
examines approaches and tools for ensuring referential data integrity and
quality. This section contains the following chapters.
Chapter 27, “What Is Wrong with My Data?,” examines approaches for
correcting “bad” data so that organizations can fully realize the potential of
the systems that are being developed.
Chapter 28, “Referential Integrity for Database Design,” defines referen-
tial integrity, describes its limitations with examples, and then proposes
methods of overcoming its limitations. Attribute referential integrity is dis-
cussed as it applies to entity-relationship and relational data models.
Chapter 29, “Data Quality: An Architectural Solution,” discusses the pro-
cess of integrating data from multiple data sources into a data warehouse,
while maintaining data quality. This chapter provides advice on resolving
such problems as caused by extracting data from multiple inconsistent data
sources or integrating data stores that utilize different types of data models.
Chapter 30, “Ensuring the Integrity of the Database,” provides an
approach that is based on organizational checks and balances, data access
security, and programmed integrity tests. The approach includes a discus-
sion of issues relevant to distributed data sources. This chapter also exam-
ines some sample tools and repositories.
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