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Database Design
Where next?
John Wordsworth
Department of Computer Science
The University of Reading
[email protected].
Room 129, Ext 6544
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Lecture objectives
• To summarise what has happened so far.
• To review topics for further study.
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What we have done
• History of data management
• Modelling data requirements with entityrelationship modelling
• Relational model of data, relational algebra,
normalisation to BCNF, SQL for data
manipulation
• Physical files and indexes
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Security and integrity: risks
• Theft and fraud
• Loss of confidentiality (secrecy) about
corporate data
• Loss of privacy in relation to personal data
• Loss of integrity (invalid or corrupt data)
• Loss of availability (it’s there but we can’t
get at it to run the business)
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Security and integrity: strategies
• Access authorization (access privileges)
• Access authentication (passwords etc.)
• Encryption firewalls (at gateway between
networks)
• Backups, journals, checkpointing (instantaneous
memory dump)
• Audit (Quality Assurance applied to all stages of
data processing)
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Transactions: key ideas
• The ACID test
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Atomicity
Consistency
Isolation
Durability
Serialisability
Commitment and rollback
Recoverability
Locking
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An e-commerce application
Tier 1
Browser
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Tier 2
Web server
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Tier 3
Database
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Data warehousing
• Subject-oriented
– decision-support rather than operational applications
• Integrated
– disparate sources and data types brought together
• Time-variant
– cumulative, frequently updated, time-stamped
• Non-volatile
– refreshed at intervals by increment, summarised
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Data mining
• The process of extracting valid, previously
unknown, comprehensible and actionable
information from large databases and using it to
make critical business decisions
• e.g.
– Identifying buying patterns of customers
– Identifying loyal customers
– Identifying successful medical therapies for different
illnesses
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Object-oriented databases
• Various object-oriented data models
• Support the storing and retrieval of objects:
– object identifier
– attributes
– methods
• Object Definition Language
• Object Query Language
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Object-relational databases
• Extensions to the relational model
• User-defined abstract data types (like
classes)
• Multivalued attributes (set types)
• SQL3
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Key points
• Transactions on databases need to have the ACID
properties.
• Security controls are important in operational
databases.
• Data warehousing and data mining are
applications based on large databases of historical
data.
• Data models other than the relational model are
emerging.
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