Transcript ch01

David M. Kroenke’s
Database Processing:
Fundamentals, Design, and Implementation
Chapter One:
Why DB?
DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition
© 2006 Pearson Prentice Hall
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Why database
• Share data
– Data/information needs to be shared to run a business
– We can run a company without its CEO, not without data
• Reduce redundancy
– Reduce inconsistent data
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Support transaction
Support data integrity
Enforce security
Support and enforce for standards
Meet complicated requirements
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The problem of sharing with file systems
• Duplication
• Inconsistence
• Separated and isolated data
– I have to fix 200 projectors made during the month of
Dec 2008
• How many did you make during that month?
– I’ll get this data from the application regarding production
• How many, out of the ones you made, did you sell?
– I may get this data from the application on distribution
• Can I get all data from one application and even cross
reference over, say, serial number? (yes using SAP)
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An example of a database
• See book on page 4.
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Types of database applications
• Transactional
– Single user, multi-user/Enterprise, e-commerce
• Batch
– Most likely has no place to modify individual record
• Decision support
– Needs DBMS support
– Reporting and data mining
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The components of a database system
• user, database application, DBMS, and
database (see Figure 1-6)
• I am not so sure about Figure 1-7,
because SQL is generally part of
(supported by) DBMS and is very different
from all other components in the figure.
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Figure 1-12 Functions of a DBMS
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Figure 1-14
• Component of a Database
– User Data
– Indexes
– Metadata
– Other database objects
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Stored procedures
Triggers
Functions
views
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Database defined
• A database is a self-describing collection of integrated
tables that are computerized (mostly from page 12)
– Self describing
– Collection of related tables/records
– computerized (my appendage)
• It may support adding, modifying, and deleting of tables
and records through DBMS communicated using SQL
• A logical database is a concept. A physical database is
the realization of a logical database filled with data,
supported by a DBMS that runs on a computer (the
hardware)
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Other definitions of database
• Collection of persistent data
• Collection of true propositions
• Made up of entities, relationships, and
properties
• Implements a data model
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Other definitions of database (2)
• Collection of persistent data
– Stores enterprise information over time
– Outlasts the running of a computer program
– Updated and retrieved in OLTP
operational/production system
– Offers decision support via data warehouse
• Collection of true propositions
– Whatever stored in the database is consider
as truth
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Other definitions of database (2)
• Made up of entities, relationships, and properties
– An entity is a person, place, event or thing, about which we wish
to store information
– A relationship is a connection between entities, about which we
wish to store information
– A relationship can be considered as a special case of entities
– Entities have properties
– Properties are the characteristics of an entity instance
• Implements a data model
– Database is a collection of true propositions
– Data model is an abstract, self-contained, logical representation
of the user’s model (not reality!!!)
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Database development process
• Generally, a database is part of one or more
applications which go through the steps of
requirements gathering, design, implementation,
testing, deploying, maintenance, and retirement
• Maintenance incurs major costs (up to 70%)
• Database Design
– Based on existing database
– For a new system
– Redesign
• All Require domain knowledge
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History of databases
• Figure 1-24
• Nowadays, when we say database, we
mean relational database
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Testing your understanding
• Three concepts
– Database
– Database management system (DBMS)
– Database system
• True or False
MS Access is not a database
True or False
MS Access is not a DBMS
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Trends
• Object oriented DBMS – more of a research thing -dead
• XML for document processing and exchange of
information
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Web service for data processing
Security
Wireless
PDA
Data mining and decision support systems
Unstructured queries
DBMS for cloud computing such as RDS from AMAZON
Column oriented storing vs. row oriented store
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No SQL