The document discusses databases and data warehouses. It begins by explaining the differences between traditional file organization and database management approaches. It then describes how relational and object-oriented databases are used to construct, populate, and manipulate databases. Finally, it discusses how data is transferred from transactional databases to data warehouses for analysis and decision making.

1. Management Information Systems,
Sixth Edition
Chapter 7:
Databases and Data Warehouses

2. Objectives
• Explain the difference between traditional file
organization and the database approach to
managing digital data
• Explain how relational and object-oriented
database management systems are used to
construct databases, populate them with data,
and manipulate the data to produce information
• Enumerate the most important features and
operations of a relational database, the most
popular database model
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3. Objectives (continued)
• Understand how data modeling and design
creates a conceptual blueprint of a database
• Discuss how databases are used on the Web
• List the operations involved in transferring data
from transactional databases to data
warehouses
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4. Managing Digital Data
• Businesses collect and dissect data for many
purposes
• Data can be stored in database format
– Easy access and manipulation
• Databases have had a profound impact on
business
– An information industry has been created
• Database technology integrated with the Internet
has contributed to commerce significantly
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5. The Traditional File Approach
• Traditional file approach: no mechanism for
tagging, retrieving, or manipulating data
• Database approach: provides powerful
mechanism for managing and manipulating data
• Traditional approach is inconvenient:
– Program-data dependency
– High data redundancy
– Low data integrity
• Data redundancy: duplication of data
• Data integrity: accuracy of data
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6. The Traditional File Approach
(continued)
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7. The Database Approach
• Database approach: data organized as entities
• Entity: an object about which an organization
chooses to collect data, such as:
– People
– Events
– Products
• Character: smallest piece of data
– A single letter or a digit
• Field: single piece of information about entity
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8. The Database Approach (continued)
• Record: collection of related fields
• File: collection of related records
• Database fields can hold images, sounds, video
clips, etc.
• Field name allows easy access to the data
• Database management system (DBMS):
program used to:
– Build databases
– Populate a database with data
– Manipulate data in a database
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11. The Database Approach (continued)
• Query: a message to the database requesting
data from specific records and/or fields
• Database must be properly secured
– Not everyone should have access to all data
– Users will have different views of the database,
based on the data they are allowed to see
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12. The Database Approach (continued)
• Database administrator (DBA): the person
responsible for managing the database
– Sets user limits for access to data in the database
• DBMS is usually bundled with a programming
language
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15. Database Models
• Database model: general logical structure
– How records stored in the database
– How relationships between records are
established
• Database models differ in:
– How records are linked to each other
– How users can navigate the database, retrieve
records, and create records
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16. The Relational Model
• Relational Model: consists of tables
• Based on relational algebra
– Tuple: record (or row)
– Attribute: field (or column)
– Relation: table of records
• To design a relational database, you must
understand the entities to be stored in the
database and how they relate
• Tables are independent of each other, but can
be related to each other
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17. The Relational Model (continued)
• Key: a field whose values identify records
– Used to retrieve records
• Primary key: a field by which records are
uniquely identified
– Each record in the table must have a unique key
value
• Composite key: combination of fields that serve
as a primary key
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19. The Relational Model (continued)
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20. The Relational Model (continued)
• Foreign key: a field that is common to two tables
– Used to link the tables
– This field is a primary key in one table and a
foreign key in the other
• Join table: composite of tables
• Two types of table relationships:
– One-to-many relationship: one item in a table is
linked to many items in the other table
– Many-to-many relationship: many items in a
table are linked to many items of the other table
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21. The Object-Oriented Model
• Object-oriented database model: uses object-
oriented approach for the database structure
• Encapsulation: combined storage of data and
relevant procedures to process it
– Allows object to be “planted” in different data sets
• Inheritance: the ability to create a new object by
replicating the characteristics of an existing
(parent) object
• Object-oriented databases (ODBs) store data
objects, not records
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23. Relational Operations
• Relational operation: creates a temporary
subset of a table or tables
• Used to create a limited list or a joined table list
• Three important relational operations:
– Select: a selection of records based on conditions
– Project: a selection of certain columns from a
table
– Join: join data from multiple tables to create a
temporary table
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24. Structured Query Language
• Structured Query Language (SQL): query
language of choice for DBMSs
• Advantages of SQL:
– It is an international standard
– It is provided with most relational DBMSs
– It has easy-to-remember, intuitive commands
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25. The Schema and Metadata
• Schema: a plan that describes the structure of
the database, including:
– Names and sizes of fields
– Identification of primary keys
– Relationships
• Data dictionary: a repository of information
about the data and its organization
– Also called metadata: the data about the data
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26. The Schema and Metadata (continued)
• Metadata includes:
– Source of the data
– Tables related to the data
– Field and index information
– Programs and processes that use the data
– Population rules: what is inserted, or updated,
and how often
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28. Data Modeling
• Databases must be carefully planned and
designed to meet business goals
• Data modeling: analysis of an organization’s
data and identification of the data relationships
– A proactive process
– Develops a conceptual blueprint of the database
• Entity relationship diagram: a graphical
representation of all entity relationships
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29. Data Modeling (continued)
• Entity relationship diagram is composed of:
– Boxes: identify entities
– Lines: indicate relationship between entities
– Crossbars: indicate mandatory fields
– Circles: indicate optional
– Crow’s feet: identify “many”
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30. Data Modeling (continued)
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31. Data Modeling (continued)
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32. Databases on the Web
• Web is dependent on databases
– Organizations must link their databases to the
Web
• Interface between Web and database required
• Interface may be programmed in one of several
Web programming languages, including:
– Java servlets
– Active server pages (ASP)
– PHP (Hypertext Preprocessor)
– Web application program interfaces (APIs)
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33. Databases on the Web (continued)
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34. Data Warehousing
• Most data collections are used for transactions
• Accumulation of transaction data is useful
• Data warehouse: a large repository database
that supports management decision making
– Typically relational
– Data is collected from transactional databases
• Data mart: a smaller collection of data focusing
on a particular subject or department
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35. From Database to Data Warehouse
• Transactional databases are not suitable for
business analysis
– Contain only current, not historical data
• Data warehouse requires large storage capacity:
– Mainframe computers are often used
– Scalability is an issue
– Data warehouses grow continually
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36. Phases in Data Warehousing
• Three phases in transferring data from a
transactional database to a data warehouse:
– Extraction phase: create files from transactional
database
– Transformation phase: cleanse and modify the
data format
– Loading phase: transfer files to data warehouse
• A properly built data warehouse becomes a single
source for all data required for analysis
• Data mining and online analytical processing
(OLAP) use data in data warehouses
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38. Summary
• Organizations collect vast amounts of data
• Database approach has several advantages
over traditional file approach
• Character: smallest piece of data
• Field: made up of multiple characters
• Record: collection of related fields
• File: collection of related records
• Database management system (DBMS): tool to
construct databases
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39. Summary (continued)
• Relational and object-oriented database models
have different advantages
• Keys are used to form links among entities
• Primary keys are unique identifiers
• Object-oriented database maintains objects that
contain data and procedures that process it
• Structured Query Language (SQL) is an
international standard for querying databases
• Database designer must construct a schema to
construct a database
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40. Summary (continued)
• Database designers conduct data modeling and
create entity relationship diagrams to plan
databases
• Many databases are linked to Web
• Data warehouses contain huge collections of
historical transaction data
• Data warehouse requires data extraction,
transformation, and loading of transactional data
• Invasion of privacy is exacerbated by database
technology
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