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Chapter 8
Data and Knowledge Management
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Learning Objectives
• Explain the difference between traditional file
organization methods and the database approach
• Explain how database management systems are used
to construct databases, populate them with data, and
manipulate the data to produce information
• Describe the different database models and the
advantages and disadvantages of each model
• Enumerate the most important features and operations
of a relational database, the most popular database
model
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Learning Objectives (Cont.)
• Illustrate how databases are changing business
operations across industries and what impact they
might have on our personal lives
• Explain the concepts of data warehousing and data
mining and their use in business and give examples
of their use
• Identify needs for knowledge storage and
management in organizations
• Give examples of the ways in which knowledge is
managed in organizations
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Managing Digital Data
• The Traditional File Approach
– Disadvantages
• Program/Data Dependency
• Data Redundancy
• Data Integrity
• Moving to Databases
– Database Management System (DBMS)
• Queries: Request data from specified fields
• Security: Giving users different views addresses
security issue
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Managing Digital Data (Cont)
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Managing Digital Data (Cont.)
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Managing Digital Data (Cont.)
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Managing Digital Data (Cont.)
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Managing Digital Data (Cont.)
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Traditional Files vs. Databases: Pros
and Cons
• Traditional File Advantages
– Simplicity
– Efficiency
– Customization
• Database Advantages
–
–
–
–
Reduced data redundancy
Application/data independence
Better control
Flexibility
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The Hierarchical Model
• Records are related hierarchically—each
category is a subcategory of the next level up
• Disadvantages of hierarchical databases
– To retrieve a record, a user must start at the root
and navigate the hierarchy.
– If a link is broken, the entire branch is lost.
– Requires considerable data redundancy
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The Hierarchical Model
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The Network Model
• Allows a record to be linked to more than one
parent
• Supports many-to-many relationships
• Advantage of the network model
– Reduced data redundancy
• Disadvantages of the network model
– Complicated to build and difficult to maintain
– Difficult to maintain and navigate
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The Network Model (Cont.)
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The Relational Model
• Consists of tables; links among entities are
maintained with foreign keys
• Advantages of relational databases
– Same advantages of a network database without the
complications
– Easier to conceptualize and maintain
– Virtually all DBMSs offered for microcomputers
accommodate the relational model
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The Relational Model (Cont.)
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The Object-Oriented Structure
• Useful for data and information that cannot be
organized into fields
• Does not store records, but data objects
• Advantages include ability to represent data
dynamically
• Disadvantages include dependence between
applications and data
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Components of Database
Management Systems
• The Schema
– Describes the structure of the database
• The Data Dictionary (Metadata)
– Maintains all information supplied by the developer
when constructing the schema
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Relational Databases:
Design and Keys
• Data Modeling
– Analyzing data and identifying relationships
– Entity Relationship (ER) Diagram, a graphical
representation of all entity relationships
– Understand symbols when reviewing a diagram
– Key: a field whose value identify records
• Primary Key
• Linking
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Relational Databases:
Design and Keys (Cont.)
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Relational Databases:
Design and Keys (Cont.)
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Components of Database
Management Systems
• The Schema
– Describes the structure of the db
• Names, types of fields, general relationships
– Types of data
• Numeric, alphanumeric, graphic, time-related
– Building a Database
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Components of Database
Management Systems (Cont.)
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The Data Dictionary
• All information supplied by db developer in the
schema is maintained here
– Table names
– Record names and types
– Field names and types
– Relationships among record types
– Who is responsible for updating the db
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The Data Dictionary (Cont.)
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Data Definition Language (DDL)
• Used to construct the schema
• Usually transparent to user of modern relational
DBMS
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Data Definition Language (Cont.)
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Data Manipulation Language
(DML)
• Software used to query the database
• Either enter a statement requesting information, or
a Query by Example (QBE)
• Programmers use this for developing applications
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Data Manipulation Language
(DML)
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Relational Operations
• Data Manipulation
– Select, Project, Join
• Structured Query Language (SQL)
– International standard DDL and DML for
relational DBMS
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Relational Operations (Cont.)
• SQL (cont.)
– Advantages
– Users do not need to learn different DDLs and
DMLs.
– SQL can be embedded in widely used 3rd
generation languages, increasing efficiency and
effectiveness.
– Programmer not forced to rewrite statements since
SQL statements are portable.
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Relational Operations (Cont.)
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Database Architecture
• Distributed Databases
– Replication
• Full copy of the entire database is stored at all sites
– Fragmentation
• Parts of database are stored where they are most
often accessed
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Database Architecture (Cont.)
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Database Architecture (Cont.)
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Client/Server Systems
• Four basic client/server models
– Applications run at a server
– Applications run on local PCs
– Applications run on both the local PCs and the
server
– Applications and key elements of the database are
split between the PCs and the server
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Databases on the Web
• Catalogs
• Libraries of books, articles, CDs, and movie
clips
• Directories
• Client lists and profiles
• Package tracking
• Customer relationship management
• Financial transactions databases
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Databases on the Web (Cont.)
• Points to Consider
• Which application to use
• How to ensure Web surfers do not interfere with
database updates
• How to maintain security
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Data Warehousing
• Data warehouse: a collection of data that supports
management decision making
• Data Mart: smaller collection of data focusing on a
particular subject or department
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Data Warehousing (Cont.)
• From Database to Data Warehouse
– Transactional db usually not suitable for analysis
because they contain current, not historical data
– Hardware must meet capacity needs
– Data and software and scalability must be
considered
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Phases in Building a Data
Warehouse
• Extraction Phase
– Builders create the files from transactional db and
save on server
• Cleansing Phase
– Data is made consistent
• Loading Phase
– Builders transfer files to data warehouse database
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Phases in Building a Data
Warehouse (Cont.)
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Data Mining and Online Analysis
• Data mining
– Sequence or path analysis
– Classification
– Clustering
– Forecasting
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Data Mining and Online Analysis
(Cont.)
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Online Analytical Processing
• Fast in response
• Enables timely decision-making
• Use data stored in data warehouses to derive ratios
and degrees of predetermined relationships
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Knowledge Management
• The attempt by organizations to:
– Transfer knowledge into databases
– Filter and separate the most relevant knowledge
– Organize knowledge in databases that either
• Allow other employees to easily access the
knowledge
• “Push” specific knowledge to employees based on
their prespecified needs
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Ethical and Societal Issues
Every Move You Make
• Out of Hand -- Out of Control
– DBMSs allow organizations to collect, maintain,
and sell vast amounts of private personal data
easily
• The Web: A Source of Data Collection
– Many consumers provide information daily without
being aware of where it is actually going
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Ethical and Societal Issues
A Too-Risky Info Highway
• Our Finances Exposed
– Personal data is distributed
• Our Health Online
– Benefits and risks
• The Upside
– Database technology enables better and faster
services
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Summary
• Traditional file organization vs. database approach
• How database management systems effect
database development
• Features and operation of a relational database
• Data warehousing and data mining
• Knowledge storage and management
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