Chapter 6: database and data warehouses
1. Organizational Information
a. Information Levels: Individuals, Department, Enterprise
b. Information Formats: Document, Presentation, Spreadsheet, Database
c. Information Granularities: Detail (Fine), Summary, Aggregate (Coarse)
2. Characteristics of high-quality information include:
a. Accuracy
b. Completeness
c. Consistency
d. Uniqueness
e. Timeliness
3. Low Quality Information within a Database
a. Missing Information
b. Incomplete Information
c. Probable duplicate information
d. Potential wrong information
e. Inaccurate Information
f. Incomplete Information
4. Types of Database Models
a. Hierarchical Database Model: Information is organized into a tree-like structure that allows repeating information using
parent/child relationships.
b. Network Database Model: Lattice structure that allows each record to have multiple parent and child record
c. Relational Database Model: stores information in logically related two-dimensional tables.
5. Relational Database Fundamentals
a. Database: Maintains information about various types of objects, events, people, and places
b. Entity – a person, place, thing, transaction, or event about which information is stored
c. Attribute (field, column) –characteristics or properties of an entity class
d. Primary Key: A field (or group of fields) that uniquely identifies a given entity in a table.
e. Foreign Key: Is a primary key in one table that appears as an attribute in another table and acts to provide a logical
relationship between the two tables.
6. Database advantages from a business perspective include
a. Increased flexibility
b. Increased scalability and performance
i. Scalability: How well a system can adapt to increased demand
ii. Performance: how quickly a system performs a certain process or transaction
c. Reduced information redundancy
d. Increased Information Integrity(quality)
i. Information Integrity: measure of the quality of information
ii. Information constraints: rules that help ensure the quality of information
iii. Relational Integrity constraints: rules that enforce basic and fundamental information-based
constraints.
iv. Business Critical Integrity constraints: Enforce business rules vital to an organization’s success and often require more
insight and knowledge than relational integrity constraints.
e. Increased Information security
7. Database management systems (DBMS) – software through which users and application programs interact with a database
a. Data-driven websites – an interactive website kept constantly updated and relevant to the needs of its customers through
the use of a database
8. Integration – allows separate systems to communicate directly with each other
a. Forward integration – takes information entered into a given system and sends it automatically to all downstream systems and
processes
b. Backward integration – takes information entered into a given system and sends it automatically to all upstream systems and
processes
9. Data warehouse – a logical collection of information – gathered from many different operational databases– that supports
business analysis activities and decision-making tasks.
a. Aggregates information throughout an organization into a single repository that allows employees to make decisions and
undertake business analysis activities.
b. Extraction, transformation, and loading (ETL): A process that extracts information form internal and external databases,
transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse.
c. Data warehouse send subsets of information to data marts.
10. Multidimensional Analysis
a. A Relational Database contains information in a series of two-dimensional tables.
b. It contains layers, each of which contains columns and rows.
c. Creates a cube like structure
11. Information cleansing or scrubbing– a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete
information
12. Data mining – the process of analyzing data to extract information not offered by the raw data alone.
13. Data Mining Tools- A variety of techniques to find patterns and relationships in large volumes of information and infer rules from them that predict future behavior and guide decision making.
All Information above compiled from below reference
Gordon, B., & Ducham, P. (2011). Information Systems. New York: McGraw-Hill/Irwin.
a. Information Levels: Individuals, Department, Enterprise
b. Information Formats: Document, Presentation, Spreadsheet, Database
c. Information Granularities: Detail (Fine), Summary, Aggregate (Coarse)
2. Characteristics of high-quality information include:
a. Accuracy
b. Completeness
c. Consistency
d. Uniqueness
e. Timeliness
3. Low Quality Information within a Database
a. Missing Information
b. Incomplete Information
c. Probable duplicate information
d. Potential wrong information
e. Inaccurate Information
f. Incomplete Information
4. Types of Database Models
a. Hierarchical Database Model: Information is organized into a tree-like structure that allows repeating information using
parent/child relationships.
b. Network Database Model: Lattice structure that allows each record to have multiple parent and child record
c. Relational Database Model: stores information in logically related two-dimensional tables.
5. Relational Database Fundamentals
a. Database: Maintains information about various types of objects, events, people, and places
b. Entity – a person, place, thing, transaction, or event about which information is stored
c. Attribute (field, column) –characteristics or properties of an entity class
d. Primary Key: A field (or group of fields) that uniquely identifies a given entity in a table.
e. Foreign Key: Is a primary key in one table that appears as an attribute in another table and acts to provide a logical
relationship between the two tables.
6. Database advantages from a business perspective include
a. Increased flexibility
b. Increased scalability and performance
i. Scalability: How well a system can adapt to increased demand
ii. Performance: how quickly a system performs a certain process or transaction
c. Reduced information redundancy
d. Increased Information Integrity(quality)
i. Information Integrity: measure of the quality of information
ii. Information constraints: rules that help ensure the quality of information
iii. Relational Integrity constraints: rules that enforce basic and fundamental information-based
constraints.
iv. Business Critical Integrity constraints: Enforce business rules vital to an organization’s success and often require more
insight and knowledge than relational integrity constraints.
e. Increased Information security
7. Database management systems (DBMS) – software through which users and application programs interact with a database
a. Data-driven websites – an interactive website kept constantly updated and relevant to the needs of its customers through
the use of a database
8. Integration – allows separate systems to communicate directly with each other
a. Forward integration – takes information entered into a given system and sends it automatically to all downstream systems and
processes
b. Backward integration – takes information entered into a given system and sends it automatically to all upstream systems and
processes
9. Data warehouse – a logical collection of information – gathered from many different operational databases– that supports
business analysis activities and decision-making tasks.
a. Aggregates information throughout an organization into a single repository that allows employees to make decisions and
undertake business analysis activities.
b. Extraction, transformation, and loading (ETL): A process that extracts information form internal and external databases,
transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse.
c. Data warehouse send subsets of information to data marts.
10. Multidimensional Analysis
a. A Relational Database contains information in a series of two-dimensional tables.
b. It contains layers, each of which contains columns and rows.
c. Creates a cube like structure
11. Information cleansing or scrubbing– a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete
information
12. Data mining – the process of analyzing data to extract information not offered by the raw data alone.
13. Data Mining Tools- A variety of techniques to find patterns and relationships in large volumes of information and infer rules from them that predict future behavior and guide decision making.
All Information above compiled from below reference
Gordon, B., & Ducham, P. (2011). Information Systems. New York: McGraw-Hill/Irwin.