1. Business Intelligence
Business intelligence - is knowledge about your customers, competitors, partners, competitive environment, and internal operations.
Two types of information processing include:
OLTP – the processing of transaction information.
OLAP – manipulation of information to support decision making.
3-1

2. Business Intelligence
3-2

3. The Relational Database Model
Database - a collection of information that you organize and access according to the logical structure of that information.
Relational database model - uses a series of logically related two-dimensional tables or files to store information in the form of a database.
Relation - describes each two-dimensional table or file in the relational model.
3-3

4. The Relational Database Model
Relational databases are composed of two parts:
Information – stored in a series of two-dimensional tables, files, or relations.
Logical structure of the information (data dictionary).
3-4

5. The Relational Database Model Collections of Information
3-5

6. The Relational Database Model Created with Logical Structures
Part Number is the primary key because of the key icon beside it.
For Percentage Markup, we defined its Format as “Percent” and its number of decimal places as 2.
3-6

7. The Relational Database Model
Primary key - a field (or group of fields in some cases) that uniquely describes each record.
Foreign key - a primary key of one file that appears in another file.
3-7

8. The Relational Database Model With Logical Ties Among the Information
3-8

9. The Relational Database Model With Built-In Integrity Constraints
Team Work
Primary Keys,
Foreign Keys, and
Integrity Constraints
(p. 133)
Integrity constraints – rules that help ensure the quality of the information.
3-9

10. Database Management System Tools
3-10

11. Database Management System Tools
DBMS engine - accepts logical requests from the various other DBMS subsystems, converts them into their physical equivalent, and actually accesses the database and data dictionary as they exist on a storage device.
3-11

12. DBMS Tools
Data definition subsystem - helps you create and maintain the data dictionary and define the structure of the files in a database.
Data manipulation subsystem - helps you add, change, and delete information in a database and mine it for valuable information. Tools here include views, report generators, QBE, and SQL.
3-12

13. DBMS Tools Data Manipulation Subsystem
Find information using the binoculars.
Click here to enter a new record.
3-13

14. DBMS Tools Data Manipulation Subsystem
By following a series of simple screens, such as those on the previous slide, you can easily create the report below.
3-14

15. DBMS Tools Data Manipulation Subsystem
Query-by-example (QBE) tools - help you graphically design the answer to a question.
3-15

16. DBMS Tools Data Manipulation Subsystem
The QBE grid
Our selection criteria
3-16

17. DBMS Tools Data Manipulation Subsystem
Structured query language (SQL) - a standardized fourth-generation query language found in most DBMSs.
The SQL below creates the same report in Figure 3.7 on page 139.
SELECT Part.[Part Number], Part.Cost, Employee.[Employee
Name], Employee.[Employee Number]
FROM Part, Employee
WHERE (((Part.Cost)>10));
3-17

18. DBMS Tools Application Generation Subsystem
Application generation subsystem - contains facilities to help you develop transaction-intensive applications.
Data entry screens
DBMS-specific programming languages
Commonly used programming languages
3-18

19. DBMS Tools Data Administration Subsystem
Data administration subsystem - a DBMS helps you manage the overall database environment (e.g., backup, recovery, security management).
On Your Own
DBMS Support
OLTP, OLAP, and
Information Management
(p. 142)
3-19

20. Data Warehouses and Data Mining What Is a Data Warehouse?
Data warehouse - a logical collection of information – gathered from many different operational databases – used to create business intelligence that supports business analysis activities and decision-making tasks.
3-20

21. Data Warehouses and Data Mining What Is a Data Warehouse?
3-21

22. Data Warehouses and Data Mining What Are Data Mining Tools?
Data mining tools - software tools you use to query information in a data warehouse. These tools include:
Query-and-reporting tools - similar to QBE tools, SQL, and report generators.
Intelligent agents – use various artificial intelligence tools to form the basis of information discovery and building business intelligence in OLAP.
3-22

23. Data Warehouses and Data Mining What Are Data Mining Tools?
Data mining tools continued
Multidimensional analysis (MDA) tools - slice-and-dice techniques that allow you to view multidimensional information from different perspectives.
Statistical tools – help you apply various mathematical models to the information stored in a data warehouse to discover new information.
3-23

24. Data Warehouses and Data Mining What Are Data Mining Tools?
3-24

25. Data Warehouses and Data Mining Data Marts – Smaller Data Warehouses
Data mart - a subset of a data warehouse in which only a focused portion of the data warehouse information is kept.
3-25

26. Data Warehouses and Data Mining Important Considerations
Do you need a data warehouse?
Do all your employees need an entire data warehouse?
How up-to-date must the information be?
What data mining tools do you need?
Team Work
How Up-to-Date Should Data Warehouse Information Be?
(p. 149)
3-26

27. MANAGING THE INFORMATION RESOURCE Who Should Oversee the Organization’s Information?
Chief information officer (CIO) - responsible for overseeing an organization’s information resource.
Data administration - plans for, oversees the development of, and monitors the information resource.
Database administration - responsible for the more technical and operational aspects of managing the information contained in organizational databases.
3-27

28. Information Ownership
MANAGING THE INFORMATION RESOURCE How Will Changes in Technology Affect Organizing and Managing Information?
Technology changes?
Convergence of information management tools?
Information ownership?
Ethics?
On Your Own
CRUD – Defining
Information Ownership
(p. 151)
3-28