Business Intelligence

Business intelligence - is knowledge about your
customers, competitors, partners, competitive
environment, and internal operations.

Two types of information processing include:


3-1
OLTP – the processing of transaction information.
OLAP – manipulation of information to support decision
making.
Business Intelligence
3-2
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
The Relational Database Model

Relational databases are composed of
two parts:
1.
2.
3-4
Information – stored in a series of twodimensional tables, files, or relations.
Logical structure of the information (data
dictionary).
The Relational Database Model
Collections of Information
3-5
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
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
The Relational Database Model
With Logical Ties Among the Information
3-8
The Relational Database Model
With Built-In Integrity Constraints
Team Work

Integrity
constraints – rules
that help ensure the
quality of the
information.
Primary Keys,
Foreign Keys, and
Integrity Constraints
(p. 133)
3-9
Database Management
System Tools
3-10
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
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
DBMS Tools
Data Manipulation Subsystem
Find information using the
binoculars.
Click here to enter a new
record.
3-13
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
DBMS Tools
Data Manipulation Subsystem

Query-by-example (QBE) tools - help
you graphically design the answer to a
question.
3-15
DBMS Tools
Data Manipulation Subsystem
The QBE grid
Our selection criteria
3-16
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
DBMS Tools
Application Generation Subsystem

Application generation subsystem contains facilities to help you develop
transaction-intensive applications.



3-18
Data entry screens
DBMS-specific programming languages
Commonly used programming languages
DBMS Tools
Data Administration Subsystem

3-19
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)
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 decisionmaking tasks.
3-20
Data Warehouses and
Data Mining
What Is a Data Warehouse?
3-21
Data Warehouses and
Data Mining
What Are Data Mining Tools?

3-22
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.
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
Data Warehouses and
Data Mining
What Are Data Mining Tools?
3-24
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
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?
3-26
Team Work
How Up-to-Date
Should Data
Warehouse
Information Be?
(p. 149)
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
MANAGING THE
INFORMATION RESOURCE
How Will Changes in Technology Affect
Organizing and Managing Information?




Technology changes?
Convergence of
information management
tools?
Information ownership?
Ethics?
3-28
On Your Own
CRUD – Defining
Information Ownership
(p. 151)