Lecture Business management information system - Lecture 16: Managing information resources

Managing Information
Resources
Lecture 16


Managing Information Resources

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Managing Information Resources Lectures explores the
management of data information, and knowledge

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It begins by identifying some problems in managing data,
and then surveys the evolution of database management
systems, including the next-generation systems

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It explores the various types of information that
companies need to manage as they treat information as
an organizational resource


Managing Information
Resources
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It concludes by discussing one of the most important
issues facing companies today: how to manage

knowledge

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Case examples include Monsanto, Owens & Minor,
HICSS Personal Proceedings, Tapiola Insurance Group,
Tennessee Valley Authority, Eastman Chemical
Company and Groove Networks


Today’s Lecture
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Introduction
Managing Data
¨ The

Three-Level Database Model

¨ Four

Data Models

¨ Getting

Corporate Data into Shape


Today’s Lecture..

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Managing Information
¨ Four

Types of Information

¨ Data

Warehouses

¨ Document
¨ Content

Management

Management


Introduction

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“Managing information resources” initially meant
managing data, first in files, then in corporate databases
which were:
¨ Well

structured

¨ Carefully

defined, and

¨ Controlled

by IS department


Introduction

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Data vs. Information vs. Knowledge
¨ Data:

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facts devoid of meaning or intent

¨ Information:

data in context

¨ Knowledge:

information with direction or intent

As the breadth of the kinds of information resources has

expanded, so has the job of managing them. The job
may not start in the IS department but it invariably ends
up there


Introduction
¨ PCs

users used ‘alone’

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Needed to share files

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Version control, back-up etc.

¨ Web

sites / content


Introduction
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Initially created their own

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Need for recovery, version control

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Corporate consistency

¨ IS

to the ‘rescue’

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Management procedures

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Discipline


Introduction ..

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Corporate databases are still a major IS department
responsibility
¨ Sometimes

housed in a variety of database models

¨ Production

databases – transaction

¨ Data

warehouses

¨ CRM

–Customer Relationship Management


Introduction
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Information in the form of documents (electronic or
paper) and Web content has exploded the size of
databases organizations now manage

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Knowledge management is becoming a key to exploiting
“intellectual assets”

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Information resources need to be well managed as
information becomes an important strategic resource

Managing Data
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Database management systems are the main tool for
managing computerized corporate data

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They have been around since the 1960s and are based
on two major principles:
¨ A three- level conceptual model and
¨ Several alternative ‘data models’ for organizing the
data


DBMS EXAMPLE


Managing Data:
The Three-Level Database Model
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Level 1 – The external, conceptual, or local level,
containing the various “user views” of the corporate data
that each application program uses
¨ Not

concerned with how the data will be physically
stored or what data is used by other applications

Managing Data:
The Three-Level Database Model
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Level 2 - The logical or “enterprise data” level
¨ ‘Technical’ (human)

control of the DBAs

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view of the database = under

Level 3 - The physical or storage level, specifying the
way the data is physically stored
¨ End

user not concerned with all these ‘pointers and
flags’ (how the data is physically organized) = they
are for use by the DBMS



The Three-Level Database Model:
Advantages
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Level 2 absorbs changes made at Level 3 such
as using a new physical storage device

¨ Individual

application programs in Level 1 do not need
to be changed when the physical layer changes

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Data only needs to be stored once in Level 2,
and different programs can draw on it and vary
the relationships among the data


Managing Data:
Four Data Models
The second major concept in database management is
alternate ways to define relationships among data
Hierarchical model: structures data so that each
element is subordinate to another in a strict
hierarchical manner

1.

‒

Parent, child etc.

Network model: allows each data item to have more
than one parent,

2.

‒

Relationships stated by pointers stored with the data


Managing Data:
Four Data Models cont.
3.

Relational model:
where the data is stored in tables.
–

Eight relational operations can be performed on this
data
Select, Project, Join, Product, Intersection,
Difference, Union, Division

4.

Entity-Relationship model:


Managing Data:
Four Data Models cont.
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¨

Microsoft Access

Relational systems are not as efficient as hierarchical or
network database systems, but because relational systems
allow people to create relationships among data on the fly.

More flexible


Microsoft Access DBMS Example


Managing Data:
Four Data Models cont.
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First used to handle end user queries – they are now
widely used in high-volume transaction systems with
huge files

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Hence, they have become the database technology of
choice in today’s systems
¨

Also = largely due to decrease in costs of
technology: processing and disk storage


Managing Data:

Four Data Models cont.
Object model: can be used to store any type of data, whether a:

4.

–

Traditional name or address,

–

An entire spreadsheet,

–

A video clip,

–

A voice annotation,

–

A photograph, or

–

A segment of music

Managing Data:
Four Data Models cont.

The tenets of objects have become increasingly
important in the world of computing

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–

E.g. Web Services because the XML modules utilize
object principles


Managing Data:
Four Data Models cont.
Typical, yet complex database applications that may
require objects:

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–

CAD for a large office building

–

Large retail chains record every product code
scanned

–

Insurance policy files e.g. claim forms, images,
video etc.