Module 3 Notes ADM1370

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Published on 16 Apr 2013
School
University of Ottawa
Department
Administration
Course
ADM 1370
Professor
Module 3 Notes
Session 1 Database Management Systems
Data and Information
Data: raw facts that describe the characteristics of an event.
Information: data converted into a meaningful and useful context.
Database maintains information about various types of objects
(inventory), events (transactions), people (employees), and places
(warehouses)
Data vs. Information: an Example
Raw Data:
o Shares exchanged in the stock market
Information:
o How did a particular stock perform during the last 6 month?
o How did it perform compare to other stocks?
Importance of Data Management
Data is everywhere in an organization
Data have become central and even vital to organizations.
Organizations need to manage their data assets very carefully to make sure
that the data are easily accessed by managers and employees across the
organization.
Transactional Data and Analytical Information
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MODULE 3 NOTES
Data Management
Data management is a structured approach for capturing, storing, processing,
integrating, distributing, securing, and archiving data effectively throughout
their life cycle.
Why does data management matter?
No enterprise can be effective without high quality data that is accessible
when needed.
Organizations with at least 1,000 knowledge workers lose ~ $5.7 million
annually in time wasted by employees reformatting data as they move
among applications.
What is the goal of data management?
To provide the infrastructure and tools to transform raw data into usable
information of the highest quality.
Data Principles
Principle of diminishing data value
Principle of 90/90 data use
Principle of data in context
Data Management Challenges
Volume of data is increasing exponentially.
Data is scattered throughout the organization.
Data is created and used offline without going through quality control checks.
Data may be redundant and out-of-date, creating a huge maintenance
problem.
File Organization
Traditional (stand-alone) File Environment
When organizations began using computers, they started with one
application at a time, usually accounting, billing, and payroll. Each app was
designed to be a stand-alone system, which led to data problems.
File: Group of
records of same type
Record: Group of
related fields
Field: Group of
words or a complete
number
Byte: Group of bits
that represents a
single character
Bit: Smallest unit of
data; binary digit (0,1)
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MODULE 3 NOTES
3
Problems with Traditional (stand-alone) File Organization
Data redundancy:
The presence of duplicate data in multiple data files so that the same data are
stored in more than one place or location
Data inconsistency:
The same attribute may have different values.
Data Isolation, Lack of data sharing and availability
Information cannot flow freely across different functional areas or different
parts of the organization.
Poor security
Management may have no knowledge of who is accessing or making changes
to the organization’s data
The Database Management System (DBMS)
A software package to create and maintain databases
Acts as interface between application programs and physical data files
Separates logical and physical views of data
Many data sources
o clickstream data from Web and e-commerce applications
o detailed data from POS terminals
o filtered data from CRM, supply chain, and enterprise resource planning
applications
DBMS permits an organization to centralize data, manage them efficiently,
and give application programs access to the stored data.
Entities, Entity Classes, and Attributes
Entity a person, place, transaction, or event about which information is
stored
o The rows in each table contain the entities
Entity class (table) a collection of similar entities
o CUSTOMER, ORDER, ORDER LINE, DISTRIBUTOR, and PRODUCT entity
classes
Attributes (fields, columns) characteristics or properties of an entity class
o The columns in each table contain the attributes
Customer ID
Customer Name
Contact Name
Phone
Relational DBMS
Represents data as two-dimensional tables
Relates data across tables based on common data element
Examples of Relational DBMS: MS Access, DB2, Oracle, MS SQL Server
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Document Summary

Data: raw facts that describe the characteristics of an event. Database maintains information about various types of objects. Information: data converted into a meaningful and useful context. (inventory), events (transactions), people (employees), and places (warehouses) Raw data: shares exchanged in the stock market. Data have become central and even vital to organizations. Organizations need to manage their data assets very carefully to make sure that the data are easily accessed by managers and employees across the organization. Data management is a structured approach for capturing, storing, processing, integrating, distributing, securing, and archiving data effectively throughout their life cycle. No enterprise can be effective without high quality data that is accessible when needed. Organizations with at least 1,000 knowledge workers lose ~ . 7 million annually in time wasted by employees reformatting data as they move among applications. To provide the infrastructure and tools to transform raw data into usable information of the highest quality.

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