Data

Information Systems and Management

Valuing Organizational Information

• Transactional Information– Contained within a business process– Supports performing daily operations

• Analytical Information– Includes transactional information plus market and

industry information

• The Value of Timely Information– Real Time: Immediate, up-to-date– Within the Decision Makers Time frame

Characteristics of High-Quality Information

• Accuracy

• Completeness

• Consistency

• Uniqueness

• Timeliness

• Using the wrong information can lead to making the wrong decision

• The wrong decision can cost time, money, and even reputations

The Cost of Low-Quality Information

The Benefits Of High-Quality Information

• Improve chances of making a good decision which, in turn, may directly affect the organizations bottom line

Data Resource Management

Data Planning• Develop an overall data and architecture

for the firm’s data resources that ties in with the firm’s strategic mission and plans, and the objectives and processes of it’s business units.

Data Administration• Involves the establishment and

enforcement of policies and procedures for managing data as a strategic corporate resource.

Cross-Functional Information Systems• Support business processes

• Production• Distribution• Order management

• Cross boundaries of Traditional business functions.

• IT helps by supporting the re-engineering and improvement of business processes.

• A strategic way to use IT to share information resources and improve both efficiency and effectiveness of business processes to help a business attain it’s strategic objectives.

Enterprise Resource Planning

• Replace functional mainframe legacy systems with cross-functional client/server network applications.

• SAP and others

Database Structures• Hierarchical

• One-to-many (Tree like)

• Network– Many-to-many

• Relational– Elements reside in two dimensional interlinked tables

• Multidimensional– Cubes of data

• Object Oriented– Encapsulation: data and operations are stored together

Entity Relationship Diagram (ERD)

• Tool Used In Data Modeling • Depicts relationships between entities• Entity: a category of stored data• Relationship: how entities are associated• Attributes: descriptive components of an

entity

• An ERD model can be easily translated into virtually any type of physical data base implementation

Entity Relationship Diagram

Customer

Order

Item

Rules Of Thumb

• 1:1 : One Table

• 1:M :primary key from one side used as a foreign key in the many side

• M:M : New table with a primary key which is a combination of both the other primary keys.

Rules Of Thumb

Bit

Byte ≡ Character

Field ≡ Data Element ≡ Attributes

Record ≡ Data Structure

Entity ≡ Table

File ≡ Database ≡ Relational

Database• Primary Key• Secondary Key (or Foreign Key)• Referential Integrity• Normalization

Normalization

• A method of simplifying complex data structures

• A process of assigning attributes to entities

• Determine how to traverse a relational database by identifying primary keys and foreign keys

Referential Integrity

The Primary key data must exist before data can be entered in the table where the primary key is used as a Foreign key.

Referential Integrity

First Normal Form (1NF)• An entity is in 1NF if there are no elements, or

group of elements, which repeat for a single occurrence of the entity.

Second Normal Form (2NF)• An entity is in 2NF if it is in 1NF and if the full

key and not part of it derive all non-key elements

Third Normal Form (3NF)• An entity is in 3NF if it is in 2NF and if the

values for the non-key elements are not dependent on any other non-key elements.

ERD Example

Department

Student

Course

Faculty

U of L Database

Faculty•Fac. # (K)•Name•Address•Dept # (k)

Organizational Chart

To Grading System

Admissions

Registration

CalendarHR

Course•Course # (K)•Course Name•Course Description•Faculty # (k)

Course #Student #MarkDepartment

•Dept. # (K)•Dept. Name•Dept. Description Student

•Student # (K)•Student Name•Student Address

Phone Book

Organizing Data

• Data is processed into information which in turn supports decision making

• Database Management System (DBMS)– User/database interface

• Database Administrator (DBA)– IT professional responsible for all aspects of the

database

Data Management

• For data to be turned into information it must first be organized in a meaningful way

• Traditional approach– Data redundancy: duplication of data in separate files– Data integrity: the degree to which data is correct

• Database approach– A pool of related data is shared by mulitple application

programs

Data Modeling

• Key Considerations:• What data will be collected• Who will have access to it• How the data will be used

• Data Model• A diagram of data entities and their

relationships

Data Modeling

• Enterprise Data Modeling• Data modeling done at the enterprise level

• Entity Relationship Diagram (ERD)• Use basic graphic symbols• Show the organization and relationships

between data

• Planned Data Redundancy• Summary totals carried in data• To improve system performance• Data Marts in ERP systems

The Relational Database Model

• Relational Model: • A database model that describes data

in which all data elements are placed in two dimensional tables

• The tables are the logical equivalent to files

• Domain: Allowable values for data attributes

Data Clean-up

• The process of looking for and fixing inconsistencies to ensure that data are accurate and complete

Overview of Database Types• Flat file

– Sequential or direct– Does not use database concepts

• Single User– One person can use the database at a

time (Access)

• Multiple Users– Large DBMS (Oracle)

Providing a User View

• Schema: • a description of the entire database

• Sub schema:• a description of a subset of the

database• Users can view and modify data terms

in the subset

Creating and Modifying the Database

• Data Definition Language (DDL)• Commands used to describe data and their

relationships

• Data Dictionary• Detailed descriptions of all data in the

database

Storing and Retrieving Data

• The system must calculate the physical location based upon logical application of data

• Concurrency Control• A method of dealing with two people

accessing the same record, in the same database, at the same time

Manipulating Data and Generating Reports

• Query-by-example (QBE)– Point and click, drag and drop

• Data Manipulation Language (DML)– Commands used to manipulate data in a database– Structured Query Language (SQL)

Selecting a Database Management System

• Determine information needs of the organization

• Considerations• Size (current and future)• Number of Concurrent Users• Performance (response time)• Integration (relation to other applications)• Features (security, privacy, templates)• The Vendor (service, reputation, viability)• Cost

• Data Warehouse:• A database that collects business

information from many sources in the enterprise, covering all aspects of the company’s processes, products, and customers

• Data Mart:• Subset of a data warehouse

Data Mining

• An information analysis tool that involves the automated discovery of patterns and relationships in a data warehouse

• Predictive Analysis• Combines historical data with

assumptions about future conditions• Used to predict outcome of events

Business Intelligence

• The process of gathering enough of the right information in a timely manner and usable form and analyzing it to have a positive impact on business strategy, tactics, or operations

• Competitive Intelligence

• Counter Intelligence

• Knowledge Management

More Business Intelligence

• Competitive Intelligence– One aspect of business intelligence limited to

information about competitors

• Counter Intelligence– The steps an organization takes to protect information

sought by “hostile” intelligence gathers

• Knowledge Management– The process of capturing a company’s collective

expertise wherever it resides – in computers, on paper, in people’s heads – and distributing it wherever it can help produce bigger payoffs

Distributed Databases

• A database in which the data may spread across several smaller databases connected via telecommunication devices

• Replicated Database– A database that holds a duplicate set of

data

Online Analytical Processing (OLAP)

• Software that allows users to explore data from a number or different perspectives

Object-Oriented

• Object-Oriented Database• Database that stores both data and its

processing instructions together

• Encapsulation