Management Information Systems Rainer Chp 3

Opening Case:
Rollins Automotive
Rollins is a small automotive dealership. Rather than employ his own people to manage a website, he is able to use Dealercarsearch.com, which manages his database
High quality data are
(List)
Accurate
Complete
Timely
Consistent
Accessible
Relevant
Concise
The Difficulties of Managing Data
*Amount of data is increasing exponentially
*scattered throughout organizations
and collected by many individuals using
various methods and devices
*Data come from many sources
*Data degrade over time (outdated data)
*Data are subject to data rot (outdated,
destroyed storage media)
*Data security, quality, and integrity are critical, yet easily jeopardized
*Inconsistent, conflicting data due to
nonintegrated information systems
*Federal regulations (Sarbanes-Oxley)
*Companies are drowning in unstructured data
Data governance
An approach to managing information across an entire organization.
“A plan for dealing with database”
Master data management (MDM)
*A strategy for data governance
*A process that spans all of an organization’s business processes and applications
*Allows companies to store, maintain,
exchange, and synchronize a consistent, accurate, and timely “single version of the truth” for the company’s core master data
Master data
A set of core data that covers a complete enterprise information system
Databases minimize the following problems:
Data redundancy, Data isolation, Data inconsistency, Data security, Data integrity, and Data independence.
Data redundancy
The same data are stored in many places.

“Can be good or Bad”

Data isolation
Various copies of the data do not agree.
Data Security
Keeping the organization’s data safe from theft, modification, and/or destruction.
Data integrity
Data must meet constraints and be reliable
Data independence
Applications and data are independent of one another.
Database management system (DBMS)
: Specific type of software for creating, storing, organizing, and accessing data from a database
Data model
A diagram that represents the entities in the database and their relationships.
Entity-relationship (ER) modeling
*Entity

*Attribute

*Relationship

*Entity
A person, place, thing, or event about which information is maintained
Entity classes: Groups of entities of a certain type (group of records)
Entity instance: The representation of a particular entity (a record)
*Attribute
A particular characteristic or quality of a particular entity
Primary key (or identifier): A field that uniquely identifies a record
Secondary keys: Other fields that have some identifying information (e.g., major, state)
*Relationship
Types: One-to-one, One-to-many, Many-to-many
Minimum and maximum cardinality
Relational database
(most popular)
The most popular database architecture
Widely used by organizational employees
Examples: Microsoft Access and Oracle
Query Languages
Used to request information from a database.
Structured query language (SQL)
The most popular query language
Allows users to perform complicated searches using relatively simple statements or key words
Query by example (QBE)
Allows users to fill out a grid or template to construct a sample or description of the needed data
Data dictionary
*Defines the format necessary to enter the data into the database
*Creates standard definitions for all attributes
*Provides organizational data resource inventory for effective data management.
Meta Data
Data about Data.
Stored in Data Dictionary
Normalization
*A process of improving the database
design structure by putting it into
its most streamlined form
*When data are normalized, attributes in the table depend only on the primary key
*Streamlines complex groupings of data
*Minimizes redundant data
*Maximizes data integrity
Provides best processing performance
Data warehouse
A large repository of historical data organized by subject to support decision makers in the organization
Data mart
A low-cost, scaled-down version of a data warehouse designed for the end-user needs in a strategic business unit (SBU) or a department
Source systems
Provide data to the warehouse or mart
Data integration
Utilize IT to Extract data from source systems, Transform it, and Load it into a warehouse or mart
Storing the data
Different architectures are available
Data quality
The quality of the data in the warehouse must meet users’ needs
Governance
Ensures that the systems meet organizational needs
Users
Include information producers (create information for others) and information consumers.
Explicit knowledge
*Objective, rational, technical knowledge that has been documented and can be distributed or transformed into a process or a strategy

*Examples: Policies, procedural guides, reports, products, strategies, goals, core competencies

Tacit knowledge
Cumulative store of subjective or experiential learning

Highly personal, imprecise, and costly to transfer

Examples: Experiences, insights, expertise, know-how, trade secrets, understanding, skill sets, learning, and organizational culture

Knowledge management (KM)
A process that helps organizations manipulate important knowledge that is part of the organization’s memory, usually in an unstructured format
Knowledge management systems
Use information technologies to systematize, enhance, and expedite intrafirm and interfirm knowledge management

Utilize best practices as the most effective and efficient ways of doing things

What’s in IT for ME?
Accounting
Use databases to keep track of the transactions and internal controls of an organization

Finance
Use external databases to obtain financial data

Marketing
Access marketing data and transactions
Contribute to an organization’s knowledge base

Production/Operations Management
Use databases to perform optimization analysis

Human Resources Management
Utilize databases to keep track of employee records
Compensate employees who contribute to knowledge base

MIS
Manage databases, maintain data dictionary, and help users access needed data and generate reports with query tools