Chapter 6 MIS

Information Granularity
Refers to the extent of detail within the information (Fine and detailed or course and abstract).
Transactional Information
Encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support daily operational tasks.
Analytical Information
Encompasses all organizational information, and its primary purpose is to support the performing of managerial analysis tasks.
Real-time Information
Immediate, up-to-date information.
Real-time Systems
Provide real-time information in response to requests.
Information Inconsistency
When the same data element has different values.
Information Integrity Issues
Occur when a system produces incorrect, inconsistent, or duplicate data.
Accurate
Is there an incorrect value in the information?
Complete
Is a value missing from the information?
Consistent
Is aggregate or summary information in agreement with detailed information?
Timely
Is the information current with respect to business needs?
Unique
Is each transaction and event represented only once in the information?
Data Governance
Refers to the overall management of the availability, usability, integrity, and security of company data.
Database
Maintains information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses).
Database Management System (DBMS)
Creates, reads, updates and deletes data in a database while controlling access and security.
Query By Example Tool (QBE)
Helps users graphically design the answer to a question against a database.
Structured Query Language (SQL)
Asks users to write lines of code to answer questions against a database.
Data Element (Data Field)
The smallest or basic unit of information.
Data Models
Logical data structures that detail the relationships among data elements using graphics or pictures.
Metadata
Provides details about data.
Data Dictionary
Compiles all of the metadata about the data elements in the data model.
Relational Database Model
Stores information in the form of logically related two-dimensional tables.
Relational Database Management System
Allows users to create, read, update, and delete data in a relational database.
Entity (Table)
Stores information about a person, place, thing, transaction, or event.
Attributes (Columns or fields)
Data element associated with an entity.
Record
A collection of related data elements .
Primary Key
A field that uniquely identifies a given record in a table.
Foreign Key
A primary key of one table that appears as an attribute in another table and acts to provide a logical relationship between the two tables.
Physical View of Information
Deals with the physical storage of information on a storage device.
Logical View of Information
Focuses on how individual users logically access information to meet their own particular business needs.
Information Redundancy
The duplication of data, or the storage of the same data in multiple places.
Information Integrity
A measure of the quality of information.
Integrity Constraints
Rules that help ensure the quality of information.
Relational Integrity Constraints
Rules that enforce basic and fundamental information based constraints.
Business Rule
Defines how a company performs certain aspects of its business and typically results in either yes/no or true/false answers.
Business Critical Integrity Constraints
Enforce business rules vital to an organization’s success and often require more insight and knowledge than relational integrity constraints.
Content Creator
The person responsible for updating and maintaining website content.
Static Information
Includes fixed data incapable of change in the event of user action.
Dynamic Information
Includes data that change based on user action.
Dynamic Catalog
An area of a website that stores information about products in a database.
Data Driven Website
An interactive website kept constantly updated and relevant to the needs of its customers using a database.
Data Warehouse
A logical collection of information, gathered from many different operational databases, that supports business analysis activities and decision-making tasks.
Inconsistent Data Definitions
Every department had its own method for recording data so when trying to share information, data did not match and users did not get the data they really needed.
Lack of Data Standards
Managers need to perform cross-functional analysis using data from all departments, which differed in granularities, formats, and levels.
Poor Data Quality
The data, if available, were often incorrect or incomplete. Therefore, users could not rely on the data to make decisions.
Inadequate Data Usefulness
Users could not get the data they needed; what was collected was not always useful for intended purposes.
Ineffective Direct Data Access
Most data stored in operational databases did not allow users direct access; users had to wait to have their queries or questions answer by MIS professionals who could code SQL.
Extraction, Transformation, and Loading (ETL)
A process that extracts information from internal and external databases, transforms it using a common set of enterprise definitions, and loads into a database warehouse.
Data Mart
Contains a subset of data warehouse information.
Information Cube
The common term for the representation of multidimensional information.
Information Cleansing or Scrubbing
A process that weeds out and fixes or discards inconsistent, incorrect, or incomplete data.
Data Quality Audits
Completed by companies to determine the accuracy and completeness of its data.
Data Mining
The process of analyzing data to extract information not offered by the raw data alone.
Data Mining Tools
Use a variety of techniques to find patterns and relationships in large volumes of information that predict future behavior and guide decision making.
Classification
Assigns records to one of a predefined set of classes.
Estimation
Determines values for an unknown continuous variable behavior or estimated future value.
Affinity Grouping
Determines which things go together.
Clustering
Segments a heterogenous population of records into a number of more homogenous subgroups.
Structured Data
Data that is already in a database or a spreadsheet.
Unstructured Data
Data that does not exist in a fixed location and can include text documents, PDFs, voice messages, emails, and so on.
Text Mining
Analyzes unstructured data to find trends and patterns in words and sentences.
Web Mining
Analyzes unstructured data associated with websites to identify consumer behavior and website navigation.
Cluster Analysis
A technique used to divide information sets into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far part from one another as possible.
Association Detection
Reveals the relationship between variables along with the nature and frequency of the relationships.
Market Basket Analysis
Analyzes such times as websites and checkout scanner information to detect customer’s choices of products and services and for inventory control, shelf-product placement, and other retail and marketing applications.
Statistical Analysis
Performs such functions as information correlations, distributions, calculations, and variance analysis.
Time-Series Information
Time stamped information collected at a particular frequency.
Forecasts
Predictions based on time series information.
Informing
Accessing large amounts of data from different management information systems.
Infographics
Displays information graphically so it can be easily understood.
Data Visualization
Describes technologies that allow users to “see” or visualize data to transform information into a business perspective.
Data Visualization Tools
Move beyond excel graphs and charts into sophisticated analysis techniques such as pie charts, controls, instruments, maps, time-series graphs, and more.
Business Intelligence Dashboards
Track corporate metrics such as critical success factors and key performance indicators and include advanced capabilities such as interactive controls allowing users to manipulate data for analysis.