Intro to Business Information Systems: Ch 6 Flashcards
data granularity
refers to extent of detail within data (fine/detailed or coarse/abstract)
Levels of organizational data
individual, department, enterprise
Formats of organizational data
Document, Presentation, Spreadsheet, Database
Granularities
Detail (Fine) - reports for a salesman, Summary - reports for all salespeople, Aggregate (Coarse) - reports across departments/organizations
4 Primary traits of value of data
Data type, data timeliness, data quality, data governance
transactional data
all data contained in a single business process/unit of work and its primary purpose is to support daily operational tasks
analytical data
all organizational data, and primary purpose is to support performing of managerial analysis tasks
real time data
immediate, up to date data
real time systems
provide real time info in response to requests
data inconsistency
when some data elements has different values
data integrity
measure of quality of data
high quality data
accurate, complete, consistent, timely, unique
low quality data
missing, incomplete, inaccurate, wrong, duplicate
data gap analysis
when company examines data to determine if can meet business expectations, while identifying possible data gaps or missing data
data steward
responsible for ensuring policies/procedures are implemented across organizations and activities as a liaison between MIS department and business
data stewardship
management and oversight of organizations data assets to help provide business users with high quality data that is easily accessible in consistent manner
data governance
refers to overall management of availability, usability, integrity, and security of company data
master data management
practice of gathering data and ensuring it is uniform, accurate, consistent, and complete including entities of customers, suppliers, products, sales, employees, and other critical entities that are commonly integrated a ross organizational systems
data validation
includes tests and evaluations used to determine compliance with data governance policies to ensure correctness of data
database
maintains data about various types of objects (inventory), events (transactions), people (employees), and places (warehouses)
database management system (DBMS)
creates, reads, updates, and deletes (CRUD) data in a database while controlling access and security
structured query language (SQL)
asks users to write lines of code to answer questions against a database
Query by example (QBE) tool
helps users graphically design answers to questions against a database
Data dictionary
compiles all metadata about data elements in the data model
data element (data field)
logical data structures that detail relationships among data elements by using graphics or pictures
metadata
provides details about data
relational database model
stores data in form of logically related, 2D tables
relational database management system
allows users to create, read, update, and delete (CRUD) data in relational database
entity
table that stores data about a person, place, thing, transaction, or event
attributes (columns and fields)
data elements associated with an entity
record
collection of related data elements
primary key
field or group of fields that uniquely identifies a given entity in a table
foreign key
primary key of one table that appears as an attribute in another table and acts to provide logical relationship between two tables
Business advantages of relational database
increased flexibility, increased scalability and performance, reduced data redundancy, increased data integrity (quality), increased data security
physical view of data
physical storage of data on storage device such as hard disk
logical view of data
focuses on how users logically access data to meet particular business needs
data latency
time it takes for data to be stored or retrieved
Business rule
defines how company performs certain aspects of business where the results are yes or no or true or false
Data redundancy
duplication of data or storage of same data in multiple places
data integrity
measure the quality of data
integrity constraints
rules that help ensure the quality of data
relational integrity constraints
rules that enforce basic or fundamental information based constraints
business critical integrity constraints
enforce rules vital to organizations success, these require more insight and knowledge than relational integrity constraints
identity management
broad administration area that deals with identifying individuals in system and controlling their access to resources in that system by associating user rights or restrictions with established identity