MIS chapter 6

The four primary reasons for low-quality information are:

-Online customers intentionally enter inaccurate information to protect their privacy. -Different systems have different information entry standards and formats. -Data-entry personnel enter abbreviated information to save time or erroneous information by accident. -Third-party and external information contains inconsistencies, inaccuracies, and errors

regression model

A statistical process for estimating the relationships among variables. Regression models include many techniques for modeling and analyzing several variables when the focus is on the relationship between a dependent variable and one or more independent variables.

optimization model

A statistical process that finds the way to make a design, system, or decision as effective as possible, for example, finding the values of controllable variables that determine maximal productivity or minimal waste.

Data-driven decision management

An approach to business governance that values decisions that can be backed up with verifiable data.

what is the relationship between entities and attributes

Each record in an entity occupies one row in its respective table.

forecasting model

Time-series information is time-stamped information collected at a particular frequency. Forecasts are predictions based on time-series information allowing users to manipulate the time series for forecasting activities.

identity management

a broad administrative area that deals with identifying individuals in a system (such as a country, a network, or an enterprise) and controlling their access to resources within that system by associating user rights and restrictions with the established identity

data artist

a business analytics specialist who uses visual tools to help people understand complex data

data broker

a business that collects personal information about consumers and sells that information to other organizations

repository

a central location in which data is stored and managed

record

a collection of related data elements

recommendation engine

a data-mining algorithm that analyzes a customer's purchases and actions on a website and then uses the data to recommend complementary products

primary key

a field that uniquely identifies a given record in a table

data warehouse

a logical collection of information—gathered from many different operational databases—that supports business analysis activities and decision-making tasks

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

extraction, transformation, and loading (ETL)

a process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse. The data warehouse then sends subsets of the information to data marts

Information cleansing or scrubbing

a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information.

prediction

a statement about what will happen or might happen in the future, for example, predicting future sales or employee turnover

data lake

a storage repository that holds a vast amount of raw data in its original format until the business needs it

data map

a technique for establishing a match, or balance, between the source data and the target data warehouse

cluster analysis

a technique used to divide an information set 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 apart as possible

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 set

an organized collection of data

structured query language (SQL)

asks users to write lines of code to answer questions against a database

comparative analysis

can compare two or more data sets to identify patterns and trends

data dictionary

compiles all of the metadata about the data elements in the data model

data mart

contains a subset of data warehouse information.

outlier

data value that is numerically distant from most of the other data points in a set of data

physical view of information

deals with the physical storage of information on a storage device

business rule

defines how a company performs certain aspects of its business and typically results in either a yes/no or true/false answer.

data visualization

describes technologies that allow users to see or visualize data to transform information into a business perspective

estimation analysis

determines values for an unknown continuous variable behavior or estimated future value. Estimation models predict numeric

variety

different forms of structured and unstructured data

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

Business-critical integrity constraints

enforce business rules vital to an organization's success and often require more insight and knowledge than relational integrity constraints

dirty data

erroneous or flawed data (see Figure 6.15). The complete removal of dirty data from a source is impractical or virtually impossible

market basket analysis

evaluates such items as websites and checkout scanner information to detect customers' buying behavior and predict future behavior by identifying affinities among customers' choices of products and services

data scientist

extracts knowledge from data by performing statistical analysis, data mining, and advanced analytics on big data to identify trends, market changes, and other relevant information

three terms that represent the data elements associated with an entity

fields attributes columns

three terms associated with entities

fields, columns, attributes

logical view of information

focuses on how individual users logically access information to meet their own particular business needs

creates, reads, updates, deletes

four functions that a database management system can perform on data in a database

query-by-example

helps users graphically design the answer to a question against a database

source data

identifies the primary location where data is collected

dynamic information

includes data that change based on user actions

static information

includes fixed data incapable of change in the event of a user action

data validation

includes the tests and evaluations used to determine compliance with data governance polices to ensure correctness of data. Data validation helps to ensure that every data value is correct and accurate.

The Four Primary Traits of the Value of Information

info type info timeliness info quality info governance

information integrity

is a measure of the quality of information

Information redundancy

is the duplication of data, or the storage of the same data in multiple places

data models

logical data structures that detail the relationships among data elements using graphics or pictures

database

maintains information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses)

algorithms

mathematical formulas placed in software that performs an analysis on a data set

real-time information

means immediate, up-to-date information

data visualization tools

move beyond Excel graphs and charts into sophisticated analysis techniques such as controls, instruments, maps, time-series graphs, and more they can help uncover correlations and trends in data that would otherwise go unrecognized

Information integrity issues

occur when a system produces incorrect, inconsistent, or duplicate data.

data gap analysis

occurs when a company examines its data to determine if it can meet business expectations, while identifying possible data gaps or where missing data might exist.

Information inconsistency

occurs when the same data element has different values

analysis paralysis

occurs when the user goes into an emotional state of over-analysis (or over-thinking) a situation so that a decision or action is never taken, in effect paralyzing the outcome. In the time of big data, analysis paralysis is a growing problem

Infographics (information graphics)

present the results of data analysis, displaying the patterns, relationships, and trends in a graphical format

distributed computing

processes and manages algorithms across many machines in a computing environment

real-time systems

provide real-time information in response to requests

metadata

provides details about data. For example, metadata for an image could include its size, resolution, and date created

information granularity

refers to the extent of detail within the information (fine and detailed or coarse and abstract)

data governance

refers to the overall management of the availability, usability, integrity, and security of company data.

data steward

responsible for ensuring the policies and procedures are implemented across the organization and acts as a liaison between the MIS department and the business

affinity grouping analysis

reveals the relationship between variables along with the nature and frequency of the relationships

Relational integrity constraints

rules that enforce basic and fundamental information-based constraints

integrity constraints

rules that help ensure the quality of information

entity

stores information about a person, place, thing, transaction, or event

relational database mode

stores information in the form of logically related two-dimensional tables

velocity

the analysis of streaming data as it travels around the internet

fast data

the application of big data analytics to smaller data sets in near-real or real-time in order to solve a problem or create Page 179business value

data aggregation

the collection of data from various sources for the purpose of data processing

virtualization

the creation of a virtual (rather than actual) version of computing resources, such as an operating system, a server, a storage device, or network resources

attributes

the data elements associated with an entity

data stewardship

the management and oversight of an organization's data assets to help provide business users with high-quality data that is easily accessible in a consistent manner.

content creator

the person responsible for creating the original website content

content editor

the person responsible for updating and maintaining website content

Master data management (MDM)

the practice of gathering data and ensuring that it is uniform, accurate, consistent, and complete, including such entities as customers, suppliers, products, sales, employees, and other critical entities that are commonly integrated across organizational systems

data mining

the process of analyzing data to extract information not offered by the raw data alone

data profiling

the process of collecting statistics and information about data in an existing source

anomaly detection

the process of identifying rare or unexpected items or events in a data set that do not conform to other items in the data set

classification analysis

the process of organizing data into categories or groups for its most effective and efficient use

volume

the scale of data

data element

the smallest or basic unit of data

data element

the smallest or basic unit of information

data latency

the time it takes for data to be stored or retrieved

veracity

the uncertainty of data, including biases, noise, and abnormality

Time-series information

time-stamped information collected at a particular frequency.

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

T/F: Business-critical integrity constraints tend to mirror the very rules by which an organization achieves success.

true

T/F: databases today scale to exceptional levels, allowing all types of users and programs to perform information processing and information-searching tasks

true

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

why does a database offer increased information security

various security features of databases ensure that individuals have only certain types of access to certain types of information

competitive monitoring

when a company keeps tabs of its competitors' activities on the web using software that automatically tracks all competitor website activities such as discounts and new products