Chapter 6 Info Tech Mgmt

Front 1

Database

Back 1

Collection of files that contains record on people, places or things.

Front 2

Entity

Back 2

A category that represents the person, place or thing. In which, we store, collect and maintain info.

Hint 2

Supplier / Part

Front 3

Attribute

Back 3

specific characteristics of each entity.

Front 4

Rational Database

Back 4

organize data into two dimensional tables with rows and columns. One table per entity.

Front 5

fields

Back 5

columns (store data representing an attribute.

Front 6

Rows

Back 6

stores data for separate records or tuples.

Front 7

Key field

Back 7

identifies each record

Hint 7

foreign key- a way to look up field to find data about the supplier of a part.

Front 8

entity relationship diagram

Back 8

clarify table relationships, one to many, & many to many.

Front 9

Normalization-

Back 9

process of streamlining complex groups of data in min. redundant data elements. Min awkward many to many relationships

Front 10

referential integrity

Back 10

rules to ensue relationships between coupled tables remain consistent.

Front 11

database mgmt system

Back 11

specific type of software for creating, storing,organizing & accessing data from a database

Hint 11

mircosoft access DBMS for desktop sys.

DB2 Oracle database nd microsoft SQL used for large frames and midrange com.

Front 12

logical view

Back 12

how end users view data

Front 13

physical view

Back 13

how data are actually structured & organized

Front 14

select

Back 14

create subset of all records meeting criteria

Front 15

join

Back 15

combines relational tables to present the server with no more info than available

Front 16

project

Back 16

create subset consisting of columns in a table. permits users to create new tables

Front 17

data dictionary

Back 17

automated or manual file storing definitions of data elements & their characteristics querying & reporting.

Front 18

Data manipulation language

Back 18

structured query language SQL

Microsoft access query

Front 19

cloud databases

Back 19

relational database engines provided by cloud computing services. Appeal to web-focused businesses

Front 20

Big Data

Back 20

large quantities unstructured & semi-structured data from internet & networked services & applications

Front 21

data warehouses

Back 21

database that store current & historical data that interests decisions makers. Data can be accessed but not altered.

Front 22

Data Mart

Back 22

subset of data warehouses that is highly focused and isolated for a specific populations of users

Front 23

Hadoop

Back 23

Open-source framework from Apache

Designed from big data, combines results into smaller data sets thats easier to analyze

Front 24

In-Memory Computing

Back 24

relies on computer main memory for data storage. shortens query response times

Front 25

Analytic Platforms

Back 25

preconfigured hardware sys. use relational/non-relational tech. to analyze large data sets

Front 26

Online Analytical Processing (OlAP)

Back 26

support multidimensional data analysis enabling users to view the same data in different ways using multiple dimensions. Users able to obtain online answers (in fast time)

Front 27

Data Mining

Back 27

finds hidden patterns and relationships in large databases and infers rules, predict the future

Hint 27

Associations-occurances linked to single event.

Sequences-events linked over time

classifications-patterns describing a group an item belongs to

clustering- discoverning as unclassified grouping

forecasting-use series of values to forecast future values

Front 28

Text Mining

Back 28

Unstructured data acct. for 80% of an org. useful info. allow Businesses to extract key elements and sum. large unstructured data sets.

Front 29

Web Mining

Back 29

discovery and analysis of useful patterns & info from the web

Hint 29

Content mining-content of websites

structure^-websites structural elements

usage^-mines user interaction data gathered by web servers

Front 30

Databases and web

Back 30

firms use the web to make info from their internal databases available to customers & partners. Web interfaces provide familiarity to users & savings over redesigning legacy sys.

Front 31

Info policy

Back 31

states organizations rules for organizing, managing, storing, sharing info

Front 32

Data Administration

Back 32

responsible for specific policies & procedures through which data can be managed as a resource

Front 33

database Administration

Back 33

responsible for design & mgmt group responsible for defining & organizing the structure & content of the database & maintaining the database.

Front 34

Poor data quality

Back 34

major obstacle to successful customer relationship mgmt

Front 35

data quality problems

Back 35

caused by redundant & inconsistent data produced by multiple sys.. Data input errors

Front 36

Data Cleansing

Back 36

detects & corrects incorrect, incomplete, improperly formatted, & redundant data