Database Management (DBMS)

database

well-designed, organized, + carefully managed collection of data

should help an organization achieve its goals, can contribute to organizational success (provides managers + decision makers with timely, accurate, + relevant information built on data)

most organizations have multiple databases

data

raw facts

information

collection of organized + processed data, has additional value beyond the value of the individual facts

knowledge

proides awareness + understanding of a set of information, shows how information can support a specific task or be used to reach a decision

value of information

diversity linked to how it helps decision makers achieve their organizations goals, helps people perform tasks efficiently + effectively

benefits gained through use of high-quality data

improves decision making (removes guess work, risk taking)

increase customer satisfaction (bad data causes unfavorable data errors)

increase sales (accurate customer targeting + communications, enables successful up-sell + cross-sell suggestions)

improves innovation

raises productivity (no need to correct data errors)

ensures compliance

characteristics of high-quality data

accessible, accurate, complete, economical, relevant, reliable, timely, verifiable

data hierarchy

entity, file, attribute, domain, data item, record, primary key, foreign key

entity

person, place, or thing for which data is collected, stored, + maintained

file

collection of entities

attribute

characteristic of an entity

domain

range of allowable values for a data attribute

data item

specific value of a data attribute

record

collection of attributes about a specific entity

primary key

attribute or set of attributes that uniquely idenfies the record

foreign key

attribute in one table that refers to the primary key in another table

database approach to data management

multiple information systems share a pool of related data

database management system (DBMS)

group of programs provided by the DBMS supplier

programs used to access + manage a database

provides an interface between the database + its users + other application programs

schema

description defining the databases logical + physical structure, identifies tables + its attributes + relationships between attributes + tables

data definition language (DDL)

collection of intructions + commands, defines + describes data + relationships in a specific database

data dictionary

detailed description of data stored in the database

adherance to data dictionary standards

makes it easy to share data among organizations

dbms function

interface between application program + database

concurrency control

addresses situation where two or more users or applications access the same record at the same time

query by example (QBE)

usual approach to developing database queries or requests

data manipulation language (DML)

allows users to access + modify the data, make queries, + generate reports

data cleansing

detects + then corrects or deletes incomplete, incorrect, inaccurate, or irreleant records residing in a database

methods of data cleansing

cross-checking data, using data enhancement to augment the data in a database by adding related information

database design

store all relevant data, provide quick access + easy modification, reflect organizations business processes

considerations of database design

content + access, logical structure + physical organization, response time, archiving, security

data modeling

tool used to design a database, enterprise data modeling, occurs at organization level/business application level

enterprise data model

identifies data entries + data attributes of greatest interest to the organization, identifies their associated standard data definitions, data length, + format, domain of valid values, + any business rules for their use

entity-relationship (ER) diagram

data model used to analyze + communication data needs, works at the individual project/application level

uses graphic symbols → identify data entities + their associated data attributes, identify the relationships among the entities of interest

fundamental characteristics of relational databases

data is organized into relations, rows represent entities + columns attributes, rows uniquely identifed by a primary key

column table data

integer numbers, decimal number, date, tect, etc.

constrained to be certain type, length, or to have a value between two limits

manipulating data in a relational database

selecting (eliminating rows according to certain criteria_

projecting (eliminating columns in a table)

joining (combine two or more tables through common data attributes to create a new table)

data normalization (eliminates data redundancy)

sql

special purpose programming language, used for accessing + manipulating relational database data

acid properties

autonomy, consistency, isolation, durability

guarentees the database transactions are processed reliably

ensures the integrity of data in the database

database of a service (DaaS)

database store on service providers servers, accessed by service subscriber over the internet, administration handled by the service provider

advantages → eliminates the installation, matinence, + monitoring of in-house databases

data management

defines the process by which data is obtained, certified fit for use, stored, secured, + processed

ensures data accessibility, reliability, + timeliness meet the data users needs

ensures data can be trusted + used by the entire organization

ensures people identified + in place who are responsible for fixing + preventing issues with data

database administrator (DBA)

skilled + trained IS professionals, holds dicussions with business users

defines their data needs, applied DPL to craft a set of databases to meet those needs, tests + evaluates databases, monitorys performance + implements changes to improve response time, assures data is secure

data steward

typically non-IS emplyees, manages critical data entities or attributes

data lifecycle management (DLM)

policy based approach, manages enterprises data flow (from initial acquisition/creation + storage, until data becomes outdated + is deleted)