Itm Chapter 3

Front 1

Zettabyte

Back 1

1000 exabytes

Front 2

Difficulties in managing data: 4

Back 2

Amount of data increasing exponentially
Data are scattered throughout organizations and collected by many individuals using various methods and devices.
Data come from many sources.
Data security, quality, and integrity are critical.

Front 3

Data governance

Back 3

is an approach to managing information across an entire organization

Front 4

Master data management

Back 4

is a process that provides companies with the ability to store, maintain, exchange, and sychnronize a consisten, accurate, and timely "single version of the truth" for the company's core master

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Master data

Back 5

are a set of core data, such as customer, product, employee, vendor, geographic location, and so on, that span all of an enterprise’s information systems.

Front 6

Master Data
Transaction Data
-What is difference, example

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Master data is the different sets like Student, Course, Time, Weekday while Transaction data is whats transacting like Nicole Vouzianas ITM 145 Mon Wed

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Data redundancy:

Back 7

The same data are stored in many places

Front 8

Data isolation:

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Applications cannot access data associated with other applications.

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Data inconsistency:

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Various copies of the data do not agree.

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Data security:

Back 10

Keeping the organization’s data safe from theft, modification, and/or destruction.

Front 11

Database management system (DBMS) minimize the following problems:

Back 11

Data redundancy
Data isolation
Data inconsistency

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DBMSs maximize the following issues:

Back 12

Data security
Data integrity
Data independence

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Data integrity:

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Data must meet constraints (e.g., student grade point averages cannot be negative).

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Data independence:

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Applications and data are independent of one another. Applications and data are not linked to each other, meaning that applications are able to access the same data

Front 15

Data Hierarchy

Back 15

Bit
Byte
Field
Record
File (or table)
Database

Front 16

A Bit

Back 16

is a binary digit, a "0" or a "1"

Bit
Byte
Field
Record
File (or table)
Database

Front 17

A Byte

Back 17

a group of eight bits that represents a single character (ex. a letter, a number, or symbol)

Bit
Byte
Field
Record
File (or table)
Database

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A field

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is a group of logically related characters (ex. a word, small group of words, or identification number)

Bit
Byte
Field
Record
File (or table)
Database

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A record

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is a group of logically related fields (ex. student in a university database)

Bit
Byte
Field
Record
File (or table)
Database

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A file

Back 20

is a group of logically related records

Bit
Byte
Field
Record
File (or table)
Database

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A database

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is a group of logically related files that stores data and the associations among them

Bit
Byte
Field
Record
File (or table)
Database

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Data model

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-is a diagram in a DBMS that represents the entities in the database and their relationships.
Entity
Attribute
Primary key
Secondary keys

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Entity

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Is a person, place, thing, or event about whcih information is maintained. A record generally describes an entity

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Attribute

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each characteristic or quality describing a particular entity

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Primary key

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is a field or attribute that uniquely identifies a record

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Secondary key

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another field that has some identifying info but typically do not identify the file with complete accuracy

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The Data Model

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is a diagram that represents the entities in the database and their relationships

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entity-relationship (ER) modeling.
Entity-relationship (ER) diagram

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modeling- The process of designing a database by organzing data entities to be used and identifying the relationships among them

Hint 28

diagram- document that shows data entities and attributes and relationships among them (rectangles for entities-- student, class, professor, diamonds for relationships-- can have)

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Entity-relationship (ER) consists of..

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Entities, attributes, and relationships

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Entity classes

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are groups of entities of a certain type

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Cardinatlity

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refers to max number of times an instance of one entity can be associated with an instance in the related entity (1 or many)

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Modality

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refers to min number of times an instance of one entity can be associated with an instance in the related entity (1 or 0)

Front 33

An instance of an entity class is

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the representation of a particular entity in an entity class, ex. John is the instance of the STUDENT entity class

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Entity instances have identifiers which

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are attributes that are unique to that entity instance, Ex. attributes for a CLASS entity are ClassName, ClassTime, ClassPlace

Front 35

Database management system (DBMS)

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is a set of programs that provides users with tools to add, delete, access, and analyze data stored in one location

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The relational database model

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is based on the concept of two-dimensional tables (records listed in rows, and attributes listed in colums)

Front 37

Structured query language (SQL)

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allows users to perform complicated searches by using relatively simple statements or keywords

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Query by example

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database language that allows users to fill out a grid or template to construct a sample or description of the data they wants (can use drag drop features)

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(SQL) a time when you would use it

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you want to know who will graduate with cum laude, so you would query student relational database with an SQL statement Selecting student name where grade point average is <3.6

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Data Dictionary

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-defines the format necessary to enter the data into the database
-collection of definitions of data elements; data characteristics that use the data elements

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Normalization

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is a methof for analyzing and reducing a relational database to its more steamlined form for minimum redundancy, maximum data intergrity, and best processing performance--> when data are normalized attributes in table depend only on the primary key

Front 42

A data warehouse

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is a repository of historical data organized by subject to support decision makers in the organization. Bc so expensive, used by large companies

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A data mart

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is a low-cost, scaled-down versaion of a data warehouse that is deisnged for the end-user needs in a strategic business unit (SBU) or department

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Data warehouses and Data Marts characteristics

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Organized by business dimension or subject
Use online analytical processing
Integrated
Time variant
Nonvolatile
Multidimensional

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Organized by business dimension or subject

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data are organized by subject, ex. by customer, vendor, product, price level

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Use online analytical processing(OLAP)

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involves the analysis of accumulated data by end users (usually in data warehouse)

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Historical data

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in data warehouses can be used for identifying trends, forecasting, and making comparisons over time

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not OLAP, online transaction processing, not for data warehouses or data marts

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processing of business transactions online as soon as they occur. Objectives are speed and efficiency

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Relational databases store data in 2 dimensional tables while, data warehouses and marts store data in more than two dimensions

Back 49

thats all

Front 50

Benefits of Data Warehousing

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1. access data quickly and easily
2. Conduct extensive analysis
3. Consolidated view

Front 51

Access data quickly and easily (benefits of Data Warehousing)

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End users can access data quickly and easily via Web browsers bc they are located in one place

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conduct extensive analysis
(benefits of Data Warehousing)

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End users can conduct extensive analysis with data in ways that may not have been possible before

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Consolidated view
(benefits of Data Warehousing)

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End ueser have a consolidated view of organizational data

Front 54

Knowledge management

Back 54

is a process that helps organizations manipulate important knowledge that is part of the organization’s memory, usually in an unstructured format.

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Knowledge

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that is contextual, relevant, and actionable. Information in actions. Ex. creating class schedule, schedule would be info and then awareness of your work schedule, your major, desired social life, could be constructed as knowledge. knowledge can be excercised to solve a problem

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Intellectual capital

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is another term often used for knowledge.

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Explicit knowledge

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objective, rational, technical knowledge that has been documented.
Examples: policies, procedural guides, reports, products, strategies, goals, core competencies
(iceberg above the waterline)

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Tacit knowledge:

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cumulative store of subjective or experiential learning. Highly personal and hard to formalize.
Examples: experiences, insights, expertise, know-how, trade secrets, understanding, skill sets, and learning
(iceberg below the waterline)

Front 59

Knowledge management systems (KMS)

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refer to the use of information technologies (the internet, intranets, etranets, databases) to systemize, enahnce, and expedite intrafirm and interfirm knowledge management. Bringing explicit and tacit knowledge in formal information systems.

Front 60

Knowledge management systems are meant to help an organization

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cope with turnover, rapid change, and downsizing by making the expertise of the organization's human capital widely accessible

ALSO KMS improve customer service, more efficient product devolpment, and impvoed employee moral and retention

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Best practices (KMS)

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Are the most effective and efficient ways of doing things, readily avaialbe to a wide range of employees

Front 62

2 problems associated with KMS

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people must actually want to share their personal tacit knowledge, to encourage this orgs must create a knowledge management culture that rewards employees who add their expertise to the knowledge base. Second, the knowledge base must be continually maintained and updated, adding and deleting info

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A functioning KMS follows a cycle that consists of

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six steps: creat knowledge, capture knowledge, refine knowledge, store knowledge, manage knowledge, disseminate knowledge

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clicksteam data

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data collected about user behavior and browsing patterns by monitoring users' activities when they visit a Web site

Front 65

indentifiers

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attributes that are unique to an entity instance

Front 66

other terms for knowledge

Back 66

intellectual captial or intellectual assets

Front 67

multidimensional structure

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storage of data in more than 2 dimensions; a common representation is the data cube

Front 68

table

Back 68

a grouping of logically related records