Chapter 3: Data and Business Intelligence Flashcards
Database
collection of related data stored in central or multiple locations. (Group of files)
Data Hierarchy Components (3)
Data File
Record
Field
Data File
Group of related records
Records
row of data files and fields
Field
column in data file
Database Design: Physical View and example
one physical view to store and retrieve data etc CD, Tape, Disk
Database Design: Logical View and 3 structures
The form of the data model and how data is presented to users
1. Hierarchical Model
2. Network Model
3. Relational Model
Hierarchical Model
Distinct authority and sequence of data, order to look up files, add or delete lines
Network Model
Different Path Sequences of data to look up files. Can change and edit
Relational Model and contains a…
Data Files linked through keys etc spreadsheets
and contains a data dictionary
Relational Model and contains a…
Data Files linked through keys etc spreadsheets
and contains a data dictionary
Data Dictionary Components and description (3)
Field Name (attribute)
Field Data Type (type)
Validation (Rule)
Primary Key
Unique identifier for each record
Foreign Key
establishes relationships among multiple tasks, primary key appears in another table
Normalization
eliminates redundant data, improves efficiency
Why don’t we have one large table or large data file?
Smaller tables increase efficiency, relevancy and reduce redundancy
Database Management Software
creating, storing, maintaining and accessing database files
2 Methods to access data files
Sequential, Random, Indexing
Sequential
Specific or numerical order
Random
Any order, regardless of location
Indexing
Access sequential or random, combination of both
Database Management Software: Database Engine
responsibilities and tasks
responsible for data storage and manipulation, retrieval
tasks: converts logical requests from users into physical equivalents
Database Management Software: Data Definition 3 tasks
create and maintain data dictionary
define structure of files
change fields
Database Management Software: Data Manipulation
4 major functions and second component
add, delete, retrieve, modify
Query Language
Query Language: what are they
4 major functions
conditional words
Keywords that specify actions
Inset, delete, select and update
other: from, where, order, and, not, or, join (conditions)
Query by example:
Process
construct statement of query forms, graphical interface
request data from database and comes in database table or formats using query language code
Database Management Software: Application Generation
design elements of an application using a database
Data entry:
interactive menus and interfaces with other programming languages
Database Management Software: Data Administration (5 tasks)
Backup and recovery
security
change management
design
evaluation
Object Oriented Databases: what is it?
Attributes
Methods
database similar to high level codes that represent real world entities
Attributes: characteristics and qualities
Methods: what they can do
Encapsulation:
Group attributes and method of class to restrict modification
Inheritance:
New class have same attributes and methods with modified specification
Data Driven Website
useful for (2)
interface to database, retrieval of data and enter data
e-commerce and forums/discussions
Distributed Databases
- servers (3)
- pros
- cons
Data stored in multiple servers
fragmentation, replication, allocations
pros: faster queries, minimize cost and failures
cons: less secure
Data-warehouse and data comes from
collection of data support decision-making applications and generating business intelligence
data comes from internal and external
Data-warehouse process (ETL)
extraction - collect data
Transformation - correct format to meet needs
loading - transfer data to warehouse
Online Analytical Processing (OLAP)
organize data, provide multidimensional analysis (cube)
Data mining analysis
discover patterns and relations
Information and reports for decision making (3)
cross reference, find patterns and trends, analyze historical data quickly
Types of Data (3)
Raw: original form
Summary: subtotals of categories
Metadata: info etc content, quality, origin, condition
Data Mart
Advantage
Smaller version of data warehouse used by single department or function
Advantage: access faster, easy to create, less expensive
Data Lake
gathers and stores raw data in a central locations
Big Data 5 V’s and description
Velocity: process time and streams, data collection
Value: probability, patterns, correlation
Veracity: Quality of data or errors, validity and reliability
Variety: Format and structure of data
Volume: how much data, records, files
Business Analytics
Descriptive
Predictive
Prescriptive
data and statistical models to gain insight into the data
what happened
predict future or events
prepare and how to prevent
