Exam 2 Flashcards
Data vs Information
Data is raw and chaotic collected facts, information is data that has been organized to form a conclusion
6 Elements of an IT system
Bit- binary digit
Byte- group of bits to make a character
Field- word or date or smth
Record- one instance/ row
File- group of records
Database- logically related files
Structured Data
Defined numerical data that can be put in a spreadsheet
Unstructured Data
Images, video, audio, takes up more room, cannot fit into spreadsheet :(
Relational Database
Interrelated tables connected by similarities
Object Oriented Database
Data is connected by objects, objects are similar to a record
NoSQL Database
No structure, everything is stored individually
5 Vs of Big Data
Volume- quantity
Velocity- speed data is generated
Variety- diversity of data
Veracity- accuracy and truthfulness
Value- (most important) ability to be converted into useful information
Dashboard
Interactive real time reports
Visualization
Graphical representation of data
4 Categories of data analytics
Descriptive- what happened
Diagnostic- why did it happen
Predictive- what is likely to happen
Prescriptive- what should we do about it
7 stages of SDLC
Planning- identify needed resources
Analysis- identify requirements
Design- requirements into specifications
Development- create the system
Testing- validate the system
Implementation- give it to users
Maintenance- keep that shit going
Waterfall vs Agile
Waterfall- traditional method each step is done after the previous is completed
Agile- hop around more flexible
Sprints, product backlogs, and sprint backlogs
sprint- single iteration of project
product backlogs- list of features
sprint backlogs- what the team will work on during current sprint
Elements to be considered when choosing a data base
Data variety, data volume, scalability, and purpose
Conceptual vs logical vs physical ERD
Conceptual - identify tables and relationships
Logical- more detail, field names in the tables
Physical- technical design
Primary vs Foreign key
Primary- field used to identify the record
Foreign- primary key used in a different table
Data redudancy
same data being stored in multiple places
Referral integrity
FK can’t exist without it being a PK somewhere else
Entity integrity
PK cannot be empty
Cardinality
Numeric relationship between data in two tables
Plurality
How many records in table 2 relate to table 1
Optionality
If there must be a record in table 2 for it to exist in table 1
SQL
Structure query language to pull information
