BEM 251 Final Flashcards
(33 cards)
Business Value of Improved Decision Making
improving many “small” decisions can add up to large annual value for business
Types of Business Decisions
Unstructured: decision maker must provide judgement, evaluation, and insight to solve problems
- each decision is new, important, and unique
Semi-Structured: only part of problem has clear answer with procedure
Structured: repetitive and routine, defined procedure so not new issue
Senior managers make unstructured
Middle semi-structured
Operational mangers tend to be more structured, common issues
Reasons why investments in I/S does not produce results
- Informational Quality: high quality decisions need high quality information
- Management Filters: managers have selective attention and biases that reject information that doesn’t line up with information
- Organizational Inertia and Politics: strong forces within org resists decision for major changes
High Velocity Automated Decision Making
are made possible with computer algorithms, highly structured decision
- eliminate humans
- require safeguards + monitoring for proper operation and regulation
ex: trading programs
Algorithm
- sequence of unambiguous rules to solve a problem
- use to obtain output for inputs
Business Intelligence
- term used to describe info used to help make decisions
- five component framework, everything
Business Analytics
hardware, software, data
Business Intelligence Vendors
create business intelligence infrastructure purchased by firm
ex: Microsoft, IBM, Oracle
Big Data
combination of massive amounts of structured, semi-structured, and unstructured data
- used for machine learning and targeting data
Data Types
Structured Data: easy to analyze, predefined data
(usually in like Excel formats)
Unstructured Data: information without predefined data model, not organized just large amounts of data
Semi-Structured Data: form of structured data without formal structure but has some hierarchy structure
Metadata: data about data, information about specific set of data
The Six Big V’s of Data
- Volume: amount of data from different sources
- Variety: types of data
- Velocity: speed big data is generated
- Veracity: degree big data can be trusted
- Value: business value of data
- Variability: ways big data can be used and formatted
Data Lake
- large pool of unprocessed data stored in original format
- highly scalable, hold all data types
- no planning/ analysis, that will happen later
- largely used for analysts and data scientists
Data Warehouse
- hold summarized data by business type
ex: OLTP (Online Transaction Processing) - traditional data warehouses use Extract Transform Load (ETL), mapped from source to tables
- data can be accessed by not altered
Data Mart
subset of data warehouse
- summarized/highly focused part of firm’s data for a specific population
- single subject focus, for specific purpose
Knowledge Management
business processes developed for creating, storing, transferring, and applying knowledge
- increase ability to learn from environ. + put into business use
- collection of system to support management info
- knowledge is important to set apart from other companies
Knowledge Transfer (KT): distribution of org. knowledge
ERD (Entry Relationship Diagram)
- Entities: type of things with instances
each instance is a row (an occurrence) - Attributes: fields about entities
columns in a row
PK: Primary Key) 100% unique, no sensitive, and must exist at time of entry
FK (Foreign Key): attribute in one table, PK in another - Relationships: meaningful association between entities, not a process
One-to-one: one instance only go to one instance
One-to-many
Many-to-many: cannot be put into databases, need an associative entity in the middle
Cardinality (0 or 1): minimum and maximum also the three pongs mean many
Relational Database
database that organizes data into structured data that can relate to others on defined relationships
ex. SQL
SQL
Structured Query Language, speaks to the database
Why are systems vulnerable?
- large amounts of data electronically
- accessibility to communication networks
Hardware Problems: (breakdowns, configurations, damage)
Software Problems: (programming errors, installation, unprotected, unauthorized) - disasters
- loss/theft
- use of networks/computers outside of control
Internet Vulnerabilities
- global internet
- large size
- fixed IP are fixed targets
- unencrypted data sent across, can be intercepted
- transmission of sensitive information can be intercepted
Malware (Malicious Software)
Viruses: software that attaches itself to programs/files, modify other programs and infects by inserting code
Worms: independent program that replicates itself to spread with computer networks
Trojan Horses: software that appears benign to cover its malicious
Spyware: install onto computers to track behviour, info and pass information, can also transmit other viruses
Keyloggers: track keystrokes, effective reconnaissance to collect info, precursor to larger attack
Remote Administration Tools (RATs): give full remote control over system
Ransomware: infect computer and locks info demanding fee to be unlocked
Hackers
exploit weaknesses to gain system
“ethical hackers”
System damage and intrusion
Cyberwarfare, Cyberterrorism, Hackitvism
Cybervandalism: intentionally disrupt, destroy, deface
DOS and DDOS
Denial of Service (DOS) - flood server with requests to crash server/network
Distributed Denial of Service (DDOS) - use lots of computers as DoS botnets (infected computers)
Internal Threats
employees - social engineering to get employees to give up information to gave access to company
- weakest link
