Management Information Systems: Strategic Metrics, Ethics, Security Questions and answers with 100% accuracy(GUARANTEED SUCCESS), and Data Technologies

Chief Information Officer (CIO)

Responsible for overseeing all uses of MIS and ensuring MIS strategically aligns with business goals and objectives.

Chief Data Officer (CDO)

Responsible for determining the types of information the enterprise will capture, retain, analyze, and share.

Chief Technology Officer (CTO)

Responsible for ensuring the throughput, speed, accuracy, availability, and reliability of the MIS.

Chief Security Officer (CSO)

Responsible for ensuring the security of business systems and safeguarding against hackers and viruses.

Chief Privacy Officer (CPO)

Responsible for ensuring the ethical and legal use of information within a company.

Chief Knowledge Officer (CKO)

Responsible for collecting, maintaining, and distributing company knowledge.

Project

A temporary activity a company undertakes to create a unique product, service, or result.

Metrics

Measurements that evaluate results to determine whether a project is meeting its goals.

Critical Success Factors (CSFs)

The crucial steps companies perform to achieve their goals and objectives and implement strategies.

Key Performance Indicators (KPIs)

The quantifiable metrics a company uses to evaluate progress toward critical success factors.

Efficiency MIS Metrics

Measure the performance of MIS itself.

Effectiveness MIS Metrics

Measure the impact MIS has on business processes and activities.

Optimal Operation

Occurs in the area of high efficiency and high effectiveness.

Benchmark

Baseline values that the system seeks to attain.

Benchmarking

The process of continuously measuring system results, comparing those results to benchmark values, and identifying steps to improve performance.

Ethics

The principles and standards that guide our behavior toward other people.

Information Ethics

Govern the ethical and moral issues arising from the development and use of information technologies.

Privacy

The right to be left alone when you want to be, to have control over personal possessions, and not to be observed without consent.

Confidentiality

The assurance that messages and information remain available only to those authorized to view them.

Information Security

The protection of information from accidental or intentional misuse by persons inside or outside an organization.

Downtime

A period of time when a system is unavailable, which can be very costly to a business.

Cybersecurity

Prevention, detection, and response to cyberattacks.

Hacker

Experts who use their knowledge to break into computers/networks for profit or challenge.

Virus

Software written with malicious intent to cause annoyance or damage.

Denial-of-Service Attack (DoS)

Attacks that flood a network with requests to prevent legitimate users from accessing it.

Phishing

A technique to gain personal information for identity theft, usually via fraudulent email.

Pharming

Reroutes requests for legitimate websites to false websites.

Insiders

A security threat as the biggest issue is often a people issue, not a technical one.

Authentication

Confirming users' identities.

Authorization

Giving someone permission to do or have something.

Content Filtering

Prevents emails with sensitive information from transmitting and stops spam/viruses.

Encryption

Scrambles information so that if stolen, it is unreadable.

Firewall

Hardware/software that guards a private network by analyzing incoming and outgoing information.

Detection and Response (Attacks)

Technologies to mitigate damage if prevention/resistance fail.

Intrusion Detection Software

Full-time monitoring tools that search for patterns in network traffic to identify intruders.

Data Challenges

Many organizations are data rich and information poor, struggling to turn data into business intelligence.

Organizational data

Difficult to access and contains both structured data (in databases) and unstructured data (voice mail, text messages, videos).

Reasons Business Analysis is Difficult from Operational Systems

Inconsistent data definitions, lack of data standards, poor data quality, inadequate data usefulness, and ineffective direct data access.

Data Warehouse

A logical collection of data gathered from many different operational databases that supports business analysis and decision-making tasks.

Primary Purpose of Data Warehouse

To aggregate data throughout an organization into a single repository for decision-making.

Data Warehouses in the 1990s

Provided the ability to support executive decision-making without disrupting day-to-day operations.

Data Aggregation

The process of compiling information.

Extraction, Transformation, and Loading (ETL)

The process used to move data from the internal and external databases into the data warehouse (or data marts).

Data Mart

A smaller segment of a data warehouse typically designed for a specific business line or department.

Data Lake

A storage repository that holds a vast amount of raw data in its original format until the business needs it.

Dirty Data

Inaccurate, duplicate, misleading, non-integrated, incorrect, non-formatted data, or data that violates business rules.

Data Cleansing (Scrubbing)

The process of weeding out and fixing or discarding inconsistent, incorrect, or incomplete information.

The Cost of Data Quality

Obtaining 'Perfect Information' (100% completeness and 100% accuracy) is pricey; managers must balance accuracy and completeness with cost.

Data Visualization

Technologies that allow users to 'see' or visualize data to transform it into a business perspective.

Infographic (Information Graphic)

Used by data artists to display patterns, relationships, and trends in a visual format.

Business Intelligence Dashboards

Track corporate metrics such as CSFs and KPIs and include interactive controls for data manipulation.

Blockchain

A specific type of database and a type of distributed ledger.

Distributed Ledger

Records classified and summarized transactional data.

Structure of Blockchain

Structures data into chunks (blocks) that are chained together, unlike a traditional database that uses tables.

Blocks in Blockchain

Data structures containing: Hash (the block's unique identifier/fingerprint), Previous Hash (hash of the prior block), and Data (transactional data).

Key Features/Advantages of Blockchain

Decentralized, Immutability, Digital Trust, Consensus Building.

Proof-of-Work

Has two main goals: to verify the legitimacy of a transaction (avoid double-spending) and to create new digital currencies by rewarding miners.

Organizational Levels and Decisions

Organizational decisions are made at three primary levels.

Decision-Making Challenges

Managers face challenges including: Need to analyze large amounts of information, Must make decisions quickly, Must apply sophisticated analysis techniques to make strategic decisions.

The Six-Step Decision-Making Process

1. Problem Identification 2. Data Collection 3. Solution Generation 4. Solution Test 5. Solution Selection 6. Solution Implementation.

Transaction Processing System (TPS)

Supports day-to-day operational or structured decisions using transactional information.

Decision Support System (DSS)

Supports managerial analysis or semi-structured decisions using analytical information.

Executive Information System (EIS)

A specialized DSS that supports senior-level executives and unstructured, long-term, nonroutine decisions.

Artificial Intelligence (AI)

Simulates human intelligence such as the ability to reason and learn.

Weak AI

Machines make decisions based on reasoning and past data.

Strong AI

Works toward providing brain-like powers to machines, making them as intelligent as humans.

Types of AI

Expert Systems, Neural Networks, Genetic Algorithms, Intelligent Agents, Virtual Reality (VR), Augmented Reality (AR), Machine Learning (ML).

Training Problems in AI

Overfitting and Underfitting.

Bias

A disproportionate weight for or against an idea.

Systems Development Life Cycle (SDLC)

The overall process for developing information systems from planning through maintenance.

Planning Phase

Establish a high-level plan and determine project goals.

Analysis Phase

Analyze end-user business requirements and refine project goals into defined functions.

Design Phase

Establish descriptions of desired features and operations (screen layouts, business rules, etc.).

Development Phase

Transform detailed design documents into the actual system.

Testing Phase

Bring all project pieces together in a testing environment to eliminate errors/bugs and verify system meets requirements.

Implementation Phase

Place the system into production for users to begin business operations.

Maintenance Phase

Perform changes, corrections, additions, and upgrades to ensure the system continues to meet business goals.

Software Costs

The later in the SDLC an error is found, the more expensive it is to fix.

Waterfall Methodology

A sequence of phases where the output of each phase becomes the input for the next (linear progression).

Agile Methodology

Aims for customer satisfaction through early and continuous delivery of useful software components developed by an iterative process using bare minimum requirements.

Rapid Application Development (RAD) Methodology

Emphasizes extensive user involvement in the rapid and evolutionary construction of working prototypes to accelerate development.

Extreme Programming (XP) Methodology

Breaks a project into tiny phases; developers cannot proceed until the first phase is complete.

Rational Unified Process (RUP)

A framework that breaks software development into four gates: Inception, Elaboration, Construction, and Transition.

Scrum

Uses small teams to produce small pieces of deliverable software using sprints (30-day intervals) and daily stand-up meetings.

Project Management

The application of knowledge, skills, tools, and techniques to project activities to meet project requirements.

Project Manager

An individual expert in planning and management who defines, develops, and tracks the project plan to ensure completion on time and on budget.

Project Deliverable

Any measurable, tangible, verifiable outcome, result, or item produced to complete a project.

Project Milestone

Represents key dates when a certain group of activities must be performed.

Project Management Office (PMO)

An internal department that oversees all organizational projects.

Project Stakeholder

Individuals and organizations actively involved in the project or whose interests are affected by its execution or completion.

Executive Sponsor

The person or group who provides the financial resources for the project.

Triple Constraint

The Project Management Interdependent Variables are Time, Resources, and Scope, with the goal of Managing Expectations.

Feasibility

Types of feasibility studies: Economic, Operational, Schedule, Technical, Political, and Legal.

Outsourcing

An arrangement where one organization provides a service for another that chooses not to perform it in-house.

Onshore Outsourcing

Sourcing to a company in the same country.

Nearshore Outsourcing

Sourcing to a company in a nearby country.

Offshore Outsourcing

Sourcing to a company in a farther-away country (often sold as 'inexpensive good work').

Moore's Law

Refers to the computer chip performance per dollar doubling every 18 months.

Sustainable (Green) MIS

Describes the production, management, use, and disposal of technology in a way that minimizes environmental damage.