Hospitality Information Systems and Data Analytics Exam Study Guide

A comprehensive set of vocabulary flashcards covering data foundations, the DIK pyramid, Big Data characteristics, hospitality-specific information systems, types of data analytics, and cognitive decision-operational decision theories.

Data

Unprocessed, raw facts, figures, or representations of reality that lack context or meaning on their own.

Information

Data that has been processed, organized, or structured to make it meaningful by answering questions like what, when, and where.

Knowledge

Information that has been interpreted and validated by individuals through experience, insight, or analysis to answer why and how.

Explicit Knowledge

Information that can be easily documented, codified, and stored in files.

Tacit Knowledge

Personal insights, intuition, experience, and commitment residing only in people's minds.

Structured Data

Highly organized data following a consistent format (words, numbers, alphanumeric) easily stored in rows/columns; managed via SQL in RDBMS.

Unstructured Data

Data that lacks a predefined structure or format and cannot fit into a traditional spreadsheet cell; makes up more than $80\%$ of all data generated today.

Semi-Structured Data

A mix of formats that lacks a strict database structure but contains structured elements for analysis, such as an X post with a timestamp and likes.

Activity Data

Digital traces left by human actions online or offline (e.g., GPS tracking) that reveal what people actually do versus what they say they do.

Conversation Data

Digital chats, emails, and social media interactions mined for content and context to conduct sentiment analysis.

Sensor Data

Real-time data generated by Internet of Things (IoT) devices in the "Web 3.0" era for monitoring and predictive maintenance.

Volume

One of the 5 Vs of Big Data referring to the massive amounts of data generated.

Velocity

One of the 5 Vs of Big Data referring to the high speed at which data is created and processed.

Variety

One of the 5 Vs of Big Data referring to the distinct formats and sources of data.

Veracity

One of the 5 Vs of Big Data referring to the trustworthiness, quality, and accuracy of the data.

Value

The most critical V of Big Data; whether the data helps achieve business goals and delivers a clear Return on Investment (ROI).

Property Management System (PMS)

The operational core of a hotel used by the Front Office and Housekeeping to manage day-to-day operations like bookings and room availability.

Point of Sale (POS)

A system used by F&B outlets or retail shops to log transactions at the time and place of purchase and track inventory.

Customer Relationship Management (CRM)

A dedicated database housing historical guest profiles (spending patterns, preferences) used to tailor marketing and drive loyalty.

Channel Manager (CM)

A centralized platform that syncs and distributes room availability across online channels like OTAs, metasearch engines, and GDS.

Application Programming Interface (API)

The protocols and rules that establish technical communication allowing two disparate software environments to link data.

On-demand self-service

A cloud infrastructure benefit that allows users to instantly change server limits $24/7$ without IT middlemen.

Measured service

A cloud infrastructure benefit featuring a utility-style, pay-as-you-go model for storage.

Descriptive Analytics

Analysis of historical statistics (mean, median, counts) to answer the question "What happened?"

Diagnostic Analytics

Analysis of patterns and relationships to figure out "Why did it happen?"

Predictive Analytics

The process of blending past data trends and intuition to forecast "What is likely to happen next?"

Prescriptive Analytics

The use of insights to advise on "What should we do about it?"

System 1 (Intuition)

Automatic, fast, unconscious, and often emotion-driven thinking based on instinct and gut feelings.

System 2 (Reasoning)

Controlled, rule-bound, logical, and slow analytical thinking; the category to which data analytics belongs.

Operational Decisions

Routine, day-to-day decisions involving direct service delivery that utilize high amounts of data and System 2 logic.

Tactical Decisions

Infrequent, mid-level decisions like managing marketing campaigns that require a balance of System 1 intuition and System 2 data.

Strategic Decisions

Highly impactful, long-term decisions such as corporate mergers that are judgment-heavy but require foundational data verification.

Sense-Checking

The role of human judgment in evaluating data for completeness and real-world accuracy to see if it makes logical sense.

Enrichment

Adding real-world context or explanations to numbers by accounting for external circumstances that data might miss.

Challenger of Judgment

A role of data analytics where solid metrics are used to challenge biased, emotional, or gut-based choices.

No-Brainer

A situation where data points so clearly to a single fact that human judgment is not necessary to make the decision.