Workshop 1 – Data types Takeaways

Vocabulary flashcards covering different data types, the characteristics of Big Data, and strategies for data collection.

Structured Data

Data that has a consistent format (words, numbers, or alphanumeric) and is organized in rows/columns in databases or spreadsheets, making it easier to analyze and cheaper to store.

Unstructured Data

Data that is very rich in insights but harder and costlier to analyze than structured data, requiring specialized tools; examples include video, images, and audio files.

Semi-Structured Data

Data that contains a combination of structured and unstructured elements, such as a social media post with structured metadata (author, date) and unstructured conversation text.

Internal Data

Data owned by the organization, such as HR data or customer service calls, which is cheap and accessible but may be limited in scope.

External Data

Data sourced from outside an organization, such as social media or government databases, which is often richer and more diverse but may come with costs and access risks.

General Data Protection Regulation (GDPR)

A regulation that companies must comply with when collecting, storing, and analyzing data, contributing to the overall costs of data management.

Activity Data

Digital traces generated from online or offline actions and behaviors, such as browsing history or GPS data.

Conversation Data

Data consisting of emails, chats, and social media posts, which is highly valuable for conducting sentiment analysis.

Photo/Video Data

Data used for customer behavior analysis, specifically through tools like in-store CCTV.

Sensor Data

Data generated by Internet of Things (IoT) devices, such as smart watches or smart TVs, used for real-time monitoring and predictive maintenance.

Internet of Things (IoT)

A network of devices like smart watches and smart TVs that generate sensor data.

Volume

One of the $5$ Vs of Big Data representing massive amounts of data.

Velocity

One of the $5$ Vs of Big Data representing high speed of data generation and processing.

Variety

One of the $5$ Vs of Big Data representing different formats and sources of data.

Veracity

One of the $5$ Vs of Big Data related to the trustworthiness and quality of the data.

Value

The most important of the $5$ Vs of Big Data, related to whether the data helps achieve business goals and results in a capital Return-on-Investment.

PMS

A hospitality-specific internal system used to gather data; stands for Property Management System.

POS

A hospitality-specific internal system used to gather data; stands for Point of Sale.

CRM

A hospitality-specific internal system used to gather data; stands for Customer Relationship Management.

Sentiment Analysis

The analysis conducted on conversation data, like emails and chats, to understand the sentiment behind the communication.