Workshop 3 – Data Analytics Takeaways

A set of vocabulary flashcards covering the core concepts of data types, the DIK pyramid, business uses for big data, and the evolution and types of data analytics.

Structured Data

Data that is highly organized and follows a consistent format, making it easily stored in tools like Excel spreadsheets. It is inexpensive to analyze but may offer limited insights. Examples include guest records and transactions.

Unstructured Data

Data that does not follow a predefined structure or format, making it difficult to store and analyze with traditional tools. It includes photos, videos, and social media posts, and often requires AI and machine learning for analysis.

Data (DIK Pyramid)

Raw facts or figures that represent reality. They are unprocessed and lack context or meaning on their own.

Information (DIK Pyramid)

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

Knowledge (DIK Pyramid)

Information that has been interpreted and validated through experience, insight, or analysis, typically answering why and how.

Explicit Knowledge

Knowledge that can be documented or codified; this is the primary focus of the DIK model.

Tacit Knowledge

Personal insights, intuition, or experiential understanding that resides in people’s minds, which the DIK model fails to adequately capture.

Operational Support

The use of data to enhance day-to-day operations, such as tracking online customer searches for inventory optimization or collecting sensor data for predictive maintenance.

Strategic Decision-making

High-level organizational decisions, such as mergers, acquisitions, or market entry, which require substantial financial and performance data analysis.

Tactical Decision-making

The use of data to support specific short-term initiatives, such as social media campaigns and promotional campaigns.

Web 3.0

The current wave of big data fueled by the Internet of Things (IoT), involving smart devices with embedded sensors.

Internet of Things (IoT)

A network of smart devices—including phones, TVs, watches, and refrigerators—that contain sensors to continuously generate data about physical activity and environmental conditions.

Descriptive Analytics

A type of analytics that summarizes and reports on a situation to answer "What happened?" using statistics such as mean, median, mode, and percentages.

Diagnostic Analytics

An analytical approach that investigates patterns and relationships to answer the question "Why did it happen?"

Predictive Analytics

The use of data and intuition to forecast future outcomes if no intervention is made, answering the question "What is likely to happen?"

Prescriptive Analytics

The stage of analytics that recommends specific actions or decisions based on insights from previous analysis, answering "What should we do about it?"