2.3 Data Trends and Challenges

What is big data?

Extremely large, complex datasets characterized by high volume, velocity, and variety, requiring advanced tools to store and analyze.

What is data-driven decision making (DDDM)?

Using facts, metrics, and analysis to guide strategies and choices rather than relying only on intuition.

What is automation?

The use of AI-driven tools and processes to perform tasks such as data classification, cleaning, and indexing with minimal human intervention.

What is a data lake?

A centralized repository that stores raw structured and unstructured data in its native format.

What is a data silo?

A collection of data isolated within one system or department and not easily shared across the organization.

What is real-time analytics?

Continuously processing data as it is generated for immediate insights.

What is ethical data use?

Handling data in ways that are legal, responsible, and respectful of privacy and social values.

What is HIPAA?

A U.S. law that sets standards for protecting the privacy and security of health information.

What is PCI DSS?

A global security standard requiring organizations that handle card data to maintain secure systems.

What is an insider threat?

A risk from within an organization, such as an employee or partner who misuses authorized access to data.

What is sustainability in data management?

Reducing the environmental impact of data storage and processing through energy-efficient technologies and renewable resources.

What are examples of modern data trends?

Cloud platforms, AI, real-time tools, automation, and edge computing.

What are common challenges in data collection and management?

Privacy concerns, integration barriers, and compliance pressures.

What concerns can emerging data technologies create?

Questions about ethics, trust, and sustainability.