Data & Analytical Methods

Big data refers to extremely large and complex datasets that are difficult to process using traditional data management techniques.

Biometrics refers to the automated recognition of individuals based on their unique biological and behavioral traits.

Approaches, techniques, and tools for collecting, processing, analyzing, and interpreting data to generate insights and inform decision-making.

Data governance is the establishment of policies and processes to ensure the quality, integrity, security, and usability of data within an organization or ecosystem.

Data interoperability is the ability of different information systems, devices, and applications to access, exchange, integrate, and cooperatively use data in a coordinated manner.

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.

Data-driven decision-making (DDDM) is the process of using data to inform and validate organizational decisions.

Geographic Information Systems (GIS) are frameworks for gathering, managing, and analyzing spatial or geographic data.

Information systems are integrated sets of components for collecting, storing, processing, and distributing information to support decision-making, coordination, control, analysis, and visualization in an organization.

Machine learning is a branch of artificial intelligence (AI) focused on enabling systems to learn from data without explicit programming.

Open data is data that is freely available to everyone to use and republish without restriction, promoting transparency, innovation, and collaboration.

Remote sensing is the process of detecting and measuring the physical characteristics of an area by measuring its reflected and emitted radiation at a distance.

Spatial analysis is the process of examining geographic data to identify patterns, relationships, and trends, enabling informed decision-making.