Data Annotation

Data Science

An interdisciplinary field using scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data.

Big Data

Extremely large and complex datasets that require advanced computational tools and techniques to store, process, and analyse.

Data Engineering

The practice of designing, building, and maintaining data infrastructure, pipelines, and architectures.

Exploratory Data Analysis

An approach to analysing datasets to summarise their main characteristics, often using statistical graphics and visualisation.

Statistical Modelling

The process of applying statistical analysis to a dataset, identifying relationships and patterns within the data.

Diagnostic Analytics

Analysis techniques focused on understanding why something happened by examining data patterns and correlations.

Time Series Analysis

Statistical techniques for analysing time-ordered data points to identify trends, cycles, and forecasting patterns.

Regression Analysis

A set of statistical processes for estimating the relationships between dependent and independent variables.

Hypothesis Testing

A statistical method for making decisions about population parameters based on sample data evidence.

Bayesian Statistics

A statistical approach that incorporates prior knowledge and updates probability estimates as new data is observed.

Monte Carlo Simulation

A computational technique using repeated random sampling to obtain numerical results for problems with many coupled variables.

Business Analytics

The practice of iterative exploration of organisational data to drive business planning and decision-making.

Analysing relationships and connections between entities represented as nodes and edges in a graph structure.

An isolated repository of data controlled by one department, inaccessible to other parts of the organisation.

Statistical and machine learning methods for predicting future values based on historical sequential data, applied to demand planning, financial forecasting, and resource allocation.

Using historical data, statistical algorithms, and machine learning to forecast future outcomes and trends.

A behavioural analytics technique that groups users with shared characteristics to track metrics over time.

The discipline of analysing data as soon as it becomes available to support immediate decision-making.

The analysis of geographic and spatial data to discover patterns, relationships, and trends tied to location.

A formal agreement between data producers and consumers that defines the structure, semantics, quality standards, and service levels of a shared data interface.

Machine Learning

A subset of AI that enables systems to automatically learn and improve from experience without being explicitly programmed.