Data Profiling

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.

Artificially generated data that mimics the statistical properties of real-world data for training and testing.

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

The ability for users to ask questions about data in plain language and receive answers, with AI translating natural language into database queries and visualisations.

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

The process of analysing customer attrition to understand why customers stop using a product or service.

Artificially generated datasets that preserve the statistical properties of real data while protecting privacy, used for testing, development, and sharing across organisational boundaries.

Online Analytical Processing — a category of software tools enabling analysis of data stored in databases for business intelligence.

An automated workflow that extracts data from sources, transforms it according to business rules, and loads it into a target system.