Exploratory Data Analysis

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.

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.

Market Basket Analysis

A data mining technique discovering associations between items frequently purchased together.

The practice of collaboration between data science and operations to automate and manage the machine learning lifecycle.

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.

A technique for determining which input variables have the most significant impact on model predictions.

An automated set of processes that moves and transforms data from source systems to target destinations.

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

Using NLP techniques to extract insights and sentiment from unstructured text data at scale.

The framework of policies, processes, and standards for managing data assets to ensure quality, security, and compliance.