Descriptive Analytics

Predictive Analytics

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

Prescriptive Analytics

Advanced analytics that recommends specific actions to achieve desired outcomes based on predictive analysis.

Real-Time Analytics

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

Customer Analytics

The practice of collecting and analysing customer data to understand behaviour, preferences, and lifetime value.

Cohort Analysis

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

Funnel Analysis

Tracking and analysing the sequential steps users take toward a desired action to identify drop-off points.

Churn Analysis

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

Graph Analytics

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

A/B Testing

A controlled experiment methodology that compares two versions of a product, feature, or experience to determine which performs better against a defined metric.

An abstraction layer that provides business-friendly definitions and consistent metrics on top of raw data, enabling self-service analytics with standardised terminology.

Tools and platforms enabling non-technical users to access and analyse data independently.

The practice of building narratives around data insights using visualisations and narrative techniques.

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

A metadata management tool that helps organisations find, understand, and manage their data assets.

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

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

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