Real-Time 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.

Descriptive Analytics

The analysis of historical data to understand what has happened in the past and identify patterns.

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.

Statistical analysis measuring the strength and direction of the relationship between two or more variables.

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

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

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

The study of graphs representing relationships between discrete objects to understand network structure and dynamics.

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

Identifying data points that differ significantly from other observations in a dataset.

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