Data Pipeline

Data Quality

The measure of data's fitness for its intended purpose based on accuracy, completeness, consistency, and timeliness.

Data Lineage

The documentation of data's origins, movements, and transformations throughout its lifecycle.

Streaming Analytics

Processing and analysing continuous data streams in real time to detect patterns and trigger responses.

ETL Pipeline

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

Data Mart

A subset of a data warehouse focused on a particular business area, department, or subject.

Data Observability

The ability to understand, diagnose, and resolve data quality issues across the data stack by monitoring freshness, distribution, volume, schema, and lineage of data assets.

Reverse ETL

The process of moving transformed data from a central warehouse back into operational tools such as CRM, marketing platforms, and customer support systems to activate insights.

The process of labelling data with informative tags to make it usable for training supervised machine learning models.

Changes in the underlying patterns that a model was trained to capture, requiring model adaptation.

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

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

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

The use of machine learning and natural language processing to automate data preparation, insight discovery, and explanation, making analytics accessible to business users.

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

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