Data Observability

Data Pipeline

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

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.

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

An approach to analysing datasets to summarise their main characteristics, often using statistical graphics and visualisation.

A reusable, well-documented, and managed dataset or analytical asset created to serve specific business needs, treated with the same rigour as software products.

A visual interface displaying key metrics and data points for monitoring performance and making informed decisions.

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

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

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

A formal agreement between data producers and consumers that defines the structure, semantics, quality standards, and service levels of a shared data interface.

Monitoring

The continuous observation of system performance, availability, and health using automated tools and dashboards.