A set of processes that automate the movement and transformation of data from source to destination.

An open-source tool for orchestrating complex data workflows using Directed Acyclic Graphs (DAGs).

The process of automating tasks and processes to improve efficiency and reduce human intervention.

A structure representing tasks and their dependencies in Apache Airflow, ensuring tasks run in a specific order.

Combining data from different sources to provide a unified view for analysis.

The process of converting data from one format or structure into another, often for analysis.

A data processing framework that extracts data from sources, transforms it, and loads it into a target system.

The process of determining when tasks should run in a workflow, crucial for timely data processing.

Relationships between tasks in a workflow that dictate the order of execution.

The overall utility of a dataset, determined by accuracy, completeness, consistency, and reliability.

A virtual space provided by cloud services where applications and data can be hosted and managed.

The ability of a data pipeline to handle increasing amounts of data or complexity without performance loss.

Techniques for managing and responding to errors during workflow execution, ensuring reliability.

The practice of using data analysis and statistical methods to inform business decisions.

A set of protocols for building software applications, allowing different systems to communicate.

The storage of large volumes of data for analysis and reporting, optimized for query performance.

The management of data availability, usability, integrity, and security in an organization.

A system that records changes to files or projects over time, facilitating collaboration and tracking.

Practices that automate the integration and deployment of code changes, enhancing development efficiency.

The distribution of workloads across multiple resources to optimize resource use and minimize response time.

A storage repository that holds vast amounts of raw data in its native format until needed.

The immediate processing of data as it becomes available, crucial for time-sensitive applications.

An analysis of a specific instance or example, used to illustrate a concept or best practice.

Written descriptions and instructions that explain how a system or process works, crucial for maintenance and training.

The process of creating a preliminary model of a system to test concepts and gather feedback.