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Analytics as Code is a concept in data analytics where code is used in creating and managing analytics workflows and solutions. Analytics as Code allows developers to leverage software engineering principles in their analytics processes, such as version control, automated testing, CI/CD, and collaboration.[1]
Instead of using a mix of coding and point-and-click interfaces to create and manage dashboards, Analytics as Code allows users to develop and express analytics objects and functionalities through code.
Code used in the Analytics as Code includes Python, YAML, and JSON, which allows engineers to write the logic and instructions of the analytics they are creating.
Analytics as code treats all elements of analytics, (ie data connectors, ETL/ELT, logical data models, metrics, visualization, dashboards, user management) as objects that can be defined, manipulated, and customized through code. These analytics objects are serialized into a human-readable and editable textual format.[2]
References
edit- ^ "What Is Analytics as Code?". GoodData. August 3, 2023.
- ^ Hänninen, Lauri (April 2, 2023). "Analytics as Code: Managing Analytics Solutions Like Any Other Software".
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