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Version: 0.18.21

Glossary

Action: A Python class with a run method that takes a Validation Result and does something with it

Batch: A selection of records from a Data Asset.

Batch Request: Provided to a Data Source in order to create a Batch.

Checkpoint: The primary means for validating data in a production deployment of Great Expectations.

Checkpoint Store: A connector to store and retrieve information about means for validating data in a production deployment of Great Expectations.

Custom Expectation: An extension of the Expectation class, developed outside of the Great Expectations library.

Data Asset: A collection of records within a Data Source which is usually named based on the underlying data system and sliced to correspond to a desired specification.

Data Assistant: A utility that asks questions about your data, gathering information to describe what is observed, and then presents Metrics and proposes Expectations based on the answers.

Data Context: The primary entry point for a Great Expectations deployment, with configurations and methods for all supporting components.

Data Docs: Human readable documentation generated from Great Expectations metadata detailing Expectations, Validation Results, etc.

Data Docs Store: A connector to store and retrieve information pertaining to Human readable documentation generated from Great Expectations metadata detailing Expectations, Validation Results, etc.

Data Source: Provides a standard API for accessing and interacting with data from a wide variety of source systems.

Evaluation Parameter: A dynamic value used during Validation of an Expectation which is populated by evaluating simple expressions or by referencing previously generated metrics.

Evaluation Parameter Store: A connector to store and retrieve information about parameters used during Validation of an Expectation which reference simple expressions or previously generated metrics.

Execution Engine: A system capable of processing data to compute Metrics.

Expectation: A verifiable assertion about data.

Expectation Store: A connector to store and retrieve information about collections of verifiable assertions about data.

Expectation Suite: A collection of verifiable assertions about data.

Metric: A computed attribute of data such as the mean of a column.

MetricProviders: Generate and register Metrics to support Expectations, and they are an important part of the Expectation software development kit (SDK).

Metric Store: A connector to store and retrieve information about computed attributes of data, such as the mean of a column.

Plugin: Extends Great Expectations' components and/or functionality.

Renderer: A method for converting Expectations, Validation Results, etc. into Data Docs or other output such as email notifications or slack messages.

Store: A connector to store and retrieve information about metadata in Great Expectations.

Supporting Resource: A resource external to the Great Expectations code base which Great Expectations utilizes.

Validation: The act of applying an Expectation Suite to a Batch.

Validation Result: Generated when data is Validated against an Expectation or Expectation Suite.

Validation Result Store: A connector to store and retrieve information about objects generated when data is Validated against an Expectation Suite.

Validator: Used to run an Expectation Suite against data.