To produce high-quality information products and perform accurate spatial analysis, your source data must be of high quality and well maintained. ArcGIS Data Reviewer enables management of data in support of data production and analysis by providing a complete system for automating and simplifying data quality control that can improve data integrity.
Data Reviewer provides a comprehensive set of quality control (QC) capabilities that enable an efficient and consistent data review process. This includes workflows that support both automated and semiautomated analysis of data to detect errors. Errors detected during data review are stored to facilitate corrective workflows and data quality reporting.
Automated data review
Automated data review evaluates a feature's quality without human intervention. Data Reviewer includes a library of configurable checks that allow you to validate data based on your quality requirements. Data Reviewer checks are designed to assess various aspects of a feature’s quality, including its attribution, integrity, or spatial relationship to other features. Data Reviewer automated checks are configurable and do not require specialized programming skills to implement. In many cases, GIS professionals with a good understanding of their data’s quality requirements can implement automated review with minimal training.
Validation-enabled services allow clients to implement automated data review using attribute rules created with Data Reviewer checks. These services leverage ArcGIS Server to carry out automated review using an organization's on-premise or cloud-hosted infrastructure. In a production environment, automated review can be triggered on an as-needed basis to support ad hoc assessment of data quality as a component of a data management workflow.
To learn more about Data Reviewer automated workflows for assessing data review, refer to the following topics:
Data Reviewer allows management of errors from detection through correction and verification. These capabilities improve data quality by identifying the source, location, and cause of errors. Costs are reduced and duplicated work is avoided by providing insight into how the error was detected, who corrected it, and whether the correction has been verified as acceptable.
Errors detected during the data review process are tracked through a defined life cycle process. This process includes three phases: Review, Correction, and Verification.
Each phase contains one or more status values that describe the actions taken as the error progresses from one phase to another.
In attribute rule-based workflows, errors are stored in the geodatabase within a series of system-maintained tables. Errors are accessed using the Error Inspector pane, which provides tools for reporting, navigation, and selection of features that facilitate error correction.
To learn more about Data Reviewer error management workflows, refer to the following topics:
- Error results and their life cycle
- Configure the Error Inspector pane
- Tutorial: Evaluate features with attribute rules