ArcGIS Data Reviewer Blog
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Directions Media Webinar: Getting the Data Right—Data QC for the ArcGIS Environment
Watch and learn how to use the tools in ArcGIS Data Reviewer to automate, centrally manage, and improve your GIS data quality control processes.Note: If you already registered for the webinar, enter your e-mail address to access the recording. If you did not already register, you will need to register first to access the video.
ArcGIS Data Reviewer saves time and organizational resources by allowing you to
Coordinate the Data Review Effort
- Efficiently manage the data review process by systematically tracking error results.
- Implement a standardized data validation process using configurable checks.
Simplify Data Quality Control Processes Using Automated Checks
Take advantage of more than 40 out-of-the-box automated validation checks.
- Author and distribute pre-configured checks to ensure consistency and repeatability of the data QC process.
- Expedite data validation by leveraging fine-grain control over the validation process.
Improve Visual Data Review
- Deploy easy-to-use tools for visually identifying missing, misplaced, or miscoded features.
- Optimize the visual review process by leveraging statistical sampling methods when it is impractical to review all features.
- Extend visual review and feedback capabilities across the organization and multiple platforms.
Manage and Report Data Quality Results
- Manage error results in a central location and easily share that information.
- Automatically capture statistics to gain insight into the source and causes of errors.
- Use tabular reports and web-based analytical dashboards to monitor data health and to identify error trends.
- Store and manage error results using scalable geodatabase technologies.
Schedule Automated Data Validation
- Schedule and automatically execute data validations on a daily, weekly, or monthly basis.
- Offload time-consuming data validations from desktop clients to intranet or cloud-hosted server infrastructure.
Simplify the quality control process by using out-of-the box checks or by creating your own.
Implement consistent, repeatable QC workflows by creating and sharing business rules throughout your organization.
Improve the visual data review process by using a systematic approach to navigate through your data.
Determine the health of your data by identifying, categorizing, and quantifying error results easily and accurately.