ArcGIS for Desktop Extensions

ArcGIS Data Reviewer

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Overview

Many organizations, especially those operating under constrained budgets, find it too costly and inefficient to implement a GIS data quality control (QC) program based on manual processes. This poses a real challenge in everyday situations that require accurate data. Poor quality data leads to costly mistakes in decision making that can be difficult to rectify.

ArcGIS Data Reviewer is Esri’s data quality management extension to ArcGIS for Desktop and ArcGIS for Server that automates and facilitates the otherwise resource-intensive process of data QC. Data Reviewer reduces the cost, time, and manpower required to complete QC tasks and can be used by individuals, teams, or throughout the enterprise.

With ArcGIS Data Reviewer, you can

  • Automate and simplify your QC process using out-of-the-box, user-configurable checks.
  • Implement a consistent, organization-wide data review process by sharing data quality business rules between teams or with contractors.
  • Free up resources by scheduling automated data validations to run at specified dates and times–enabling staff to work on other priority tasks.
  • Track and report the review, correction, and verification of your data by automatically capturing user information and a date/time stamp.
  • Streamline the error correction workflow across the organization by managing QC results from a centralized location.
  • Leverage industry-specific QC templates published on the ArcGIS Resource Center.
  • Create your own data validation methods by building checks specific to your organization using custom code or geoprocessing models/scripts.

ArcGIS Data Reviewer is also available as an extension to ArcGIS for Server.

See success stories from organizations like yours that are using ArcGIS Data Reviewer to improve their operations and make reliable business decisions.

ensure your data supports

Ensure your data supports current and future business requirements by implementing consistent, repeatable, and managed data quality control processes.


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