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erwin Data Quality

Most enterprises don’t have the insight needed to understand data quality or the data quality automation and data quality tools needed to improve it. Poor data quality or lacking data quality visibility can result in your data becoming a costly challenge instead of a strategic advantage. erwin Data Intelligence automates data profiling, data quality assessment, ongoing data observability, and data remediation to ensure IT, data governance teams and business users alike have the visibility and collaborative abilities to make the most of the opportunity that data presents.
The health check dashboard in the erwin data quality platform

See erwin Data Quality in action online on May 24

Live Webinar – Building Data Trust Through Data Intelligence

Uniting data intelligence and data quality

erwin Data Intelligence delivers automated data quality capabilities and integrated data quality tools to support data governance, fuel data trust and promote data quality collaboration. Based on the DQLabs augmented data quality platform, recognized within the Gartner 2021 Hype Cycle for Data Management, erwin’s data quality offering leverages metadata stored within erwin Data Catalog to automate data profiling and streamline data quality assessment to deliver data quality scoring, correlation visuals, and other data quality measures. Add optional data observability for continuous drift monitoring and behavioral analysis, and data remediation capabilities to take data quality initiatives further.

Data quality automation with erwin Data Intelligence

Manage the entire data quality lifecycle with erwin Data Intelligence by Quest. Combine data intelligence, automation and an integrated, modern augmented data quality platform with accessible data quality tools to automate the data profiling, quality scoring, ongoing quality monitoring and data remediation of your most critical data sources. Improve data quality, reduce operational costs and risks, and extend data quality visibility across your enterprise to guide decision-making surrounding data use and to fuel data trust.

Metadata-driven data quality assessment

Initiate the quality assessment of a data source at the environment, table or column level from the metadata within erwin Data Catalog.

Automated data discovery and profiling

Use AI/ML-enabled discovery capabilities within the erwin data quality platform to detect data patterns and auto-create business rules for data quality assessment. Auto-profile based on business rules and auto-generate data quality scores.

Data quality visibility for all

Data quality scores appear in the erwin data quality platform as well as alongside data catalog metadata, in erwin Data Intelligence data asset searches, and within data lineage, impact analysis and mind map visualizations.

Ongoing data observability

With optional continuous drift monitoring, you can monitor 14 types of deviation across data, metadata and datasets associated with data-at-rest or streaming data. Gauge data volatility with a high-medium-low drift level indicator, set auto-alerts and use other data quality tools to understand and manage variations.

Data behavioral analysis

Leverage behavioral analysis within optional continuous drift monitoring capabilities to track data trends over a previous time and forecast future data trends for business operational use.

Data remediation analysis

Add on optional capabilities to use auto-profiling and other data quality tools to assess the need and potential for data remediation. An assigned impact score forecasts the percentage of bad data that can be remediated into good.

Data remediation tools

Use erwin data quality tools to tackle cleansing, deduplication, standardization and other data remediation using optional reference-based or ML-based curation and parsing capabilities, and through third-party tools.

Data remediation collaboration

Capture and collaborate on data quality issues within optional data remediation issue-tracking and conversation capabilities, and other data quality tools within the erwin data quality platform.

Data quality dashboards

Use the detailed data quality dashboard within the erwin data quality platform to drill into detailed data quality status, profile assessments, correlations and platform usage, and also view a data quality overview within the erwin Data Catalog dashboard.

Easy data source connectivity

Choose from an out-of-the-box library of data source connectors to industry standard data sources including Microsoft SQL Server, MySQL, Oracle, PostgreSQL, Salesforce, Snowflake and more.

erwin Data Quality Tour

erwin Data Intelligence delivers the organizational visibility and data quality tools and automation to understand and improve data quality. Take a look:
Data Quality Visibility
Data Profiling and Analysis
Data Observability
Data Remediation
Data Quality Collaboration
Augmented Data Catalog with All DQ Scores

Data Quality Visibility

Raise the visibility of source data quality through dedicated dashboards and the integration of data quality scoring within
erwin Data Intelligence.

The Value of Integrated Data Quality

High-quality data is critical for businesses when it comes to improving business outcomes, streamlining operational costs, and reducing overall risk. Businesses are looking for deepened integrated data quality and visibility capabilities so that IT, data governance teams and business users across the board are able to ensure appropriate data usage and build data trust.

Stewart Bond IDC Research Director for Data Integration and Data Intelligence Software

Get started now

Poor data quality is expensive, increases operational risks, and reduces data trust and use across the organization. Gain the visibility and data quality automation needed to tackle data quality head on today.

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