Quest Data Quality
Reliable, trusted data demands clear data quality visibility and well-integrated, automated data quality tools to keep data quality high. Quest Data Quality helps governance teams and data consumers understand data quality and delivers the capabilities to improve it with automated data profiling and data quality scoring, consumer-friendly discovery, and cross-platform data observability.
02:45
AI demands reliable data and trusted models
See how integrated data quality and observability can support AI governance
Build data trust and ensure data is AI-ready
Quest Data Quality, part of Quest Data Intelligence and the Quest Trusted Data Management Platform, delivers integrated data quality visibility and the augmented data quality tools to fuel data and AI governance, build data trust, and keep critical data sources reliable. Based on the Gartner-recognized, augmented data quality platform from DQLabs, Quest Data Quality uses data catalog metadata to automate data profiling and quality assessment and then shares data quality scores widely for data consumers – within data lineage, impact analysis, semantic mind maps, and as one component of automated data trust scoring. Data observability, alert triage, and the platform’s self-learning capabilities combine with consumer-friendly discovery tools and quality issue management to help teams ensure high-quality data pipelines.
Choose intelligence-integrated data quality automation
Boost your data intelligence and take advantage of these capabilities below to ensure reliable data for AI use, improve data quality, reduce operational costs and risks, and extend data quality visibility across your enterprise.
Metadata-driven data quality assessment
Initiate the quality assessment of a data source at the environment, table, or column level from the data catalog metadata.
Automated data discovery and profiling
Use AI/ML-enabled discovery to detect data patterns and auto-create business rules for quality assessment. Auto-profile based on business rules and auto-generate data quality scores.
Data quality visibility for all
Data quality scoring is visible far beyond Quest Data Quality – alongside catalog metadata, in data lineage, impact analysis, semantic mind maps, and can be used as one component in automated trust scoring.
Cross-platform data observability
Continuously monitor critical data sources and AI data and be alerted when data quality drifts beyond acceptable thresholds. Self-learning capabilities evolve data quality measures based on your alert response.
Consumer-friendly data quality discovery
Explore data quality through discovery capabilities similar to online shopping
sites today. View assets, tables, views, attributes, reports and more filtering by data quality scores, alerts, domains, applications and other criteria.
Data behavioral analysis
Leverage behavioral analysis through data observability capabilities to track data trends over a previous time and forecast future data trends for business operational use.
Data remediation tools
Leverage data remediation tools such as reference or ML-based curation and parsing to intelligently clean and enrich bad data. Integrate with third-party cleansing and enrichment tools and generate coding scripts for use in ETL and data pipeline management solutions.
Data remediation collaboration
Triage issues arising from data observability alerts using built-in issue
management capabilities. Extend alert communication and issue collaboration beyond Quest with integration to email, Slack, Teams, JIRA and ServiceNow.
Data quality dashboards
Drill into detailed data quality status, profile assessments, correlations, and platform usage through customizable analytics dashboards.
Easy data source connectivity
Choose from an out-of-the-box library of data source connectors to industry
standard data sources including Amazon Redshift, Databricks, Google BigQuery,
Microsoft Azure Synapse, SQL Server, Oracle, Snowflake and more.
Quest Data Quality Tour
Quest delivers organizational visibility and automated data quality tools to build data trust and improve data quality. Take a look:
Data Quality Visibility
Raise visibility and understanding of data quality through quality dashboards
and intelligence-integrated data quality scoring. View data quality scores in
the data catalog, data lineage, mind maps, and impact analysis. Use scoring also as
one component within automated data trust scoring visible in Quest
Data Marketplace.
Data Profiling and Analysis
Leverage data catalog metadata to assess the quality of a new data source. Then use AI/ML-enabled auto-discovery to detect data patterns and automatically generate quality scoring.
Consumer-Friendly Data Quality Discovery
Explore data quality using familiar search and filter capabilities. View assets, tables, views, attributes, reports, and more filtering by data quality scores, alerts, domains, applications, etc. to zero-in on needed information.
Cross-Platform Data Observability
Keep data reliable with data observability that continuously monitors critical data sources and AI datasets. Out-of-the-box quality measures, auto-deployment during profiling, and no-code advanced anomaly detection unite to alert you if data drifts beyond acceptable thresholds. Self-learning platform capabilities evolve quality measures based on your alert response for efficient future monitoring.
Data Remediation
Leverage data remediation tools including reference or ML-based curation and
parsing rules to intelligently clean and enrich bad data. Integrate with
additional third-party cleansing and enrichment solutions as needed. Generate
coding scripts for use in ETL and other data pipeline management tools to speed
issue resolution.
Data Quality Collaboration
Raise data quality literacy through scoring, visualizations and dashboards.
Use conversational tools and built-in issue tracking to support collaborative efforts to improve data quality. Send alert notifications and
extend issue workflows through email, Microsoft Teams, Slack, JIRA and
ServiceNow. Keep stakeholders engaged and working together in data quality
initiatives.
Resources
Quest Data Quality
Wealth management firm simplifies audit preparation and gains data estate visibility
Since 1991, clients have put their trust in St. James’s Place, one of the largest advice-led wealth management firms in the UK....
Scaling AI and Business Value through Automated Data Products
Data teams are pressured to move faster with analytics and AI but most data delivery efforts remain slow, manual, and one‑off. ...
Govern Your Way to AI-Ready Data and Business Value
Data governance programs have long been driven, and funded, by the need to defend against regulatory risk and improve data qual...
TDWI: State of Data Quality
Discover how your organization's data quality management compares to industry peers. Download the TDWI report and learn how erw...
Dataversity Demo Day: Data Quality with Nadeem Siddique
In this on-demand webinar, you’ll learn how to ensure your data is trustworthy, reliable and AI-ready.
On-demand webinar: The State of Data Quality
Trustworthy data is foundational for business success, informing decision making, machine learning and AI. So, what is the curr...
Quest Data Intelligence
Make trusted data and AI models easy to find, understand, govern, score and use in your enterprise
Get started now
Learn how Quest integrated data quality automation can help you understand and boost the quality of your data. Deliver data you can trust.