Use our competitive advantage in order to achieve yours with Data3Sixty® DQ+, our enterprise data quality solution. As the data landscape evolves, data management is an organizational endeavor that is always changing. The one constant that will always remain is the undisputed need for accurate, consistent and reliable data. As the pioneer in data integrity, we’ve spent four decades validating information across complex data environments, monitoring and resolving data inaccuracies and leveraging machine learning and business-centric workflows to ensure you can depend on your data to drive success.
Data quality should be a part of your company’s data DNA. Expand beyond simple data quality checks to obtain a detailed view of your data throughout its journey. Ongoing quality monitoring and point-to-point reconciliation is fundamental to building user trust and delivering consistent insights.
Automating data quality checks across the entire data supply chain from the time information enters your organization throughout its whole journey.
Score the likelihood of possible inaccuracies based on historical data characteristics and issue reconciliations by leveraging machine learning algorithms.
Reconcile data from source to source in accordance with how your business operates to account for complex scenarios such as timeliness and reasonability.
Automatically catalog data quality rules and metadata to operationalize and provide transparency into data governance and quality program ROI gains.
There is only one formula for success. Data3Sixty enables all data consumers to know what data is available, what it means and if they can trust it before drawing insights. Teams can easily measure, communicate and collaborate on data across all business levels within the organization to ensure that clear and consistent results are shared. Anything less is a recipe for disaster.
Understand the context of your data by automatically tagging a data semantic type.
Significantly lower development time and redundancies by sharing and reusing data quality rules.
Teams can seamlessly collaborate on data quality metrics and visualizations with the ability to annotate on dashboards and capture point-in-time feedback.
Manage data quality exceptions through workflow tasks that can be routed and assigned to key stakeholders for remediation.
Use your data to generate the most value. Measure the impact of data by aligning it with business goals and outcomes. Insights practically uncover themselves when you have a quality-driven governance program in place.
Generate custom data quality scores aligned directly with your business goals and measure how data can be used to predict business results.
Gain personalized insights about your raw or curated data with customized dashboards that visually connect data to outcomes.
Access historical audit information to decrease review cycle time of compliance and policy audits.
Users gain deeper clarity into data of any size, from individual files to data lakes and streams at scale.
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