Data Quality Engine
A unique / patented rules engine that encapsulates all the technical complexity and gives an intuitive wizard based approach to write and executes rules. The rules engine supports not just the classical master data rules like Data Completeness, Validity, Uniqueness, Timeliness but also data integrity, aggregate data validation
Patented cross-system validation capability
Compare data across multiple source systems simultaneously. Using this capability, you can compare integrity of data across multiple systems in real-time. It opens up significant more use-cases for data quality
Master Data Rules
Check uniqueness, Completeness, Validity of data. Apply complex filter conditions using an intuitive wizard. Create a composite ruleset to check completeness of a record across multiple columns. Create a business rules logic with multiple conditions just with a few clicks.
Aggregate Process Quality Rules
Define and rule rules for aggregated process validations. Check for count of total records, sum of key metrics in the data. Combined with data integrity rules, these rules can automate complete comparisons of data migrations from legacy to new applications
Data Reconciliation Rules
Match master or transactional documents across multiple systems field by field. For example, you can use it for 3-way match of purchase orders or use it for validation of data migration or data integration programs to compare source and target.
Supply Chain Network Completeness Rules
The biggest problem in running supply chain planning tools is the incompleteness of data, not from a master data record standpoint but from sourcing standpoint. You can write rules which can automate check across multiple tables in a database and identify cases where network is not completely defined.
Don’t just identify exceptions, Cleanse your Data
Cleansing Workbench allows you to change individual records, mass update records or create update rules. Apply them once and you can save them as macros to be applied automatically in future.
Not just cleanse, Write-back to Source Application
Close the loop of your data quality process by using the write-back feature of application. Apply the cleansing changes back to your source system. Do a direct write update to databases, excel files or integrate API calls to update applications like SAP and Oracle ERP. DvSum provides a SOX compliant write-back mechanism with controls to update data into a Production system.