Integrating customer, supplier and operational data residing at different sources and in different formats, and providing users with a unified view of the data, poses a challenge for many companies.
Our easy to use Data Integration Software – DQ Studio™ enables users of all proficiencies to quickly link, match and deduplicate all database formats, regardless of size, to deliver a single view of the enterprise, making your data fit for its intended use.
DQ Studio™ for Data Integration
The latest edition to our suite of software is our DQ Studio™ Software. Based on the windows workflow DQ Studio™ provides solutions for Data Integration, Data Migration, Data Cleansing and other Business Automation processes. DQ Studio™ is designed to speed up and reduce the risk for any data integration, data migration or data quality project.
DQ Studio™ Editions
- Express – Our runtime edition, allows any workflow orchestration created using our Professional or Enterprise editions to be executed on any cloud or on premise environment.
- Professional - Our single user edition which allows users to create and run almost 800 preconfigured activities in nearly 40 Modules.
- Enterprise – Professional edition plus, a collaborative environment which supports multiple developers working on the same project database.
Features of DQ Studio™
- Connect to 16 different data source types
- Connect directly to system applications using their API’s
- Employs over 792 workflow activities packaged in 25 modules
- Includes functionality to run or schedule workflows
- Stores workflows in the Compact Edition database repository
- Includes functionality to deploy workflows on stand-alone machines
Complications arise when attempting to merge data from legacy systems into a new system. It is not realistic to assume that any two systems that maintain the same sort of data will easily map to each other. Legacy systems may suffer from a lack of clear definition of data requirements, field values, naming conventions, etc. and merging data with different formats and structures can be a hazard-prone process and the cause of delays and increased costs.
All too often, customer data integration highlights data quality problems that require a comprehensive solution to deal with inconsistent, incomplete or inaccurate data, lack of conformity, lack of integrity and duplicate records.
Using a proven data profiling and integration solution to merge information from disparate sources will ensure a successful customer data integration project with minimal delays and costs.
Like Master Data Management (MDM) and Single Customer View (SCV), Customer Data Integration projects are only a success when the data used to integrate systems are made consistent, are correctly formatted and duplicate free. Associating customer data across disparate business systems requires experience and sophisticated matching capabilities if records are to be associated correctly and false positives avoided.