"The ability to transform data so that it can be shared seamlessly across information systems, applications and processes is often the biggest data integration hurdle for companies," said
Traditionally a manual process, data transformation poses multiple challenges for enterprises. In particular, the process of modeling data sources to targets to generate interfaces and create data mapping transformation rules can be both time consuming and error-prone. With Liaison Interface Intuition, companies can rapidly generate data mapping interfaces by analyzing and inferring layouts based upon the structure and content of sample data. Interface Intuition allows enterprises to quickly improve source to target matching with fewer errors, resulting in increased productivity and accuracy in interface generation. Companies can save hours to days worth of work depending on the data model. Interface Intuition is extremely useful when working with data types that do not have a self-describing definition, such as EDI, CSV, fixed-width files, JSON or XML that does not have a DTD or Schema. Additionally, the interactive, visual UI allows users to work directly with the data models, further reducing the time it takes to create interfaces.
Semantic Intuition enables enterprises to derive a starter vocabulary and data model based on actual information used in the company's data integrations. This process of creating canonical data models provides input that allows companies to create services more efficiently and easily, while also aligning the services with the enterprise data model. In turn, companies can perform impact analysis and govern their data integrations more effectively. Here, the intuitive, web-based UI helps enterprises define, maintain and review canonical models in a centralized repository.
Underlying the release of
Keywords for this news article include: Software, Machine Learning, Emerging Technologies, Information Technology, Artificial Intelligence, Information and Data Transformation.
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