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Value-stream mapping has supporting methods that are often used in lean environments to analyze and design flows at the system level (across multiple processes).. Although value-stream mapping is often associated with manufacturing, it is also used in logistics, supply chain, service related industries, healthcare, [5] [6] software development, [7] [8] product development, [9] project ...
According to SAP, PI reduces the TCO by providing a common repository for interfaces. The central component of SAP PI is the SAP Integration Server, which facilitates interaction between diverse operating systems and applications across internal and external networked computer systems. PI is built upon the SAP Web Application Server.
SAP NetWeaver Master Data Management (SAP NW MDM) is a component of SAP's NetWeaver product group and is used as a platform to consolidate, cleanse and synchronise a single version of the truth for master data within a heterogeneous application landscape. It has the ability to distribute internally and externally to SAP and non-SAP applications.
For example, if the source system lists FirstName but the destination lists PersonGivenName, the mappings will still be made if these data elements are listed as synonyms in the metadata registry. Semantic mapping is only able to discover exact matches between columns of data and will not discover any transformation logic or exceptions between ...
Example of a more complex EPC diagram (in German). An event-driven process chain (EPC) is a type of flow chart for business process modeling. EPC can be used to configure enterprise resource planning execution, and for business process improvement. It can be used to control an autonomous workflow instance in work sharing.
SAP Business Technology Platform (SAP BTP) is a platform as a service developed by SAP SE that offers a suite of services including database and data management, AI, analytics, application development, automation and integration all running on one unified platform.
The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects.
The goal of the pattern is to keep the in-memory representation and the persistent data store independent of each other and the data mapper itself. This is useful when one needs to model and enforce strict business processes on the data in the domain layer that do not map neatly to the persistent data store. [2]