Master Data Management (MDM) provides organizations with a reliable process for collecting, aggregating and distributing high-quality data throughout an enterprise. The process must ensure consistency and control for ongoing maintenance and use of such information. MDM solutions safeguard an organization against the use of multiple (potentially inconsistent) versions of critical data in different areas of its operations.
Master Data is information essential to the operation of a business and often includes data about customers, products, employees, vendors or materials. This type of information tends to be non-transactional and is frequently categorized into operational data and reference data. In contrast to operational data which tends to represent facts or system states, reference data typically defines characteristics or meta-data of a particular system. For example in finance a Securities Master data set contains the names of all securities that a firm or system deals with, as well as all possible versions of the names. Such relationships are some times referred to as semantic mappings.
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Master Data is typically used by multiple groups and stored in different data systems across an organization leading to duplicate and/or inaccurate information. Keeping master and reference data synchronized and up to date is the responsibility of master data management systems. The most common reasons why a business experiences serious MDM issues are unplanned expansion or growth through mergers and acquisitions. Addressing these challenges in today’s rapidly changing environment requires a fresh perspective on the problem. Data management solutions typically address data identification, normalization, collection, aggregation and transformation, as well as error detection and correction, data distribution and governance. |
Solutions for data management encompass people, processes, and the technology required to manage a consistent flow of data across the enterprise. It is a collaborative process that naturally fits within the Collaborative Computing paradigm. If enterprise data assets are considered product, then data management infrastructure is a tool for building an organization's data factory.
Data Caching and Distribution
The Service Application Engine™ offers several capabilities critical to an evolving data management infrastructure. The application fabric's Dataspace technology is an alternative data management system that allows developers to distribute and cache reference data essential to applications in real-time across the enterprise. Reference data may be accessed through a variety of client applications, API and protocols including JDBC and Restful HTTP requests.
The fabric may also be used as a flexible mechanism for real-time data distribution and data synchronization of master data. Using Integration Service Packs allows developers to bridge the so called "last mile" of integration allowing a data management system to connect to a variety of existing IT assets. Data may be sourced from such systems, transformed and easily distributed across the enterprise.
Semantic Mapping
The application fabric provides facilities for semantic mapping and data transformation, allowing developers to change data formats to comply with the requirements of source and target systems. The semantic mapper service supports high-performance transformation of XML documents without the need for cumbersome style sheet processor technologies. Data mapping facilities maintain a dictionary of semantic types used to map the data elements. The mapper includes Domain and Range lists useful in value look-up and decode functions, that may be dynamically loaded and synchronized across multiple mapper services.
Key Platform Features
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