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Better processes with high quality master data

Date:
October 1, 2015
Source:
Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO
Summary:
Where is the field of master data management currently headed? How can companies find the right products to meet their needs? In a recent market study, researchers compared the master data management systems of 14 providers, with a primary focus placed on the features of the various systems.
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Where is the field of master data management currently headed? How can companies find the right products to meet their needs? In a recent market study, Fraunhofer IAO compared the master data management systems of 14 providers, with a primary focus placed on the features of the various systems.

In the digital age, data is becoming available in ever greater volumes, and the complexity of this data is increasing as well. At the same time, the number of processes supported by IT systems within companies and other organizations is also on the rise. For this reason, it is becoming increasingly important for enterprises to systematically manage their master data. For several years now, established methods and tools for master data management and data quality management have been available on the market for this purpose, thus allowing small and medium-size companies with limited resources to successfully roll out their own implementations.

Viewing master data within the context of business processes

In order for companies to create practical, cost-effective implementations, they must not only choose the right IT solutions but also look at the master data within the context of business processes. This includes processes such as those where master data are used in the rendering of services. It is also important for companies to pay attention to processes that either create new master data or affect existing master data.

New study on master data management provides an overview of the market

In the recent study entitled "Multidomain Master Data Management Systems 2015," Fraunhofer IAO focuses chiefly on the features of modern master data management systems, classifying these with respect to IT developments and application options. The study is intended as a response to the growing market for, and increasing interest in, master data solutions. It features a market overview of current multidomain master data systems, with a user-friendly presentation of current systems and their features that makes it easier for potential users to compare available products. In addition to the market overview, the study also covers potential trends in the sector over the next several years with its survey of master data management system developers.

Initial findings of the study presented at SSF 2015

Fraunhofer IAO will present the study's initial findings at the Stuttgart Software Technology Forum from October 20-22, 2015 in Stuttgart. On the first day of the event, senior researchers at Fraunhofer IAO will provide an overview of several topics in seminars such as "Master Data Management and Information Quality," "Business Process Management," and "An Introduction to Document Management Systems." During the following two days, researchers and field experts will share their experiences on the topics of "Business Process Management," "Data Quality Management And Data Governance," as well as "Introduction to Master Data Management Systems."


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Materials provided by Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO. Note: Content may be edited for style and length.


Cite This Page:

Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO. "Better processes with high quality master data." ScienceDaily. ScienceDaily, 1 October 2015. <www.sciencedaily.com/releases/2015/10/151001095413.htm>.
Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO. (2015, October 1). Better processes with high quality master data. ScienceDaily. Retrieved April 24, 2024 from www.sciencedaily.com/releases/2015/10/151001095413.htm
Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO. "Better processes with high quality master data." ScienceDaily. www.sciencedaily.com/releases/2015/10/151001095413.htm (accessed April 24, 2024).

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