Information System Function-Data Architecture Planning Based on Subspace Partition

Yuwen Huo (), Xuedong Gao () and Ai Wang ()
Additional contact information
Yuwen Huo: University of Science and Technology Beijing
Xuedong Gao: University of Science and Technology Beijing
Ai Wang: University of Science and Technology Beijing

A chapter in LISS 2022, 2023, pp 75-88 from Springer

Abstract: Abstract Under the background of big data, the development of enterprise business and the growth of data lead to the characteristics of enterprise information system with complex business functions, large amount of data, and sparse connection between functions and data. Therefore, dividing the information system structure based on the link between functions and data can effectively improve the construction and operation efficiency of enterprise information systems and facilitate system maintenance and management. However, the traditional information system planning method only focuses on the planning of the functions, and cannot plan a reasonable data structure at the same time. In order to solve the above problems, this study proposes A Information System Function-Data Architecture Planning Method that can simultaneously complete the information system function-data system planning. It takes the Function-Data Subspace Partition Algorithm as the core, and realizes the information system structure partition from the perspective of function and data at the same time.

Keywords: system structure partition; Two-dimensional clustering; Subspace partition (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-99-2625-1_6

Ordering information: This item can be ordered from
http://www.springer.com/9789819926251

DOI: 10.1007/978-981-99-2625-1_6

Access Statistics for this chapter

More chapters in Lecture Notes in Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().