Design of Marketing Scenario Planning Based on Business Big Data Analysis
- Authors
- Hong, Seungkyun; Shin, Sungho; Kim, Young Min; Seon, Choong-Nyoung; Um, Jung ho; Song, Sa-kwang
- Issue Date
- Aug-2015
- Publisher
- Springer
- Keywords
- Big data; Business intelligence; Marketing scenario; Prescriptive analytics; Scenario optimization
- Citation
- Lecture Notes in Electrical Engineering, v.9191, pp.585 - 592
- Indexed
- SCOPUS
- Journal Title
- Lecture Notes in Electrical Engineering
- Volume
- 9191
- Start Page
- 585
- End Page
- 592
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/156548
- DOI
- 10.1007/978-3-319-20895-4_54
- ISSN
- 18761100
- Abstract
- As the amount and the type of data for business decision making are rapidly increasing, the importance of big data analytics is gradually critical for making effective business strategy. However, big data analytics based decision making systems basically requires distributed parallel computing capability in order to make timely business strategy recommendation via processing huge amount unstructured as well as structured business data. We introduce a big data analytics system for automatic marketing scenario planning based on big data platform software such as Hadoop and HBase. The analytics methodology for scenario planning is based on prescriptive analytics which is the most advance methodology consisting of generation of business scenarios and their optimization, among the three analytics of descriptive, predictive, and prescriptive analytics. Additionally, we developed a prototype of marketing scenario planning system and its graphical user interface, as well as the system architecture based on Hadoop eco-system based distributed parallel computing platform.
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