1.
Study for Big data
analysis design model
Joonho Park
Soongsil University of Computer Science
DBCS(DAEBO Communication & systems)
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2.
Agenda
• Introduction
• Characteristics of Big data Analysis
• Research Framework
• Finding and Implication
• Conclusion
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3.
Introduction
• Through Big Data Analytics requires design
decisions.
• The implementation of the project through the CBD
and Agile methodologies.
• No model design phase that can make decisions.
• The big data analysis projects carried out through the
issue recently.
• Decision analysis model proposed by the issue.
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4.
Characteristics of Big data
Analysis
• The requirements of big data requirements
development project is different.
• If you are not clear on the requirements analysis
phase of the project is high possibility of delay.
• The number of data analysis, data types,
depending on the amount of data, other artifacts
is presented.
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5.
Research Framework
• Survey of big data project.
• Environmental analysis that matches the characteristics of each business.
• Big data business analysis that has been applied to each other business.
• Spatial big data project. 1, 2
• Analysis of the development methodology that has been introduced into the primary
industry.
• Problem presentation of each procedure.
• Financial project
• Lack of experience human resources, lack of specialized human resources.
• No specific requirements of the customer.
• No model designed caused by development methodology applied.
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6.
Finding and Implication
• Understanding the characteristics of each
industry through the design analysis model
required.
• For example, big data space also requires an
understanding of the spatial information.
• Data understanding of the banking business
and marketing needs to understand directions.
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7.
Conclusion
• Analysis services Model
• Collecting data on development methodology
and data design methodology proposed draft
• Service model proposed for the execution-
schedule
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8.
Thank You
park1058@ssu.ac.kr
park1058@dbcs.co.kr
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