Using Big Data Analytics to Optimize Practical Large Databases

<p>Big data analytics is gaining popularity for enterprises in optimizing their business processes ranging from retailers, supply chains, to online shopping stores. Existing practical raw data are far from usable to achieve the goal. Therefore, a good data pre-processing approach is required and is a key step to success. We propose to research on the effectiveness of data pre-processing and the business process based on a real world database. Our methodology involves natural language processing. Our key goal is to study appropriate methods with big data analysis techniques that can handle errors, ambiguity, and repeated descriptions caused by human languages. In this study, we did a simple language similarity checking to understand the database status. We also applied a logical representation system in our database to prove this concept.</p>

Name thesis:degree_name

Master of Science in Computer Science (MSCS)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Year dc:date.available

2021

Author dc:creator

• Lu, Po-Chun

Contributors dc:contributor

• Dr. Dan Lo
• Dr. Reza Meimandi Parizi

• Big Data
• Database
• Logical representation
• Computer Sciences
• Data Science

Repository record dc:identifier

https://digitalcommons.kennesaw.edu/cs_etd/48

OAI identifier oai:identifier

oai:digitalcommons.kennesaw.edu:cs_etd-1050