Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/409132
Title: Downtime Reduction Techniques for Data Migration from Structured Database to Unstructured Database
Researcher: Rathika, V
Guide(s): Arockiam, L
Keywords: Computer Science
Computer Science Information Systems
Engineering and Technology
University: Mother Teresa Womens University
Completed Date: 2022
Abstract: In the past few years, Big Data technologies have turned out to be important in several applications. Various industrial sectors like e-commerce, banking, hospital management and also educational institutions have implemented big data technologies to deduct valuable insights by performing big data analysis. Big data has placed its roots in the fields of big data integration, big data security, big data migration, etc. The existing traditional tools are not mature enough to handle the big data. The existing tools for big data manipulation gives results with very slow responsiveness. They also show lack of exactness, versatility and performance. Technological advancements generate more data which are in unstructured format. This poses critical challenges to the organizations in storing and processing the data. newline
Pagination: xix, 220p.
URI: http://hdl.handle.net/10603/409132
Appears in Departments:Department of Computer Science

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01_title.pdfAttached File105.96 kBAdobe PDFView/Open
02_declaration.pdf222.23 kBAdobe PDFView/Open
03_certificate.pdf340 kBAdobe PDFView/Open
04_acknoeledgement.pdf71.1 kBAdobe PDFView/Open
05_contents.pdf439.21 kBAdobe PDFView/Open
06_list of tables.pdf293.27 kBAdobe PDFView/Open
07_abstract.pdf11.38 kBAdobe PDFView/Open
08_chapter 1.pdf1.24 MBAdobe PDFView/Open
09_chapter 2.pdf547.59 kBAdobe PDFView/Open
10_chapter 3.pdf810.14 kBAdobe PDFView/Open
11_chapter 4.pdf1.07 MBAdobe PDFView/Open
12_chapter 5.pdf805.67 kBAdobe PDFView/Open
13_chapter 6.pdf1.04 MBAdobe PDFView/Open
14_conclusion.pdf473.52 kBAdobe PDFView/Open
15_bibliography.pdf265.47 kBAdobe PDFView/Open
16_appendices.pdf4.06 MBAdobe PDFView/Open
17_abbreviations.pdf366.63 kBAdobe PDFView/Open
80_recommendation.pdf564.48 kBAdobe PDFView/Open
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