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You searched for subject:(big data). Showing records 1 – 30 of 1195 total matches.

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San Jose State University

1. Desai, Khushali Yashodhar. Big Data Quality Modeling And Validation.

Degree: MS, Computer Engineering, 2018, San Jose State University

  The chief purpose of this study is to characterize various big data quality models and to validate each with an example. As the volume… (more)

Subjects/Keywords: Big Data; Big Data Quality

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APA (6th Edition):

Desai, K. Y. (2018). Big Data Quality Modeling And Validation. (Masters Thesis). San Jose State University. Retrieved from https://scholarworks.sjsu.edu/etd_theses/4898

Chicago Manual of Style (16th Edition):

Desai, Khushali Yashodhar. “Big Data Quality Modeling And Validation.” 2018. Masters Thesis, San Jose State University. Accessed June 25, 2019. https://scholarworks.sjsu.edu/etd_theses/4898.

MLA Handbook (7th Edition):

Desai, Khushali Yashodhar. “Big Data Quality Modeling And Validation.” 2018. Web. 25 Jun 2019.

Vancouver:

Desai KY. Big Data Quality Modeling And Validation. [Internet] [Masters thesis]. San Jose State University; 2018. [cited 2019 Jun 25]. Available from: https://scholarworks.sjsu.edu/etd_theses/4898.

Council of Science Editors:

Desai KY. Big Data Quality Modeling And Validation. [Masters Thesis]. San Jose State University; 2018. Available from: https://scholarworks.sjsu.edu/etd_theses/4898


University of Georgia

2. Cheng, Xiao. The rise of the Big Data: why should statisticians embrace collaborations with computer scientists.

Degree: MS, Statistics, 2013, University of Georgia

Big Data has been the new trend in businesses. As technology advances, the ability to collect large amount of data and learn insights from them… (more)

Subjects/Keywords: Big Data

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APA (6th Edition):

Cheng, X. (2013). The rise of the Big Data: why should statisticians embrace collaborations with computer scientists. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/cheng_xiao_201312_ms

Chicago Manual of Style (16th Edition):

Cheng, Xiao. “The rise of the Big Data: why should statisticians embrace collaborations with computer scientists.” 2013. Masters Thesis, University of Georgia. Accessed June 25, 2019. http://purl.galileo.usg.edu/uga_etd/cheng_xiao_201312_ms.

MLA Handbook (7th Edition):

Cheng, Xiao. “The rise of the Big Data: why should statisticians embrace collaborations with computer scientists.” 2013. Web. 25 Jun 2019.

Vancouver:

Cheng X. The rise of the Big Data: why should statisticians embrace collaborations with computer scientists. [Internet] [Masters thesis]. University of Georgia; 2013. [cited 2019 Jun 25]. Available from: http://purl.galileo.usg.edu/uga_etd/cheng_xiao_201312_ms.

Council of Science Editors:

Cheng X. The rise of the Big Data: why should statisticians embrace collaborations with computer scientists. [Masters Thesis]. University of Georgia; 2013. Available from: http://purl.galileo.usg.edu/uga_etd/cheng_xiao_201312_ms


Wake Forest University

3. Bowling, Roy Nathaniel. Big Data and the Rhetorical Narrative.

Degree: 2014, Wake Forest University

 This project effectively illustrates a tactic by which the constructs of narrative inquiry from a humanist perspective, in particular the rhetorical narrative tradition, can migrate… (more)

Subjects/Keywords: Big Data

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APA (6th Edition):

Bowling, R. N. (2014). Big Data and the Rhetorical Narrative. (Thesis). Wake Forest University. Retrieved from http://hdl.handle.net/10339/47448

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Bowling, Roy Nathaniel. “Big Data and the Rhetorical Narrative.” 2014. Thesis, Wake Forest University. Accessed June 25, 2019. http://hdl.handle.net/10339/47448.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Bowling, Roy Nathaniel. “Big Data and the Rhetorical Narrative.” 2014. Web. 25 Jun 2019.

Vancouver:

Bowling RN. Big Data and the Rhetorical Narrative. [Internet] [Thesis]. Wake Forest University; 2014. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10339/47448.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bowling RN. Big Data and the Rhetorical Narrative. [Thesis]. Wake Forest University; 2014. Available from: http://hdl.handle.net/10339/47448

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

4. Zgraggen, Emanuel Albert Errol. Towards Accessible Data Analysis.

Degree: Department of Computer Science, 2018, Brown University

 In today's world data is ubiquitous. Increasingly large and complex datasets are gathered across many domains. Data analysis - making sense of all this data(more)

Subjects/Keywords: Big data

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APA (6th Edition):

Zgraggen, E. A. E. (2018). Towards Accessible Data Analysis. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:792684/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Zgraggen, Emanuel Albert Errol. “Towards Accessible Data Analysis.” 2018. Thesis, Brown University. Accessed June 25, 2019. https://repository.library.brown.edu/studio/item/bdr:792684/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Zgraggen, Emanuel Albert Errol. “Towards Accessible Data Analysis.” 2018. Web. 25 Jun 2019.

Vancouver:

Zgraggen EAE. Towards Accessible Data Analysis. [Internet] [Thesis]. Brown University; 2018. [cited 2019 Jun 25]. Available from: https://repository.library.brown.edu/studio/item/bdr:792684/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zgraggen EAE. Towards Accessible Data Analysis. [Thesis]. Brown University; 2018. Available from: https://repository.library.brown.edu/studio/item/bdr:792684/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of KwaZulu-Natal

5. Vela Vela, Junior. The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban.

Degree: 2017, University of KwaZulu-Natal

 The increase of number of data available in today’s world has prompted different industries to find a way to get the value out of the… (more)

Subjects/Keywords: Big data analysis.; Technology.; Big data.; Adoption.

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APA (6th Edition):

Vela Vela, J. (2017). The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban. (Thesis). University of KwaZulu-Natal. Retrieved from http://hdl.handle.net/10413/15171

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Vela Vela, Junior. “The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban.” 2017. Thesis, University of KwaZulu-Natal. Accessed June 25, 2019. http://hdl.handle.net/10413/15171.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Vela Vela, Junior. “The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban.” 2017. Web. 25 Jun 2019.

Vancouver:

Vela Vela J. The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban. [Internet] [Thesis]. University of KwaZulu-Natal; 2017. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10413/15171.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vela Vela J. The employees’ perception on the adoption of big data analytics by selected medical aid organisations in Durban. [Thesis]. University of KwaZulu-Natal; 2017. Available from: http://hdl.handle.net/10413/15171

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Universidade do Minho

6. Torres, Hugo Miguel Oliveira. Benchmarking de tecnologias de Big Data aplicadas à saúde-medicina .

Degree: 2017, Universidade do Minho

 Os avanços tecnológicos observados nas últimas décadas levaram a um aumento no volume e variedade dos dados gerados. Esses dados, quando armazenados, processados e analisados,… (more)

Subjects/Keywords: Big data; Big data technologies; Big data in healthcare; Benchmarking

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APA (6th Edition):

Torres, H. M. O. (2017). Benchmarking de tecnologias de Big Data aplicadas à saúde-medicina . (Masters Thesis). Universidade do Minho. Retrieved from http://hdl.handle.net/1822/54930

Chicago Manual of Style (16th Edition):

Torres, Hugo Miguel Oliveira. “Benchmarking de tecnologias de Big Data aplicadas à saúde-medicina .” 2017. Masters Thesis, Universidade do Minho. Accessed June 25, 2019. http://hdl.handle.net/1822/54930.

MLA Handbook (7th Edition):

Torres, Hugo Miguel Oliveira. “Benchmarking de tecnologias de Big Data aplicadas à saúde-medicina .” 2017. Web. 25 Jun 2019.

Vancouver:

Torres HMO. Benchmarking de tecnologias de Big Data aplicadas à saúde-medicina . [Internet] [Masters thesis]. Universidade do Minho; 2017. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/1822/54930.

Council of Science Editors:

Torres HMO. Benchmarking de tecnologias de Big Data aplicadas à saúde-medicina . [Masters Thesis]. Universidade do Minho; 2017. Available from: http://hdl.handle.net/1822/54930


Delft University of Technology

7. Verheij, B.A. The process of big data solution adoption:.

Degree: 2013, Delft University of Technology

 This research concerned the process of big data solution adoption and the main issues that firms experience in this process. Using eight cases within the… (more)

Subjects/Keywords: big data; big data solution; NoSQL; big data solution adoption

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APA (6th Edition):

Verheij, B. A. (2013). The process of big data solution adoption:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:369986f0-dd24-4855-aa85-8f69a3325191

Chicago Manual of Style (16th Edition):

Verheij, B A. “The process of big data solution adoption:.” 2013. Masters Thesis, Delft University of Technology. Accessed June 25, 2019. http://resolver.tudelft.nl/uuid:369986f0-dd24-4855-aa85-8f69a3325191.

MLA Handbook (7th Edition):

Verheij, B A. “The process of big data solution adoption:.” 2013. Web. 25 Jun 2019.

Vancouver:

Verheij BA. The process of big data solution adoption:. [Internet] [Masters thesis]. Delft University of Technology; 2013. [cited 2019 Jun 25]. Available from: http://resolver.tudelft.nl/uuid:369986f0-dd24-4855-aa85-8f69a3325191.

Council of Science Editors:

Verheij BA. The process of big data solution adoption:. [Masters Thesis]. Delft University of Technology; 2013. Available from: http://resolver.tudelft.nl/uuid:369986f0-dd24-4855-aa85-8f69a3325191


University of Hawaii – Manoa

8. Kang, Qiuling. Sentiment analysis of big social data with Apache Hadoop.

Degree: 2015, University of Hawaii – Manoa

M.S. University of Hawaii at Manoa 2014.

Twitter is a microblog service and is a very popular communication mechanism. Users of Twitter express their interests,… (more)

Subjects/Keywords: Twitter data sets; big data

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APA (6th Edition):

Kang, Q. (2015). Sentiment analysis of big social data with Apache Hadoop. (Thesis). University of Hawaii – Manoa. Retrieved from http://hdl.handle.net/10125/101227

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kang, Qiuling. “Sentiment analysis of big social data with Apache Hadoop.” 2015. Thesis, University of Hawaii – Manoa. Accessed June 25, 2019. http://hdl.handle.net/10125/101227.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kang, Qiuling. “Sentiment analysis of big social data with Apache Hadoop.” 2015. Web. 25 Jun 2019.

Vancouver:

Kang Q. Sentiment analysis of big social data with Apache Hadoop. [Internet] [Thesis]. University of Hawaii – Manoa; 2015. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10125/101227.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kang Q. Sentiment analysis of big social data with Apache Hadoop. [Thesis]. University of Hawaii – Manoa; 2015. Available from: http://hdl.handle.net/10125/101227

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Montana State University

9. Ganesan Pillai, Karthik. Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions.

Degree: College of Engineering, 2014, Montana State University

 Due to the current rates of data acquisition, the growth of data volumes in nearly all domains of our lives is reaching historic proportions [5],… (more)

Subjects/Keywords: Data mining.; Big data.

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APA (6th Edition):

Ganesan Pillai, K. (2014). Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions. (Thesis). Montana State University. Retrieved from https://scholarworks.montana.edu/xmlui/handle/1/9422

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ganesan Pillai, Karthik. “Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions.” 2014. Thesis, Montana State University. Accessed June 25, 2019. https://scholarworks.montana.edu/xmlui/handle/1/9422.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ganesan Pillai, Karthik. “Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions.” 2014. Web. 25 Jun 2019.

Vancouver:

Ganesan Pillai K. Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions. [Internet] [Thesis]. Montana State University; 2014. [cited 2019 Jun 25]. Available from: https://scholarworks.montana.edu/xmlui/handle/1/9422.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ganesan Pillai K. Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions. [Thesis]. Montana State University; 2014. Available from: https://scholarworks.montana.edu/xmlui/handle/1/9422

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Saskatchewan

10. Turland, Madeline G 1993-. Farmers’ willingness to participate in a big data sharing program: A study of Saskatchewan grain farmers.

Degree: 2018, University of Saskatchewan

Big data in crop agriculture is information collected by sophisticated machinery at the farm level, as well as externally generated data, such as field satellite… (more)

Subjects/Keywords: big data; data sharing

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APA (6th Edition):

Turland, M. G. 1. (2018). Farmers’ willingness to participate in a big data sharing program: A study of Saskatchewan grain farmers. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/11053

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Turland, Madeline G 1993-. “Farmers’ willingness to participate in a big data sharing program: A study of Saskatchewan grain farmers.” 2018. Thesis, University of Saskatchewan. Accessed June 25, 2019. http://hdl.handle.net/10388/11053.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Turland, Madeline G 1993-. “Farmers’ willingness to participate in a big data sharing program: A study of Saskatchewan grain farmers.” 2018. Web. 25 Jun 2019.

Vancouver:

Turland MG1. Farmers’ willingness to participate in a big data sharing program: A study of Saskatchewan grain farmers. [Internet] [Thesis]. University of Saskatchewan; 2018. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10388/11053.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Turland MG1. Farmers’ willingness to participate in a big data sharing program: A study of Saskatchewan grain farmers. [Thesis]. University of Saskatchewan; 2018. Available from: http://hdl.handle.net/10388/11053

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Tampere University

11. Syrjärinne, Paula. Urban Traffic Analysis with Bus Location Data .

Degree: 2016, Tampere University

 Tässä työssä esitellään Tampereen alueen julkisen liikenteen linja-autoista kerätyn datan käyttöä ja analysointia. Aineistoa on analysoitu useilla eri algoritmeilla ja monesta eri näkökulmasta. Osa analyyseista… (more)

Subjects/Keywords: data-analyysi; big data; älyliikenne; data analysis; big data; ITS

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APA (6th Edition):

Syrjärinne, P. (2016). Urban Traffic Analysis with Bus Location Data . (Doctoral Dissertation). Tampere University. Retrieved from http://tampub.uta.fi/handle/10024/98613

Chicago Manual of Style (16th Edition):

Syrjärinne, Paula. “Urban Traffic Analysis with Bus Location Data .” 2016. Doctoral Dissertation, Tampere University. Accessed June 25, 2019. http://tampub.uta.fi/handle/10024/98613.

MLA Handbook (7th Edition):

Syrjärinne, Paula. “Urban Traffic Analysis with Bus Location Data .” 2016. Web. 25 Jun 2019.

Vancouver:

Syrjärinne P. Urban Traffic Analysis with Bus Location Data . [Internet] [Doctoral dissertation]. Tampere University; 2016. [cited 2019 Jun 25]. Available from: http://tampub.uta.fi/handle/10024/98613.

Council of Science Editors:

Syrjärinne P. Urban Traffic Analysis with Bus Location Data . [Doctoral Dissertation]. Tampere University; 2016. Available from: http://tampub.uta.fi/handle/10024/98613


Indiana University

12. Suriarachchi, Isuru. Big provenance stream processing for data-intensive computations .

Degree: 2018, Indiana University

 Industry, academia, and research alike are grappling with the opportunities that Big Data brings in the ability to analyze data from numerous sources for insight,… (more)

Subjects/Keywords: Big Data; Big Provenance; Stream Processing

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APA (6th Edition):

Suriarachchi, I. (2018). Big provenance stream processing for data-intensive computations . (Thesis). Indiana University. Retrieved from http://hdl.handle.net/2022/22579

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Suriarachchi, Isuru. “Big provenance stream processing for data-intensive computations .” 2018. Thesis, Indiana University. Accessed June 25, 2019. http://hdl.handle.net/2022/22579.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Suriarachchi, Isuru. “Big provenance stream processing for data-intensive computations .” 2018. Web. 25 Jun 2019.

Vancouver:

Suriarachchi I. Big provenance stream processing for data-intensive computations . [Internet] [Thesis]. Indiana University; 2018. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/2022/22579.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Suriarachchi I. Big provenance stream processing for data-intensive computations . [Thesis]. Indiana University; 2018. Available from: http://hdl.handle.net/2022/22579

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Victoria

13. Chrimes, Dillon. Towards a big data analytics platform with Hadoop/MapReduce framework using simulated patient data of a hospital system.

Degree: School of Health Information Science, 2016, University of Victoria

 Background: Big data analytics (BDA) is important to reduce healthcare costs. However, there are many challenges. The study objective was high performance establishment of interactive… (more)

Subjects/Keywords: Big Data; Big Data Analytics; Big Data Tools; Big Data Visualizations; Hadoop Ecosystem; Health Big Data; Hospital Systems; Interactive Big Data; Patient Data; Simulations

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chrimes, D. (2016). Towards a big data analytics platform with Hadoop/MapReduce framework using simulated patient data of a hospital system. (Masters Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/7645

Chicago Manual of Style (16th Edition):

Chrimes, Dillon. “Towards a big data analytics platform with Hadoop/MapReduce framework using simulated patient data of a hospital system.” 2016. Masters Thesis, University of Victoria. Accessed June 25, 2019. http://hdl.handle.net/1828/7645.

MLA Handbook (7th Edition):

Chrimes, Dillon. “Towards a big data analytics platform with Hadoop/MapReduce framework using simulated patient data of a hospital system.” 2016. Web. 25 Jun 2019.

Vancouver:

Chrimes D. Towards a big data analytics platform with Hadoop/MapReduce framework using simulated patient data of a hospital system. [Internet] [Masters thesis]. University of Victoria; 2016. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/1828/7645.

Council of Science Editors:

Chrimes D. Towards a big data analytics platform with Hadoop/MapReduce framework using simulated patient data of a hospital system. [Masters Thesis]. University of Victoria; 2016. Available from: http://hdl.handle.net/1828/7645


Georgia Tech

14. Lee, Kisung. Scalable big data systems: Architectures and optimizations.

Degree: PhD, Computer Science, 2015, Georgia Tech

Big data analytics has become not just a popular buzzword but also a strategic direction in information technology for many enterprises and government organizations. Even… (more)

Subjects/Keywords: Big data; Graph data; Spatial data

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APA (6th Edition):

Lee, K. (2015). Scalable big data systems: Architectures and optimizations. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55520

Chicago Manual of Style (16th Edition):

Lee, Kisung. “Scalable big data systems: Architectures and optimizations.” 2015. Doctoral Dissertation, Georgia Tech. Accessed June 25, 2019. http://hdl.handle.net/1853/55520.

MLA Handbook (7th Edition):

Lee, Kisung. “Scalable big data systems: Architectures and optimizations.” 2015. Web. 25 Jun 2019.

Vancouver:

Lee K. Scalable big data systems: Architectures and optimizations. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/1853/55520.

Council of Science Editors:

Lee K. Scalable big data systems: Architectures and optimizations. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/55520

15. Cao, Xiang. Efficient Data Management and Processing in Big Data Applications.

Degree: PhD, Computer Science, 2017, University of Minnesota

 In today's Big Data applications, huge amount of data are being generated. With the rapid growth of data amount, data management and processing become essential.… (more)

Subjects/Keywords: Big Data; Data Management; Data Processing

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APA (6th Edition):

Cao, X. (2017). Efficient Data Management and Processing in Big Data Applications. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/188863

Chicago Manual of Style (16th Edition):

Cao, Xiang. “Efficient Data Management and Processing in Big Data Applications.” 2017. Doctoral Dissertation, University of Minnesota. Accessed June 25, 2019. http://hdl.handle.net/11299/188863.

MLA Handbook (7th Edition):

Cao, Xiang. “Efficient Data Management and Processing in Big Data Applications.” 2017. Web. 25 Jun 2019.

Vancouver:

Cao X. Efficient Data Management and Processing in Big Data Applications. [Internet] [Doctoral dissertation]. University of Minnesota; 2017. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/11299/188863.

Council of Science Editors:

Cao X. Efficient Data Management and Processing in Big Data Applications. [Doctoral Dissertation]. University of Minnesota; 2017. Available from: http://hdl.handle.net/11299/188863


University of California – Riverside

16. Jacobs, Steven. A BAD Thesis: The Vision, Creation, and Evaluation of a Big Active Data Platform.

Degree: Computer Science, 2018, University of California – Riverside

 Virtually all of today's Big Data systems are passive in nature, responding to queries posted by their users. Instead, this thesis aims to shift Big(more)

Subjects/Keywords: Computer science; Active Data; Big Active Data; Big Data

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APA (6th Edition):

Jacobs, S. (2018). A BAD Thesis: The Vision, Creation, and Evaluation of a Big Active Data Platform. (Thesis). University of California – Riverside. Retrieved from http://www.escholarship.org/uc/item/47g680h1

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Jacobs, Steven. “A BAD Thesis: The Vision, Creation, and Evaluation of a Big Active Data Platform.” 2018. Thesis, University of California – Riverside. Accessed June 25, 2019. http://www.escholarship.org/uc/item/47g680h1.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Jacobs, Steven. “A BAD Thesis: The Vision, Creation, and Evaluation of a Big Active Data Platform.” 2018. Web. 25 Jun 2019.

Vancouver:

Jacobs S. A BAD Thesis: The Vision, Creation, and Evaluation of a Big Active Data Platform. [Internet] [Thesis]. University of California – Riverside; 2018. [cited 2019 Jun 25]. Available from: http://www.escholarship.org/uc/item/47g680h1.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Jacobs S. A BAD Thesis: The Vision, Creation, and Evaluation of a Big Active Data Platform. [Thesis]. University of California – Riverside; 2018. Available from: http://www.escholarship.org/uc/item/47g680h1

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brunel University

17. Lakoju, Mike. A strategic approach of value identification for a big data project.

Degree: PhD, 2017, Brunel University

 The disruptive nature of innovations and technological advancements present potentially huge benefits, however, it is critical to take caution because they also come with challenges.… (more)

Subjects/Keywords: Big data strategy; Savi-bigd; Big data; Digital business strategy; Big data framework

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lakoju, M. (2017). A strategic approach of value identification for a big data project. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/15837 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764867

Chicago Manual of Style (16th Edition):

Lakoju, Mike. “A strategic approach of value identification for a big data project.” 2017. Doctoral Dissertation, Brunel University. Accessed June 25, 2019. http://bura.brunel.ac.uk/handle/2438/15837 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764867.

MLA Handbook (7th Edition):

Lakoju, Mike. “A strategic approach of value identification for a big data project.” 2017. Web. 25 Jun 2019.

Vancouver:

Lakoju M. A strategic approach of value identification for a big data project. [Internet] [Doctoral dissertation]. Brunel University; 2017. [cited 2019 Jun 25]. Available from: http://bura.brunel.ac.uk/handle/2438/15837 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764867.

Council of Science Editors:

Lakoju M. A strategic approach of value identification for a big data project. [Doctoral Dissertation]. Brunel University; 2017. Available from: http://bura.brunel.ac.uk/handle/2438/15837 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764867


University of Technology, Sydney

18. Zhang, X. Toward scalable and cost-effective privacy-preserving big data publishing in cloud computing.

Degree: 2014, University of Technology, Sydney

Big data and cloud computing are two disruptive trends nowadays, provisioning numerous opportunities to current IT industry and research communities while posing significant challenges on… (more)

Subjects/Keywords: Cloud computing.; Big data.; Privacy.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zhang, X. (2014). Toward scalable and cost-effective privacy-preserving big data publishing in cloud computing. (Thesis). University of Technology, Sydney. Retrieved from http://hdl.handle.net/10453/30324

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Zhang, X. “Toward scalable and cost-effective privacy-preserving big data publishing in cloud computing.” 2014. Thesis, University of Technology, Sydney. Accessed June 25, 2019. http://hdl.handle.net/10453/30324.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Zhang, X. “Toward scalable and cost-effective privacy-preserving big data publishing in cloud computing.” 2014. Web. 25 Jun 2019.

Vancouver:

Zhang X. Toward scalable and cost-effective privacy-preserving big data publishing in cloud computing. [Internet] [Thesis]. University of Technology, Sydney; 2014. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10453/30324.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Zhang X. Toward scalable and cost-effective privacy-preserving big data publishing in cloud computing. [Thesis]. University of Technology, Sydney; 2014. Available from: http://hdl.handle.net/10453/30324

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Halmstad University

19. Eriksson, Marcus. Utmaningar i upphandlingsprocessen av Big datasystem : En kvalitativ studie om vilka utmaningar organisationer upplever vid upphandlingar av Big data-system.

Degree: Information Technology, 2017, Halmstad University

Organisationer har idag tillgång till stora mängder data som inte kan hanteras av traditionella Business Intelligence‐verktyg. Big data karakteriseras av stor volym, snabb hastighet… (more)

Subjects/Keywords: Big Data; Big Data strategy; Procurement; Acquisition; Challenges; Big data; Big data-strategi; Upphandlingsprocess; Utmaningar; Information Systems; Systemvetenskap, informationssystem och informatik

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Eriksson, M. (2017). Utmaningar i upphandlingsprocessen av Big datasystem : En kvalitativ studie om vilka utmaningar organisationer upplever vid upphandlingar av Big data-system. (Thesis). Halmstad University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-35802

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Eriksson, Marcus. “Utmaningar i upphandlingsprocessen av Big datasystem : En kvalitativ studie om vilka utmaningar organisationer upplever vid upphandlingar av Big data-system.” 2017. Thesis, Halmstad University. Accessed June 25, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-35802.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Eriksson, Marcus. “Utmaningar i upphandlingsprocessen av Big datasystem : En kvalitativ studie om vilka utmaningar organisationer upplever vid upphandlingar av Big data-system.” 2017. Web. 25 Jun 2019.

Vancouver:

Eriksson M. Utmaningar i upphandlingsprocessen av Big datasystem : En kvalitativ studie om vilka utmaningar organisationer upplever vid upphandlingar av Big data-system. [Internet] [Thesis]. Halmstad University; 2017. [cited 2019 Jun 25]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-35802.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Eriksson M. Utmaningar i upphandlingsprocessen av Big datasystem : En kvalitativ studie om vilka utmaningar organisationer upplever vid upphandlingar av Big data-system. [Thesis]. Halmstad University; 2017. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-35802

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Queens University

20. Eftekhari, Azadeh. BINARY: A FRAMEWORK FOR BIG DATA INTEGRATION FOR AD-HOC QUERYING .

Degree: Computing, 2016, Queens University

 Traditional relational database systems are not practical for big data workloads that require scalable architectures for efficient data storage, manipulation, and analysis. Apache Hadoop, one… (more)

Subjects/Keywords: ad-hoc query; big data

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APA (6th Edition):

Eftekhari, A. (2016). BINARY: A FRAMEWORK FOR BIG DATA INTEGRATION FOR AD-HOC QUERYING . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/14234

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Eftekhari, Azadeh. “BINARY: A FRAMEWORK FOR BIG DATA INTEGRATION FOR AD-HOC QUERYING .” 2016. Thesis, Queens University. Accessed June 25, 2019. http://hdl.handle.net/1974/14234.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Eftekhari, Azadeh. “BINARY: A FRAMEWORK FOR BIG DATA INTEGRATION FOR AD-HOC QUERYING .” 2016. Web. 25 Jun 2019.

Vancouver:

Eftekhari A. BINARY: A FRAMEWORK FOR BIG DATA INTEGRATION FOR AD-HOC QUERYING . [Internet] [Thesis]. Queens University; 2016. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/1974/14234.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Eftekhari A. BINARY: A FRAMEWORK FOR BIG DATA INTEGRATION FOR AD-HOC QUERYING . [Thesis]. Queens University; 2016. Available from: http://hdl.handle.net/1974/14234

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Universiteit Utrecht

21. Franzke, A.S. Big Data Ethicist - What will the role of the ethicist be in advising governments in the field of big data?.

Degree: 2016, Universiteit Utrecht

 This paper elaborates on the question how the ethicist can address the demands for ethical expertise in governments occurring through big data practices. In the… (more)

Subjects/Keywords: big data; ethic; e-government

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APA (6th Edition):

Franzke, A. S. (2016). Big Data Ethicist - What will the role of the ethicist be in advising governments in the field of big data?. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/336098

Chicago Manual of Style (16th Edition):

Franzke, A S. “Big Data Ethicist - What will the role of the ethicist be in advising governments in the field of big data?.” 2016. Masters Thesis, Universiteit Utrecht. Accessed June 25, 2019. http://dspace.library.uu.nl:8080/handle/1874/336098.

MLA Handbook (7th Edition):

Franzke, A S. “Big Data Ethicist - What will the role of the ethicist be in advising governments in the field of big data?.” 2016. Web. 25 Jun 2019.

Vancouver:

Franzke AS. Big Data Ethicist - What will the role of the ethicist be in advising governments in the field of big data?. [Internet] [Masters thesis]. Universiteit Utrecht; 2016. [cited 2019 Jun 25]. Available from: http://dspace.library.uu.nl:8080/handle/1874/336098.

Council of Science Editors:

Franzke AS. Big Data Ethicist - What will the role of the ethicist be in advising governments in the field of big data?. [Masters Thesis]. Universiteit Utrecht; 2016. Available from: http://dspace.library.uu.nl:8080/handle/1874/336098


Hong Kong University of Science and Technology

22. Wang, Lu. Techniques and applications of random sampling on massive data.

Degree: 2015, Hong Kong University of Science and Technology

 Living in the era of big data, we often need to process and analyze data sets that have never been so large and fast-growing. Random… (more)

Subjects/Keywords: Big data; Sampling (Statistics)

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APA (6th Edition):

Wang, L. (2015). Techniques and applications of random sampling on massive data. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-b1514598 ; http://repository.ust.hk/ir/bitstream/1783.1-78835/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wang, Lu. “Techniques and applications of random sampling on massive data.” 2015. Thesis, Hong Kong University of Science and Technology. Accessed June 25, 2019. https://doi.org/10.14711/thesis-b1514598 ; http://repository.ust.hk/ir/bitstream/1783.1-78835/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wang, Lu. “Techniques and applications of random sampling on massive data.” 2015. Web. 25 Jun 2019.

Vancouver:

Wang L. Techniques and applications of random sampling on massive data. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2015. [cited 2019 Jun 25]. Available from: https://doi.org/10.14711/thesis-b1514598 ; http://repository.ust.hk/ir/bitstream/1783.1-78835/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wang L. Techniques and applications of random sampling on massive data. [Thesis]. Hong Kong University of Science and Technology; 2015. Available from: https://doi.org/10.14711/thesis-b1514598 ; http://repository.ust.hk/ir/bitstream/1783.1-78835/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

23. Loza Corera, María. De los microdatos a los datos masivos. Cuestiones legales.

Degree: 2018, TDX

 Internet ha supuesto una revolución en todas las áreas de nuestra vida, la manera que tenemos de trabajar, de comunicarnos y relacionarnos con los demás,… (more)

Subjects/Keywords: big data; protección de datos

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APA (6th Edition):

Loza Corera, M. (2018). De los microdatos a los datos masivos. Cuestiones legales. (Thesis). TDX. Retrieved from http://hdl.handle.net/10803/571763

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Loza Corera, María. “De los microdatos a los datos masivos. Cuestiones legales.” 2018. Thesis, TDX. Accessed June 25, 2019. http://hdl.handle.net/10803/571763.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Loza Corera, María. “De los microdatos a los datos masivos. Cuestiones legales.” 2018. Web. 25 Jun 2019.

Vancouver:

Loza Corera M. De los microdatos a los datos masivos. Cuestiones legales. [Internet] [Thesis]. TDX; 2018. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10803/571763.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Loza Corera M. De los microdatos a los datos masivos. Cuestiones legales. [Thesis]. TDX; 2018. Available from: http://hdl.handle.net/10803/571763

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Penn State University

24. Iyer, Karthik Thyagarajan. Computational complexity of data mining algorithms used in fraud detection.

Degree: MS, Industrial Engineering, 2015, Penn State University

 According to estimates by certain government agencies, 10% of the total medical expenditure is lost to healthcare fraud. Similarly the credit card industry loses billions… (more)

Subjects/Keywords: Data mining; Complexity; Big O

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Iyer, K. T. (2015). Computational complexity of data mining algorithms used in fraud detection. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/26437

Chicago Manual of Style (16th Edition):

Iyer, Karthik Thyagarajan. “Computational complexity of data mining algorithms used in fraud detection.” 2015. Masters Thesis, Penn State University. Accessed June 25, 2019. https://etda.libraries.psu.edu/catalog/26437.

MLA Handbook (7th Edition):

Iyer, Karthik Thyagarajan. “Computational complexity of data mining algorithms used in fraud detection.” 2015. Web. 25 Jun 2019.

Vancouver:

Iyer KT. Computational complexity of data mining algorithms used in fraud detection. [Internet] [Masters thesis]. Penn State University; 2015. [cited 2019 Jun 25]. Available from: https://etda.libraries.psu.edu/catalog/26437.

Council of Science Editors:

Iyer KT. Computational complexity of data mining algorithms used in fraud detection. [Masters Thesis]. Penn State University; 2015. Available from: https://etda.libraries.psu.edu/catalog/26437


Princeton University

25. Zhao, Tianqi. Statistical Inference for Big Data .

Degree: PhD, 2017, Princeton University

 This dissertation develops novel inferential methods and theory for assessing uncertainty of modern statistical procedures unique to big data analysis. In particular, we mainly focus… (more)

Subjects/Keywords: Big Data; Statistical Inference

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APA (6th Edition):

Zhao, T. (2017). Statistical Inference for Big Data . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp017d278w62w

Chicago Manual of Style (16th Edition):

Zhao, Tianqi. “Statistical Inference for Big Data .” 2017. Doctoral Dissertation, Princeton University. Accessed June 25, 2019. http://arks.princeton.edu/ark:/88435/dsp017d278w62w.

MLA Handbook (7th Edition):

Zhao, Tianqi. “Statistical Inference for Big Data .” 2017. Web. 25 Jun 2019.

Vancouver:

Zhao T. Statistical Inference for Big Data . [Internet] [Doctoral dissertation]. Princeton University; 2017. [cited 2019 Jun 25]. Available from: http://arks.princeton.edu/ark:/88435/dsp017d278w62w.

Council of Science Editors:

Zhao T. Statistical Inference for Big Data . [Doctoral Dissertation]. Princeton University; 2017. Available from: http://arks.princeton.edu/ark:/88435/dsp017d278w62w

26. Lindström, Frej. Impact analysis of characteristics in product development : Change in product property with respect to component generations.

Degree: Mathematics and Mathematical Statistics, 2017, Umeå University

  Scania has developed a unique modular product system which is an important successfactor, creating exibility and lies at the heart of their business model.… (more)

Subjects/Keywords: Statistics; big data; Mathematics; Matematik

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APA (6th Edition):

Lindström, F. (2017). Impact analysis of characteristics in product development : Change in product property with respect to component generations. (Thesis). Umeå University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-136911

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lindström, Frej. “Impact analysis of characteristics in product development : Change in product property with respect to component generations.” 2017. Thesis, Umeå University. Accessed June 25, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-136911.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lindström, Frej. “Impact analysis of characteristics in product development : Change in product property with respect to component generations.” 2017. Web. 25 Jun 2019.

Vancouver:

Lindström F. Impact analysis of characteristics in product development : Change in product property with respect to component generations. [Internet] [Thesis]. Umeå University; 2017. [cited 2019 Jun 25]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-136911.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lindström F. Impact analysis of characteristics in product development : Change in product property with respect to component generations. [Thesis]. Umeå University; 2017. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-136911

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Universitat de Valencia

27. Loza Corera, María. De los microdatos a los datos masivos. Cuestiones legales .

Degree: 2017, Universitat de Valencia

 Internet ha supuesto una revolución en todas las áreas de nuestra vida, la manera que tenemos de trabajar, de comunicarnos y relacionarnos con los demás,… (more)

Subjects/Keywords: big data; protección de datos

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Loza Corera, M. (2017). De los microdatos a los datos masivos. Cuestiones legales . (Doctoral Dissertation). Universitat de Valencia. Retrieved from http://hdl.handle.net/10550/61015

Chicago Manual of Style (16th Edition):

Loza Corera, María. “De los microdatos a los datos masivos. Cuestiones legales .” 2017. Doctoral Dissertation, Universitat de Valencia. Accessed June 25, 2019. http://hdl.handle.net/10550/61015.

MLA Handbook (7th Edition):

Loza Corera, María. “De los microdatos a los datos masivos. Cuestiones legales .” 2017. Web. 25 Jun 2019.

Vancouver:

Loza Corera M. De los microdatos a los datos masivos. Cuestiones legales . [Internet] [Doctoral dissertation]. Universitat de Valencia; 2017. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10550/61015.

Council of Science Editors:

Loza Corera M. De los microdatos a los datos masivos. Cuestiones legales . [Doctoral Dissertation]. Universitat de Valencia; 2017. Available from: http://hdl.handle.net/10550/61015

28. Mäntysaari, Piia-Pauliina. Big data : tieto lisää (muutakin kuin) tuskaa .

Degree: 2018, Theseus

Subjects/Keywords: big data

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mäntysaari, P. (2018). Big data : tieto lisää (muutakin kuin) tuskaa . (Thesis). Theseus. Retrieved from http://www.theseus.fi/handle/10024/159988

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mäntysaari, Piia-Pauliina. “Big data : tieto lisää (muutakin kuin) tuskaa .” 2018. Thesis, Theseus. Accessed June 25, 2019. http://www.theseus.fi/handle/10024/159988.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mäntysaari, Piia-Pauliina. “Big data : tieto lisää (muutakin kuin) tuskaa .” 2018. Web. 25 Jun 2019.

Vancouver:

Mäntysaari P. Big data : tieto lisää (muutakin kuin) tuskaa . [Internet] [Thesis]. Theseus; 2018. [cited 2019 Jun 25]. Available from: http://www.theseus.fi/handle/10024/159988.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mäntysaari P. Big data : tieto lisää (muutakin kuin) tuskaa . [Thesis]. Theseus; 2018. Available from: http://www.theseus.fi/handle/10024/159988

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Uppsala University

29. Lind, Simon. Distributed Ensemble Learning With Apache Spark.

Degree: Biology Education Centre, 2016, Uppsala University

Subjects/Keywords: Big Data

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lind, S. (2016). Distributed Ensemble Learning With Apache Spark. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-274323

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lind, Simon. “Distributed Ensemble Learning With Apache Spark.” 2016. Thesis, Uppsala University. Accessed June 25, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-274323.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lind, Simon. “Distributed Ensemble Learning With Apache Spark.” 2016. Web. 25 Jun 2019.

Vancouver:

Lind S. Distributed Ensemble Learning With Apache Spark. [Internet] [Thesis]. Uppsala University; 2016. [cited 2019 Jun 25]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-274323.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lind S. Distributed Ensemble Learning With Apache Spark. [Thesis]. Uppsala University; 2016. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-274323

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Oklahoma

30. Yetgin, Emre. Cognitive Fit in Visualizing Big Data.

Degree: PhD, 2015, University of Oklahoma

 This dissertation examines the consequences of cognitive fit in visualizing big data. Specifically, it focuses on the interplay between different types of business data analysis… (more)

Subjects/Keywords: Visualization; Cognitive Fit; Big Data

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APA (6th Edition):

Yetgin, E. (2015). Cognitive Fit in Visualizing Big Data. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/14568

Chicago Manual of Style (16th Edition):

Yetgin, Emre. “Cognitive Fit in Visualizing Big Data.” 2015. Doctoral Dissertation, University of Oklahoma. Accessed June 25, 2019. http://hdl.handle.net/11244/14568.

MLA Handbook (7th Edition):

Yetgin, Emre. “Cognitive Fit in Visualizing Big Data.” 2015. Web. 25 Jun 2019.

Vancouver:

Yetgin E. Cognitive Fit in Visualizing Big Data. [Internet] [Doctoral dissertation]. University of Oklahoma; 2015. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/11244/14568.

Council of Science Editors:

Yetgin E. Cognitive Fit in Visualizing Big Data. [Doctoral Dissertation]. University of Oklahoma; 2015. Available from: http://hdl.handle.net/11244/14568

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