Historical College Scorecard Big Data Analysis using In-Memory Processing

1
Kunal Pritwani
Kunal Pritwani
2
Atinder Singh
Atinder Singh
3
Dharmesh Soni
Dharmesh Soni
4
Mounika Vallabhaneni and Jongwook Woo
Mounika Vallabhaneni and Jongwook Woo
1 California State University

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Data set is collected for colleges of United States. We would like to analyze different dimensions like SAT scores, ear-ning after graduation, net price and grant financial aids which is a great analyzation for the students. Big Data platform and BI tool such as Spark and tableau are adopted for data analy-zation and visualization. It is found that the top colleges for mean earnings are from medical field, mean earnings with respect to states, detailed comparison of average net price of California and New York, SAT scores for different colleges and also average undergraduates receiving Pell Grant in each colle-ges which will help students to select a college which meets their requirement.

11 Cites in Articles

References

  1. Kaggle (2016). Unknown Title.
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  3. Ran Liu,Kenneth Koedinger (2016). Going Beyond Better Data Prediction to Create Explanatory Models of Educational Data.
  4. Nathaniel Scharping (2016). Which Countries Are Paying the Highest Price for Particulate Air Pollution?.
  5. Atinder Singh (2016). CollegeScorecardAnalysis." Github -Atinder03.
  6. Kunal Pritwani (2016). College-Historical-Analysis.
  7. (2011). Special technical session on high performance computing for pattern recognition at the 1998 international conference on parallel and distributed processing techniques and applications (PDPTA'98), July 13–16, 1998, Las Vegas, Nevada, USA Call for Papers.
  8. Jongwook Woo (2013). Market Basket Analysis algorithms with <scp>MapReduce</scp>.
  9. (2016). Best Graduate Schools by Salary Potential.
  10. (2016). Announcements from APPAM.
  11. Michael Hurwitz,Jonathan Smith (2016). Student Responsiveness to Earnings Data in the College Scorecard.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Kunal Pritwani. 2017. \u201cHistorical College Scorecard Big Data Analysis using In-Memory Processing\u201d. Global Journal of Computer Science and Technology - H: Information & Technology GJCST-H Volume 17 (GJCST Volume 17 Issue H1): .

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GJCST Volume 17 Issue H1
Pg. 21- 28
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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March 13, 2017

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Data set is collected for colleges of United States. We would like to analyze different dimensions like SAT scores, ear-ning after graduation, net price and grant financial aids which is a great analyzation for the students. Big Data platform and BI tool such as Spark and tableau are adopted for data analy-zation and visualization. It is found that the top colleges for mean earnings are from medical field, mean earnings with respect to states, detailed comparison of average net price of California and New York, SAT scores for different colleges and also average undergraduates receiving Pell Grant in each colle-ges which will help students to select a college which meets their requirement.

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Historical College Scorecard Big Data Analysis using In-Memory Processing

Kunal Pritwani
Kunal Pritwani California State University
Atinder Singh
Atinder Singh
Dharmesh Soni
Dharmesh Soni
Mounika Vallabhaneni and Jongwook Woo
Mounika Vallabhaneni and Jongwook Woo

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