Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/1746
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dc.contributor.authorNingning Wu
dc.contributor.authorM. Eduard Tudoreanu
dc.contributor.authorRichard Wang
dc.contributor.authorWenxue Jiang
dc.date.accessioned2020-03-16T18:01:01Z-
dc.date.available2020-03-16T18:01:01Z-
dc.date.issued2019-05-13
dc.identifier.citationPublished--Unlimited Distribution
dc.identifier.urihttps://dair.nps.edu/handle/123456789/1746-
dc.descriptionAcquisition Management / Defense Acquisition Community Contributor
dc.description.abstractThe Federal Funding Accountability and Transparency Act of 2006 (FFATA) required federal contract, grant, loan, and other financial assistance awards of more than $25,000 be displayed on a publicly accessible and searchable website to give the American public access to information on what the federal government spends every year and how it spends the money. Federal acquisition databases, such as those maintained by usaspending.gov and fpds.gov, serve this purpose. These databases contain contract information for all U.S. departments for the last 20 years. However, little has been done to dig into the data and extract the information that may provide valuable insights on potential ways to improve the efficiency of acquisition management. This paper takes a data science approach to assessing and enhancing the quality of the databases and to discovering patterns that can be potentially useful for acquisition research and practice.
dc.description.sponsorshipAcquisition Research Program
dc.languageEnglish (United States)
dc.publisherAcquisition Research Program
dc.relation.ispartofseriesAcquisition Management
dc.relation.ispartofseriesSYM-AM-19-057
dc.subjectData Enhancement
dc.subjectFinancial Assistance Awards
dc.subjectUsaspending.Gov
dc.subjectFpds.Gov
dc.subjectAcquisition Management
dc.titleData Enhancement and Analysis of Federal Acquisition Databases
dc.typeArticle
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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