Full Citation
Title: Analytics for Everyone
Citation Type: Dissertation/Thesis
Publication Year: 2018
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Abstract: Analyzing relational data typically involves tasks that facilitate gaining familiarity or insights and coming up with findings or conclusions based on the data. This process is usually practiced by data experts, such as data scientists, who share their output with a potentially less expert audience (everyone). Our goal is to enable everyone to participate in analyzing data rather than passively consuming its outputs (analytics democratization). With today’s increasing availability of data (data democratization) on the internet (web) combined with already widespread personal computing capabilities such a goal is becoming more attainable. With the recent increase of public data, i.e., Open Data, users without a technical background are keener than ever to analyze new data sets that are relevant to wide sectors of society. An important example of Open Data is the data released by governments all over the world, i.e., Open Government. This dissertation focuses on two main challenges that would face data exploration scenarios such as exploring open data found over the web. First, the infrastructure necessary for interactive data exploration is costly and hard to manage, especially by users who do not have technical knowledge. Second, the target users need guidance through the data exploration since there are too many starting points.
Url: https://uwspace.uwaterloo.ca/bitstream/handle/10012/13350/ELGEBALY_KAREEM.pdf?sequence=1
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Authors: El Gebaly, Kareem
Institution: University of Waterloo
Department: School of Computer Science
Advisor: Jimmy Lin
Degree: Doctor of Philosophy in Computer Science
Publisher Location: Waterloo, Ontario, Canada
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Data Collections: IPUMS USA
Topics: Methodology and Data Collection
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