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<p class="MsoNormal"><span style="color:black">This is an announcement of Suhail Rehman's Candidacy Exam.<o:p></o:p></span></p>
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<span style="color:black">===============================================<o:p></o:p></span></p>
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<span style="color:black">Candidate: Suhail Rehman<o:p></o:p></span></p>
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<span style="color:black"> <o:p></o:p></span></p>
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<span style="color:black">Date: Wednesday, February 16, 2022<o:p></o:p></span></p>
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<span style="color:black"> <o:p></o:p></span></p>
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<span style="color:black">Time: 12:30 pm CST<o:p></o:p></span></p>
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<span style="color:black"> <o:p></o:p></span></p>
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<span style="color:black">Remote Location: <span class="apple-converted-space"> </span><a href="https://uchicago.zoom.us/j/95986092331?pwd=bjFrNzBwUzNBaTJLUXh5dWJkQnduQT09" title="https://uchicago.zoom.us/j/95986092331?pwd=bjFrNzBwUzNBaTJLUXh5dWJkQnduQT09">https://uchicago.zoom.us/j/95986092331?pwd=bjFrNzBwUzNBaTJLUXh5dWJkQnduQT09</a><span class="apple-converted-space"> </span>Meeting
ID: 959 8609 2331 Passcode: 517138<o:p></o:p></span></p>
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<span style="color:black"> <o:p></o:p></span></p>
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<span style="color:black">Title: Reconstructing the Lineage of Artifacts in Data Lakes<o:p></o:p></span></p>
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<span style="color:black"> <o:p></o:p></span></p>
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<span style="color:black">Abstract: As organizations' data storage, archival, and retrieval needs have evolved beyond simple<span class="apple-converted-space"> </span><o:p></o:p></span></p>
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<span style="color:black">relational databases to complex collaborative data lake architectures, a data stewardship<span class="apple-converted-space"> </span><o:p></o:p></span></p>
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<span style="color:black">and organization crisis has emerged. It is difficult to reason about existing data artifacts in<span class="apple-converted-space"> </span><o:p></o:p></span></p>
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<span style="color:black">data lakes without reliable lineage information and metadata. There is substantial interest in<o:p></o:p></span></p>
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<span style="color:black">automated tools and techniques inferring data artifacts' lineage within data lakes.<o:p></o:p></span></p>
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<span style="color:black"> <o:p></o:p></span></p>
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<span style="color:black">In this thesis, we the study of lineage in data lakes and specifically the possibility, accuracy,<o:p></o:p></span></p>
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<span style="color:black">and efficiency of retrospectively constructing the lineage of data artifacts within a data lake.<o:p></o:p></span></p>
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<span style="color:black">Specifically, we are proposing a method that retrospectively uses sketch and estimation<o:p></o:p></span></p>
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<span style="color:black">techniques, as well as similarity functions applied at various levels of granularity to (a) organize<o:p></o:p></span></p>
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<span style="color:black">data artifacts into the individual workflows that generated them, and (b) infer a lineage tree for<o:p></o:p></span></p>
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<span style="color:black">said artifacts that most closely resemble their ground truth derivations.<o:p></o:p></span></p>
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<span style="color:black"> <o:p></o:p></span></p>
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<span style="color:black">Advisors: Aaron Elmore<o:p></o:p></span></p>
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<span style="color:black"> <o:p></o:p></span></p>
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<span style="color:black">Committee Members: Aaron Elmore, Michael Franklin, and Raul Castro Fernandez<o:p></o:p></span></p>
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