Queue Portrait: Hilary Mason

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Chief Data Scientist at Bitly, Hilary Mason, discusses the current state of data science. https://vimeo.com/74990264

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Pat Helland - Data on the Outside vs. Data on the Inside
This article describes the impact of services and trust on the treatment of data. It introduces the notions of inside data as distinct from outside data. After discussing the temporal implications of not sharing transactions across the boundaries of services, the article considers the need for immutability and stability in outside data. This leads to a depiction of outside data as a DAG of data items being independently generated by disparate services.


Kate Matsudaira - The Science of Managing Data Science
What are they doing all day? When I first took over as VP of Engineering at a startup doing data mining and machine learning research, this was what the other executives wanted to know. They knew the team was super smart, and they seemed like they were working really hard, but the executives had lots of questions about the work itself. How did they know that the work they were doing was the "right" work? Were there other projects they could be doing instead? And how could we get this research into the hands of our customers faster?


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Assessing the quality or validity of a piece of data is not usually done in isolation. You typically examine the context in which the data appears and try to determine its original sources or review the process through which it was created. This is not so straightforward when dealing with digital data, however: the result of a computation might have been derived from numerous sources and by applying complex successive transformations, possibly over long periods of time.


Zachary Hensley, Jibonananda Sanyal, Joshua New - Provenance in Sensor Data Management
In today’s information-driven workplaces, data is constantly being moved around and undergoing transformation. The typical business-as-usual approach is to use e-mail attachments, shared network locations, databases, and more recently, the cloud. More often than not, there are multiple versions of the data sitting in different locations, and users of this data are confounded by the lack of metadata describing its provenance or in other words, its lineage. The ProvDMS project at the Oak Ridge National Laboratory (ORNL) described in this article aims to solve this issue in the context of sensor data.


George Neville-Neil (aka Kode Vicious) sits down with Chief Data Scientist at Bitly, Hilary Mason, to discover more about what data science is, what the work of a data scientist entails, and how to build systems that make doing data science possible.

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