Queue Portrait: Hilary Mason

Queue Portraits

  • View Comments
  • Print

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

Related:

Pat Helland - Autonomous Computing
Autonomous computing is a pattern for business work using collaborations to connect fiefdoms and their emissaries. This pattern, based on paper forms, has been used for centuries. Here, we explain fiefdoms, collaborations, and emissaries. We examine how emissaries work outside the autonomous boundary and are convenient while remaining an outsider. And we examine how work across different fiefdoms can be initiated, run for long periods of time, and eventually be completed.


Archie L. Cobbs - Persistence Programming
A few years ago, my team was working on a commercial Java development project for Enhanced 911 (E911) emergency call centers. We were frustrated by trying to meet the data-storage requirements of this project using the traditional model of Java over an SQL database. After some reflection about the particular requirements (and nonrequirements) of the project, we took a deep breath and decided to create our own custom persistence layer from scratch.


Torsten Ullrich - Real-world String Comparison
In many languages a string comparison is a pitfall for beginners. With any Unicode string as input, a comparison often causes problems even for advanced users. The semantic equivalence of different characters in Unicode requires a normalization of the strings before comparing them. This article shows how to handle Unicode sequences correctly. The comparison of two strings for equality often raises questions concerning the difference between comparison by value, comparison of object references, strict equality, and loose equality. The most important aspect is semantic equivalence.


Ashish Gehani, Raza Ahmad, Hassan Irshad, Jianqiao Zhu, Jignesh Patel - Digging into Big Provenance (with SPADE)
Several interfaces exist for querying provenance. Many are not flexible in allowing users to select a database type of their choice. Some provide query functionality in a data model that is different from the graph-oriented one that is natural for provenance. Others have intuitive constructs for finding results but have limited support for efficiently chaining responses, as needed for faceted search. This article presents a user interface for querying provenance that addresses these concerns and is agnostic to the underlying database being used.


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.

Comments

(newest first)

Leave this field empty

Post a Comment: