Chris Beaumont - Data Analysis with SciDB-Py
940 views · Published 11 June 2014 · 51:38 · Indexed 25 October 2026
Channel: PyData · 2014 · People & Blogs
PyData SV 2014 While the Python ecosystem thrives at in-memory data analysis, what is missing is a high performance, seamless integration with a persistent data store. When dealing with larger datasets, data scientists are forced to think more carefully about low-level bookkeeping details -- this inhibits discovery. SciDB-Py addresses this problem by providing a high-level interface to SciDB -- a high performance database optimized for array-based computation at scale. 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
More from this channel
-
31:23
Kostas Perifanos - Authorship Attribution Using Python
-
31:08
Prash Majmudar - Measuring the Digital Economy Using Big Data
-
36:26
Ian Ozsvald - The High Performance Python Landscape
-
37:48
Mike Muller - Shared Memory Parallelism with Python
-
35:01
Martin Goodson - Most Winning A/B Test Results are Illusory
-
30:19
Mark Basham - Python for High Throughput Science
-
1:13:42
David Cournapeau & Simon Jagoe - Narrowing the Gap Between Array Computing and Databases
-
31:38
Emlyn Clay - Phython, Pharmaceuticals & Discovery