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PyData NYC 2015
November 10th 2015
Karim Chine
karim.chine@rosettahub.com
Towards a universal platform
for
data science
on
public and private clouds
2
A universal open platform
for data science
Computational Components
R packages, Wrapped C,C++,Fortran code, Python modules, Matlab Toolkits…
Open source or commercial
Computational Resources
Clusters, grids, private or public clouds
Free or pay-per-use
Computational GUIs
HTML5 and Desktop Workbench
Built-in views /Plugins /Collaborative views
Open source or commercial
Computational Scripts
R / Python / Matlab / Groovy
Computational APIs
Java / SOAP / REST, Stateless and stateful
Computational Storage
Local, NFS, FTP, Amazon S3, EBS
Generated Computational Web Services
Stateful or stateless, mapping of R objects/functions
Elastic-
R
3
Infrastructures federation:
rosetta virtual cloud
Public
Clouds
Private Cloud
44
AWS: programmable
infrastructure
Command Line
Web Console
SDK
API
55
Command Line
Web Console
SDK
API
rosettaHUB: programming with
data and infrastructure
6
Google Docs-like real time
collaboration
7
Traceable and Reproducible
data science
Elastic-R
AMI 1
R 2.10 BioC
2.5
Elastic-R
AMI 2
R 2.9 BioC
2.3
Elastic-R
AMI 3
R 2.8
BioC 2.0
Elastic-R Amazon Machine Images
Elastic-R
EBS 1
Data Set
XXX
Elastic-R
EBS 2
Data Set
YYY
Elastic-R
EBS 3
Data Set
ZZZ
Elastic-R
EBS 4
Data Set VVV
Elastic-R
AMI 2
R 2.9
BioC 2.3
Elastic-R EBS
4
Data Set VVV
Amazon Elastic Block Stores
Eastic-R
AMI 2
R 2.9
BioC 2.3
Elastic-R.org
Elastic-R EBS
4
Data Set VVV
8
Architecture
9
Architecture
10
Data science universal engine
 Remote Java/R
Processes
 Events-driven Remote
Objects/Engines
 R, Python, Mathematica,
Matlab, Scilab, ...
 Collaborative Spreadsheets
 Collaborative Scientific
Graphics Canvas
 Collaborative Dashboard with
collaborative widgets
11
www.rosettahub.com

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Towards a Universal Platform for Data Science

  • 1. PyData NYC 2015 November 10th 2015 Karim Chine karim.chine@rosettahub.com Towards a universal platform for data science on public and private clouds
  • 2. 2 A universal open platform for data science Computational Components R packages, Wrapped C,C++,Fortran code, Python modules, Matlab Toolkits… Open source or commercial Computational Resources Clusters, grids, private or public clouds Free or pay-per-use Computational GUIs HTML5 and Desktop Workbench Built-in views /Plugins /Collaborative views Open source or commercial Computational Scripts R / Python / Matlab / Groovy Computational APIs Java / SOAP / REST, Stateless and stateful Computational Storage Local, NFS, FTP, Amazon S3, EBS Generated Computational Web Services Stateful or stateless, mapping of R objects/functions Elastic- R
  • 3. 3 Infrastructures federation: rosetta virtual cloud Public Clouds Private Cloud
  • 5. 55 Command Line Web Console SDK API rosettaHUB: programming with data and infrastructure
  • 6. 6 Google Docs-like real time collaboration
  • 7. 7 Traceable and Reproducible data science Elastic-R AMI 1 R 2.10 BioC 2.5 Elastic-R AMI 2 R 2.9 BioC 2.3 Elastic-R AMI 3 R 2.8 BioC 2.0 Elastic-R Amazon Machine Images Elastic-R EBS 1 Data Set XXX Elastic-R EBS 2 Data Set YYY Elastic-R EBS 3 Data Set ZZZ Elastic-R EBS 4 Data Set VVV Elastic-R AMI 2 R 2.9 BioC 2.3 Elastic-R EBS 4 Data Set VVV Amazon Elastic Block Stores Eastic-R AMI 2 R 2.9 BioC 2.3 Elastic-R.org Elastic-R EBS 4 Data Set VVV
  • 10. 10 Data science universal engine  Remote Java/R Processes  Events-driven Remote Objects/Engines  R, Python, Mathematica, Matlab, Scilab, ...  Collaborative Spreadsheets  Collaborative Scientific Graphics Canvas  Collaborative Dashboard with collaborative widgets