sas is open (for business) · while allowing sas to extend open source applications with...
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SAS IS OPEN (FOR BUSINESS)
MATT MALCZEWSKI, SAS CANADA
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ACKNOWLEDGEMENTS
TAMARA DULL, SAS BEST PRACTICES
STEVE HOLDER, NATIONAL ANALYTICS LEAD, SAS CANADA
TINA SCHWEIHOFER, SENIOR SOLUTION SPECIALIST, SAS
CANADA
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5 OPEN SOURCE
MYTHS
the open source myth… …and the reality
It’s free. Licensing is free: that’s it.
It’s ‘Geekware’. At first… but not over time.
It’s ‘not ready’ for the Enterprise. 2010: 42%. 2015: 78%1
It’s hard to support. Strength of community!
It’s not secure. 55% believe it’s more secure.1
1Source: 2015 Future of Open Source Survey, North Bridge and Black Duck Software, April 2015
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COMPARISONS
• Open Source Offers:
+A robust online community.
+An extensive array of algorithms.
+Low cost barriers to entry.
+Fast adoption of new innovation.
• SAS Offers:
+Productivity for users regardless of skillset.
+Scalability to address any problem or dataset.
+Governed analytics and data.
+The support organizations require for
production and operational analytics.
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OPEN SOURCE
REVOLUTION….
… means the evolution of SAS to embrace and extend the capabilities of open
source as part of an analytics ecosystem.
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SAS EMBRACES
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INTEGRATION
POSSIBILITIES
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OPEN SOURCE IN
SAS
SAS® Enterprise Miner offers score code support for 6 different R packages
and allows users to import any type of R code. The open source node can
also be used to import any open source model.
Allows users to create ensemble models using open source and SAS.
Models can be converted to score code for operational deployment from within
a drag-and-drop interface. This results in improved productivity, deployment
and scalability.
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WHY IS THIS
IMPORTANT?
Improve model lift and performance by creating blended models that
combine the best of SAS and Open Source.
SAS automatically generates documentation capturing best practices,
promoting collaboration and helping reduce turnover risk.
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Facilitating InteroperabilityA simple example
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IN REAL LIFE
2 3 4
5
Leverage reusable data
preparation tasks.
Develop models using multiple
statistical methods.
Leverage advanced Machine
Learning.Integrate R Models.
Choose Champion and
Deploy.
1
What if you had to
CODE this in your
language of choice?
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SAS IN OPEN
SOURCE
+Base SAS offers a Java object to incorporate a variety of external languages,
including Python.
+This allows SAS Procedures to be be called from open source tools.
+The Jupyter kernel for SAS brings the power of SAS data manipulation and
analytics capabilities to the Jupyter notebook.
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WHY IS THIS
IMPORTANT?
This allows data scientists to code in their language and interface of choice,
while allowing SAS to extend open source applications with productivity and
the ability to scale to any data volume.
Using SAS in open source can ease the transition of non-SAS users: calling
SAS via stored processes/APIs from other programming interfaces is a simple
way for open source programmers to access SAS.
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Bringing SAS to R
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THE POWER OF
MODELS
• SAS supports analytic model deployment with inventory, scoring, monitoring
and retraining capabilities for SAS and Open Source models.
Supported
PMML Non-PMML
Inventory n n n n n
Publish &
Score
Batch n n n n n
In-Database n n n n n
Web Service n n n n n
Streaming n n n n n
Monitor n n n n n
Retrain n n n n n
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THE FUTURE IS NOW…
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SAS VIYA
22
SUPPORTING CURRENT INDUSTRY TRENDS
RESTful API’s
Multi-threaded hyper-computing
Memory spilloverScalable
Elastic
Easy installs
Charge-back capable
Advanced machine learning
Analytics lifecycle support
Integrated solutions
Micro-services
architecture
Plug n’ play
Python, Java, Lua support
Backward compatible ‘Any data, any platform’
End-to-end
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SAS AND OPEN SOURCE
EXTENDopen source by improving
its interoperability and
utility for the enterprise
EMBRACEopen source by including it
and leveraging it where we
can
SAS
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THANK YOU
TWITTER: MALCHEW
LINKEDIN: MATT MALCZEWSKI