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EMERGING TECH TRENDS AND ANALYTICS

OLIVER SCHABENBERGER

EVP & CHIEF TECHNOLOGY OFFICER

@OSCHABENBERGER

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Open Source

Big Data

Data &

Analytics

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OUR R&D JOURNEY

SAS®

High-Performance

Analytics

2010

SAS®

LASR

Analytic Server

2011

SAS®

Cloud Analytic

Services

20132009

SAS®

High-Performance

Risk

2016

In-memory

high-end analytics

SMP & MPP

Multi-user, in-memory

analytics w/ Hadoop

SMP & MPP

MPP, in-memory

risk calculations

and querying

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Need to integrate technology

4

1Movement of data to cloud and edge

2Diversity in ways analytics are

consumed and approached

7Reduce technical debt

6Service-based architecture

5Extensibility, openness

3Simplicity in management,

deployment, monitoring, updates

FORCES THAT MOTIVATE SAS®

Viya™

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SAS®

Viya™

• Analytical Lifecycle

• Governance

• Integrated

• Enabling

• Languages

• APIs and Services

Consumption Based

Private and Public

Elastic

Deploy, Provision, Use

Self Service

Innovative

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SAS®

Viya™

…WITH SAS 9

&• It’s an AND strategy

• Each is designed to solve a different set of use cases

• Can co-exist on same hardware (physical or virtual)

• Incentives for existing customers

• Connective tissue bridges both platforms

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SAS®

9

DataCode

BRIDGING SAS®

9 AND SAS®

VIYA™

DataModel

Code

1

2

3

• SAS®

9 data accessible within SAS®

Viya™

• SAS®

Viya™

models publishable to SAS®

9

• Remotely execute code from / to both3

2

1

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2 SOFTWARE STREAMS: SAS®

9 AND SAS®

VIYA™

SAS Visual Data Mining and Machine

Learning 8.1

Data Management

SAS as an Open Platform

SAS Visual Investigator

Cyber Security

Event Stream Processing

Customer Intelligence 360

SAS 9.4M4

SAS Visual

Statistics

Event Stream Processing

SAS Visual

Analytics

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FROM SOFTWARE TO SMARTWARE

type & run click & browse

point and click touch and swipe

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MACHINE LEARNING PROCESSING

ARTIFICIALINTELLIGENCE

DEEP LEARNING

INFORMATIONCOMPUTATIONAL

PROGRAMMING

DATA

AUTOMATIC

DEEP

B R A I N

REALITY

DE

SIG

N

TE

CH

NO

LO

GY PERFORMANCE

ROBOTICS ALGORITHMS

CLASSIFICATION

ME

TH

OD

S

COMPUTATION

SCIENCE

QUALITYPROCESSING

INNOVATION

PY

TH

ON

PATTERN

MIN

ING

SOURCE PATTERN

RE

CO

GN

ITIO

N

MODELS

ANALYSIS

CLASSIFICATION

HIERARCHICAL

PREDICTIVETHEORYNEURAL

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MACHINE LEARNING

Data-driven

Non-algorithmic

Techniques

Learning based

on deep neural

networks

“Data does the

programming"

Data-driven

Algorithmic

techniques

Data trains

algorithm

Training is the

process of

shaping

Know ledge Augmenta t ion

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MACHINE LEARNING APPLICATIONS

1

Speech Recognition

3

Diagnostic of Mental Disorders

2

Natural Language Processing

4

Radiology Medical Imaging

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f o r w a r d

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@OSCHABENBERGER

LINKEDIN.COM/IN/OSCHABENBERGER

STAY IN TOUCH