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KLOG PÅ SAS

VIYA UPDATE

[email protected]

TECHNICAL ACCOUNT MANAGER


executable anywhere data is (on-disk, in-

stream, in-database, in-memory, in-device)

SAS will analyze data of any size

in any form (table, stream, web service)

in any location (on-premises, cloud, hosted, hybrid)

from any source (private, public, partner)

by any language (SAS, Python, Java, REST-API)


Web

browser

Other

client

Smart

device

RDBMS Hadoop

RESTful APIsMicroservices In-Memory Engine

SAS Studio &

Python/Java/Lua

interfaces

SAS

Environment

Manager

Data Connectors / Accelerators

In-Database / embedded processes

VIYA PLATFORM

Cloud Analytic Services (CAS)

Work-

space

server


Visual

Analytics

Visual

Statistics

Visual Data

Mining and

Machine

Learning

Visual Data Mining and Machine Learning

Baseline

Procedures

VS

Procedures

VDMML

Procedures

Visual Analytics GUI

VS

Action sets

VDMML

Action setsBaseline

Action sets

Python API

SAS Studio UI

…..

…..

…..


April Summer Fall

SAS®

Visual Data Mining

and Machine Learning

SAS®

Visual Analytics

SAS®

Visual Statistics

SAS®

Visual Investigator

2017

SAS®

Studio

SAS®

Data Management

• Access

• Data Quality

• Data Prep

SAS®

Visual Scenario

Designer

SAS®

Analytics Suite

SAS®

Analytics as a

Service

etc….

Early Adopters SAS®

Visual Data Mining

and Machine Learning

SAS®

Visual Investigator

Early Adopters

SAS®

Visual Scenario

Designer

SAS® Viya™ announced

Early Preview

SAS®

9.4 M4

SAS®

Visual Analytics

SAS®

Visual Statistics

SUBJECT TO CHANGE


2016

2017

SUBJECT TO CHANGE

VDMML, VA, VS Visual Investigator

VDMML, VA, VS VDMML, VA, VS


SAS VIYA - SAS STUDIO

DEMO


SAS®

9

• SAS®

9 data accessible within SAS®

Viya™

• Remotely execute code from / to both

• SAS®

Viya™

models publishable to SAS®

9

Bridging SAS® 9 and SAS® Viya™

Data Code DataModel ModelModelCodeData


SAS 9.4

2016 2017 2018 …

SAS Viya


USECASE

Hvad kan VDMML bruges til – nu ?Innovation Lab

Machine Learning

Data Discovery / Explorering

Data Science

Advanced Analytics

SAS Viya

Big Data


SAS®Viya™ Programming

REST APIs

SAS® 9

Next-gen Solutions

Visual Statistics

Visual Analytics

Visual Investigator

Visual Data Mining


Open platform with a common code base that is…• Executable anywhere (in-Memory, in-Database, in-

Hadoop, in-Cloud, in-Stream, in-Device)

• Portable to any IT environment (desktop, server, grid,

cluster, or cloud)

• Accessible from third party applications

• Available in any public / private cloud

• Capable of management and inventory of all analytics

assets

• Infused with sophisticated and native search that does

not require pre-defined schemas in applications

Support for the Analytics Lifecycle• Data Management

• Visual Data Exploration

• Interactive Discovery

• Advanced Analytics

• Model Versioning & Inventory

• Decision Management

• Reporting

• Dashboards


SPØRGSMÅL?

[email protected]

TECHNICAL ACCOUNT MANAGER


Following are several examples of SAS 9.4 solutions that contain user interface features that you can use to issue SAS/CONNECT

statements to bridge the SAS 9.4 and SAS Viya environments:

SAS Enterprise MinerFrom your SAS Enterprise Miner process flow diagram running on SAS 9.4, you can remotely submit SAS Data Mining and Machine Learning

procedures to run in SAS Viya and then return the results to SAS 9.4 and integrate them into the SAS Enterprise Miner output.

SAS Model ManagerYou can run SAS Data Mining and Machine Learning procedures and train models in your SAS Viya environment, and then upload the models

and the models’ metadata to SAS 9.4. From SAS 9.4, you can remote submit code to register the SAS Viya created model and metadata in SAS

Model Manager. You can use SAS Model Manager to manage both your SAS 9.4 models and your SAS Viya models. For example, you can use

SAS Model Manager to deploy score code derived from both SAS 9.4 and SAS Viya models to a database.

SAS Data Integration StudioYou can use SAS Data Integration Studio on SAS 9.4 to perform tasks such as fetching data from multiple sources and preparing the data for

mining. Then, you can use the Data Transfer node to upload the data table to SAS Viya and load it directly into memory.

SAS Enterprise Guide / SAS Add-In for Microsoft OfficeYou can use the custom code nodes in either of these products to upload or download data between the two environments. For example, you

could remote submit code to SAS Viya for processing, and then return the computational results back to SAS Enterprise Guide on SAS 9.4.

SAS StudioYou can use the SAS Studio web interface to perform many programming actions in SAS Viya. For example, you could enter code in SAS Studio

to access data in your SAS Viya environment, remotely submit SAS Viya procedures to run on the data, and then transfer the results data

between the two environments.

SAS Stored ProcessesYou can save SAS/CONNECT SIGNON, RSUBMIT, UPLOAD, and DOWNLOAD statements as SAS Stored Processes,

and then use the SAS Stored Processes as another way to bridge your SAS 9.4 and SAS Viya environments.


SAS Viya Does Not Replace SAS 9

SAS 9 and SAS Viya are two unique platforms built for different use cases. However, these platforms share

some functionality. For example, SAS 9 uses the SAS programming language, and SAS Viya uses the next

generation of SAS programming with the new CAS programming language. The CAS language is very similar

to the SAS language. Some procedures are available on both platforms, so some existing SAS code can be

run on the SAS Viya platform. However, SAS Viya also contains new procedures that take advantage of the

open, distributed environment. As a result, some SAS 9 procedures do not exist in the new SAS Viya

environment.

• Because of the advancement in technology and infrastructure since SAS 9 was released, the technology

of SAS Viya is very different from SAS 9. Here are some examples: In SAS Viya, SAS Cloud Analytics

Services is the third-generation of in-memory services from SAS. It replaces SAS LASR Analytic Server

and the SAS High-Performance Analytics engine in SAS 9.

• For functionality other than CAS, there is no concept of roles or capabilities in SAS Viya. Access to

functionality is managed by rules that target a service, a service endpoint, a media type, or a pseudo URL.

• Instead of the metadata-based authorization, SAS Viya maintains authorization within the CAS engine and

by using host identities.

• In SAS Viya, images are a recognized data type.


SAS®

Viya™

…WITH SAS HIGH PERFORMANCE ANALYTICS

• SAS High Performance Data Mining

• SAS High Performance Statistics

• SAS High Performance Text Mining

• SAS Visual Data Mining and

Machine Learning

• SAS Visual Statistics

What it is In-memory analytic processing

algorithms/methods specifically designed for big

data, complex analysis and fast results from

built-in workflow.

In-memory analytic processing

algorithms/methods optimized for

parallel processing and initially

programmatically available. Designed

for big data, complex analysis, fast

results and open to be used from 3rd

party languages

Who it’s for Dir / VP IT, BI; LOB Dir / VP/ Lead; CAO, VP /

Dir Analytics; Data Scientist / Miner/ Statistician

Data Scientist / Miner / Statistician,

Analytic and Application Engineers


SAS®

Viya™

…WITH ENTERPRISE MINER

• SAS Enterprise Miner 14.1 • SAS Visual Data Mining and Machine Learning 8.1

What It Is • An integrated drag-and-drop process flow and programming

interface streamlining the end to end data mining and

machine learning process.

• SAS’ complete library of state-of-the-art statistics, data

mining, machine learning, and text mining capabilities. New

methods from VDMML accessible via the SAS 9.4 bridge.

• Enables automated batch processing and model retraining

• One, scalable in-memory processing environment.

Integration with SAS Grid Manager. Windows, Linux, AIX,

etc…

• Scorecode deployable via SAS, Java, C, in-database or via

web-services in SAME evironment

• Seamlessly integrates with SAS Model Manager 9.4 to

completely enable the analytics life cycle.

• Can call on open source models from within EM. Generates

PMML.

• Supports data mining and machine learning process via two independent

interactive and programming interfaces.

• Growing library of statistical, data mining, machine learning, and text mining

capabilities. Integrated optimization into methods using autotuning.

Basic deep learning capabilities.

• Library for reading in image files directly into SAS environment

• One, scalable in-memory processing environment. Failover, elastic, cloud-

friendly. Linux-only.

• Scorecode deployable via SAS, Java, C, in-database or via web-services

USING THE BRIDGE TO 9.4

• Integrates with SAS Model Manager 9.4 USING THE BRIDGE TO 9.4

• Can call actions through APIs for Java, Python, Lua and REST API

Who It’s ForData scientists, statisticians, data miners, engineers,

researchers and scientists

Data scientists, statisticians, data miners, engineers, researchers and scientists.

New and existing customers who are interested in leveraging the latest

machine learning algorithms and don’t mind the tradeoffs.

klog pÅ sas · sas data integration studio you can use sas data integration studio on sas 9.4 to...

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