sas viya. Примеры проектов на новой платформе · introduce defect...

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SAS Viya. Примеры проектов на новой платформе


SAS 9.4 high-level architecture

SAS Grid Compute Nodes Middle Tier Client Tier

Server TierData Tier

Variuos Data Sources

SAS Web clients

SASDesktop clients

(Java, .NET)

SASMetadata Cluster

Clustered SAS WebApplication Servers

(Applications and Services)

SAS High-PerformanceAnalytics

Analytical Data Warehouse

SAS LASR Analytics

Data Warehouse

Metadata Tier

SASMobile clients

PostgreSQL SAS Web Infrastructure

Platform Data Server

SAS Embedded Process

SAS Event Stream ProcessingSAS Micro Analytic Server

Streaming data


Par

alle

l & S

eria

l, P

ub

/ S

ub

, W

eb S

ervi

ces,

MQ

s

Source-basedEngines

Microservices

UAA

QueryGen

Folders

CAS Mgmt

Data Source Mgmt

AnalyticsGUIs

etc…

BIGUIs

EnvMgr

ModelMgmt

Log

Audit

UAAUAA

Data Mgmt GUIs

In-Memory Runtime Engine

In-Database

In-Hadoop

In-StreamSolutions

APIs

Platform

Analytics

Data ManagementFraud and Security Intelligence

Business VisualizationRisk Management

!

Customer Intelligence

Cloud Analytics Services (CAS)


SAS Viya 3.4


SAS Viya products and UIs

Customer-written code

Customer-written code

SAS 9.4 M5 products and UIs

SAS 9.4 M5

LASR and / or HPA runtimes

Metadata (WIP)-based mid-tier

MVA runtime

(full functionality)

Other runtimes

(ESP, In-Database)

SAS Viya

CAS runtime

Today’s architecture

SAS/ConnectServer

Microservices-based mid-tier

Viya MVA runtime(minimal

functionality)

SAS 9 “bridge” to SAS Viya

SAS Viya “bridge” to SAS 9

Copyr i g ht © 2014, SAS Ins t i tu t e Inc . A l l r ights reser ve d .

PURE SAS VIYA

USE CASECHINA SEMICONDUCTOR MANUFACTURING COMPANY

Use Case #1 – Quality Control

Process Efficiency

• Efficient in-memory processing

• Reduce time to run weekly QC

checks

• Utilize SAS Visual Analytics to

review results

Use Case #2 – Image Processing

and Deep Learning

• Read in images of wafers

• Apply new SAS Viya CNN

algorithms to identify flaws in wafers

Use Case #3 – Open Source

Interface

Use Python as an interface

Introduce defect image type

Classification which types

➢ Purpose : Detect on the wafer with spatial patterns is usually a cube for the identification of equipment problems or process variations.

Usually, defect image classification capability for different defect types need over 90%accuracy. The challenge is redetection of small size

defect, number of classified defect type. Do defect types classification is key objectives on defect image application. In common, having

around 10-15 different types and how to defect “unknow” using learning process will be other key objectives.

Copyr i g ht © 2016, SAS Ins t i tu t e Inc . A l l r ights reser ve d .

Pa

ralle

l, W

eb S

erv

ices,

MQ

s

Source-basedEngines

Microservices

UAA

Query

Gen

Folders

CAS

Mgmt

Data

Source

Mgmt

Analytics

GUIs

etc.…

BI

GUIs

Env

Mgr

Model

Mgmt

Log

Audit

UAAUAA

Data

Mgmt

GUIs

In-Memory Engine

In-Hadoop

Solutions

APIs

Infrastructure

Platform

PURE SAS VIYA

USE CASESAS

®

Viya™

ARCHITECTURE

Analytics

Data Management

Business Visualization

Cloud Analytics Services (CAS)

In-Database

KEY BENEFITS

1) Access to Hadoop

2) Fast In-Memory data processing

3) Application of Deep Learning (CNN) algorithms

4) Use Python as the primary interface


SAS Germany‘s first opportunity for Viya

• Germany‘s largest retail company

• About 25% market share in Germany

• 11.500 stores and supermarkets

• ~ 350 000 employees

• ~ 50 billion euro sales volume in 2016

• Long-term SAS customer

• SAS DI Server, Enterprise Miner, Data Loader, STAT/ETS/IML

• Introduced Hadoop to their landscape 2 years ago

- SAS Germany‘s first customer on MapR

Customer Profile


SAS Viya

• Business unit (Database Marketing) got interested in Viya at the end of 2016

• Data scientists mainly use programming clients (SAS Display Manager, EG)

• Little use of SAS Enterprise Miner GUI

• SAS VDMML seemed to be a good fit in terms of analytical capabilities

• Everything client need seemed to be available

• EDEKA want to use some of the new features (Factorization Machines)

• Some data scientists with Python know-how

• Meet them where they are


SAS ViyaSolution scenarios

• Viya Single Node

• Recommend to use a separate machine

• SAS 9.4 M5 on theSAS9 side to leverageseamless integrationtools

- Data preparation still done on SAS9 side

20.05.2017, v1.0 (MAK) Option A: SAS 9.4 Plattform & SAS VDMML auf Single -Server (SMP)

Topologie

SAS Clients (9.4 & Viya)Datenquelle(n)

SAP ERP System

Oracle

Teradata

Authentifizierung

Host Authentifizierung für SAS 9.4

AD/LDAP Authentifizierung für

SAS Viya

Hadoop Cluster

MapR Hadoop Platform v5.2

6 Data Nodes

SAS Embedded Process

Shared Storage (optional)

SAS Enterprise Miner Projekte

SAS Data Marts

SAS ABTs

SAS 9.4 M5 Metadaten ServerSAS Enterprise Miner Server - Lizenz läuf im Dezember ausSAS Data Surveyor for SAP - SAS Data Integration ServerSAS/GRAPH; SAS/STATSAS/ETS; SAS/IMLSAS/Access to OracleSAS/Access to TeradataSAS/Access to HadoopSAS Data Loader for HadoopSAS Bridge to Viya

SAS 9.4 M5 SAS Analytics Server4 Cores / 32-64 GB RAMSLES 11 SP3

SAS Cloud Analytics Services (CAS) - In-Memory EngineCAS Controller - CAS Monitor - CAS Client ServicesCAS WorkerCAS Clients - SAS Studio Web Application - SAS Workspace CAS ClientSAS MicroservicesVisual Data Mining and Machine Learning (VDMML)

SAS Viya 3.2/3.3 (VDMML)4 Cores / min. 64-96 GB RAMSLES 11 SP3

SAS 9.4

SAS Management Console

SAS Enterprise Miner

SAS Data Integration Studio

SAS Enterprise Guide

SAS Viya

SAS VDMML (Browser)

SAS VA (Browser)

SAS VS (Browser)

EP EP EP EPEPEP


SAS ViyaSolution scenarios

• Viya Distributed

• Deploy CAS on MapRdata nodes

• Recommend to increase to 8 cores at least (4x8 cores)

• Deploy Viya support services on SAS9 node

• SAS 9.4 M5 on the SAS9 side to leverage seamless integration tools

For the fiscal year ending in

January 2017, Walmart’s total

Revenue was $485.9 Billion


• Small Format- Store format optimization- Remodel Optimization- Store Clustering

• Supply Chain- Forecasting Truck demand for 2yr- DC Route Optimization

• Real Estate- Store layout optimization- Site selection for remodels

• Energy- Solar energy production- Energy demand by store by hour

Known High Impact Analytics Projects • Logistics and Transportation

- Ability to leverage existing projects - U.S. Distribution Center Network Coverage

Model- Transportation Optimization

• Forecasting- Forecast Online Sales- Demand Planning and Forecasting for Stores

• Omni Channel Merchandising & Marketing- Customer Analytics- Market Basket Analysis- Trade Area Analytics- Marketing Attribution

Enhanced Analytical Innovation HubLeveraging SAS Open Platform

• Make it easier for users to access environment

• Provide relevant tools to work being completed

• Allow world wide access to environment• Simplicity in managing global platform• Leverage central IT functions

• Unrestricted user access• Additional organizations and users

leverage central environment

Increase utilization of investment in SAS

Improve User Experience

Develop Global Analytics Platform

SAS GridSAS ViyaAnalytics

• Add Small environment of Viya to the below which adds the following benefits;

• Allow for Open Source programming (API’s for R, Python, Java, Lua, REST) that teams already have strong skills in

• Industry leading machine learning, deep learning and natural language processing

• Governance of and standardization on models and analytics

• SAS’s Open Platform Viya is the next iteration of SAS’s industry leading analytics platform that will enable significant future innovation

• Keep same number of cores (64 Cores) – “like for like approach” with fresh architecture and versions of software

• Combine Sunnyvale and Grid environment to provide for large scale forecasting

• License the same software across all grid nodes for ease of deployment and future upgrades

• Provide for high availability & lower cost by virtualizing & clustering SAS Metadata, Midtier and Grid Manager

Open Platform– Including SAS ViyaRecommendations Summary

Platform Goals & Returns

Better Best

WorkersControllers


&SAS Viya

SAS 9

one SAS platform

SAS platform strategy

sas viya. Примеры проектов на новой платформе · introduce defect...

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