The Future of the SAS Platform. Mathias

Transcription

1 The Future of the SAS Platform Mathias

2 The analytics economy

3 The question is not whether data should be shared, but how we can usher in responsible methods for doing so. Link to Press Release

4 One platform that powers the analytics economy

5 Our digital transformation to power the analytics economy

6 Prior to SAS Viya Support for any analytics use case SAS 9.4 products and UIs Customer-written code Broad and extensive customer base in production Modernization needed to adapt to changing technology, business trends MVA runtime Metadata (WIP)-based mid-tier SAS 9.4 LASR and / or HPA runtimes Other runtimes (ESP, In- Database)

7 Parallel & Serial, Pub / Sub, Web Services, MQs Data Enablement Source-based Engines Solutions Enablement Customer Intelligence Analytics In-Stream In-Hadoop In-Database In-Memory Runtime Engine Cloud Analytics Services (CAS) Microservices UAA UAA UAA Data Source Mgmt Folders etc BI GUIs CAS Mgmt Log Analytics GUIs Data Mgmt GUIs Query Gen Env Mgr Model Mgmt Audit Solutions APIs Business Visualization Risk Management! Fraud and Security Intelligence Data Management Deployment Enablement Platform IT Enablement Developer Enablement

8 SAS interfaces (both licensed with every offering, optionally installable) SAS Visual Analytics GUI A B B C Visual Analytics 8.1 (B requires A) (B products require A) Unified and Managed Visual Statistics 8.1 (C requires A & B) Visual Data Mining and Machine Learning 8.1 SAS Studio GUI Visual Analytics 8.1 (procedures) Visual Statistics 8.1 (procedures) Visual Forecasting 8.1 (procedures) Visual Data Mining and Machine Learning 8.1 (procedures) Additional offerings not shown: SAS Event Stream Processing SAS Visual Investigator SAS Visual Scenario Designer Optimization 8.1 (procedures) Econometrics 8.1 (procedures) Company Confidential For Internal Use Only

9 MULTIPLE INTERFACES, SINGLE CODE BASE Visual Interfaces Programming Interfaces API Interfaces Company Confidential For Internal Use Only

10 proc print data = hmeq (obs = 10); run; Workers APIs Controller df = s.castable( hmeq ) df.head(10) CAS Action [table.fetch] table.name = hmeq from = 1 to = 10 df <- defcastable(s, hmeq ) head(df, 10)

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12 SAS platform strategy & SAS Viya SAS 9 one SAS platform

13 Today s architecture SAS 9.4 M4 products and UIs Customer-written code Customerwritten code SAS Viya products and UIs Metadata (WIP)-based mid-tier Microservices-based mid-tier SAS 9.4 M4 SAS/CONNECT bridge to SAS Viya SAS/CONNECT SAS Viya MVA runtime (full functionality) LASR and / or HPA runtimes Other runtimes (ESP, In- Database) Viya MVA runtime (minimal functionality) CAS runtime

14 September release architecture (projected) SAS 9.4 M5 products and UIs Customer-written code Customerwritten code SAS Viya products and UIs Metadata (WIP)-based mid-tier Microservices-based mid-tier SAS 9.4 M5 SAS Viya MVA runtime (full functionality) LASR and / or HPA runtimes Other runtimes (ESP, In- Database) bridge to SAS Viya no SAS/CONNECT Viya MVA runtime (deployed for Viya-only customers) CAS runtime

15 One SAS platform projected architecture Supports for any pre-existing 9.4, Viya-based code SAS products and UIs Customer-written code Single deployment Support for single, multiuser scenarios Elastic, fault-tolerant Cognitive MVA runtime Microservices-based mid-tier SAS platform CAS runtime Other runtimes (ESP, In- Database)

16 What Does This Mean To You? It means: Code is designed for parallel, distributed processing FAST so you can: Scale methods without redefining code Direct support for SAS, Python, R, Java, Lua Access to new machine learning algorithms SAS programs available as REST APIs Enable & collaborate new colleagues Expand your analytic toolkit Make your code portable Company Confidential For Internal Use Only

17 Cloud-based product experiences PaaS License an integrated set of products and capabilities that deploy to any public or private cloud RaaS Get answers to your specific questions without software SaaS Access individual products or toolsets via a selfservice business delivery model APIs Access individual capabilities as public REST APIs Marketplaces Add your IP to existing APIs and offer them for resale

18 What Comes Next? AI and cognitive computing Intelligent automation Networked data G P U s Ambient analytics

19 Key Takeaways Scaling portable analytics Facilitating collaboration Platform for your new innovations

20 Experience Your New Possible