SAS Event Stream Processing

Transkript

1 SAS vent Stream Processing i samspil med SAS Real-Time Decision Manager Jan Thomas Løwe, CI Konsulentdirektør, SAS Institute

2 SAS vent Stream Processing Baggrund

3 SAS vent Stream Processing Baggrund Software designet til løbende at analysere data, mens det er i bevægelse, og som det bliver genereret. Bryder det traditionelle paradigme med lagring af data for derefter at analysere det. Data gemmes som udgangspunkt ikke. Vigtige hændelser kan. Vigtige hændelser kan alarmere. (Overvåge sensorer og trigge alerts). Vigtige hændelser kan initiere realtidskundeinteraktioner. Hændelsen afleveres til SAS Real-Time Decision Manager.

4 SAS vent Stream Processing (SP) Historie Produktet har eksisteret i nogle år efterhånden - og indtil nu som en kodebaseret løsning - uden interface Første kunde 2. kvartal 2013 I dag flere end 25 implementeringer SAS SP 3.1 blev frigivet i maj nu med grafisk interface, SAS SP Studio + SAS SP Stream Viewer Tidligere (version 2.3 & før) Nu (version 3.1)

5 PUBLISHING INTRFAC SUBSCRIBING INTRFAC SAS vent Stream Processing Funktionel arkitektur SP STUDIO SP STRAM VIWR VNT STRAM PROCSSING NGIN Processes data continuously, on the move, in-memory with very high speed and low latency Apply rules and analysis using a dataflow centric SP model Filtering, aggregation, pattern detection, calculations, correlations, procedural, text mining, thresholding and much more

6 SAS VNT STRAM PROCSSING SOURC WINDOW FILTR : QTY >=1000 AGGRGATION ID SYMB TextQTY PRIC ID SYMB QTY PRIC SYMB AV_PRIC DATA IN (vents) DATA OUT (vents) ID SYMB QTY PRIC 10 IBM ksempel Vi får handler fra et kapitalmarked Vi ønsker den aktuelle, gennemsnitlige pris af handler, hvor Quantity >= 1000 Fremgangsmåde: 1. vent Stream Processing ngine 2. Bygger din SP-model (Continuous Query) 3. Start SP-modellen 4. Sender data, som de genereres

7 SAS VNT STRAM PROCSSING SOURC WINDOW FILTR : QTY >=1000 AGGRGATION ID SYMB TextQTY PRIC ID SYMB QTY PRIC SYMB AV_PRIC DATA IN (vents) 10 IBM MS IBM 105 MS 26 IBM 110 IBM MS 26 DATA OUT (vents) 40 IBM ID SYMB QTY PRIC

8 SAS Real-Time Decision Manager t produkt i SAS Customer Intelligence-suiten Inbound Campaign Management Træffe beslutninger i realtid i interaktive kundekanaler Beslutninger = tilbud, budskaber, anbefalinger eller andet (NBA/NBO/NBR) Kan inkludere/kombinere analytics (scoring i realtid), forretningslogik og kontaktstrategier Typiske kanaler inkluderer POS, CC, web Kanal sender decision request via WS n decision returneres fra RTDM

9 Real-Time vs. Batch Decision Outbound / Batch Decision Begynd at vælge tusindvis af kunder Segmenter i grupper på baggrund af eksisterende information Tildel tilbud til grupper Udfør udgående kontakt Inbound / Real-Time Decision n enkelt kunde møder op ved kontakttouchpoint Information i realtid videregives Baseret på hændelsen/ kontaktårsag træffes en beslutning til at finde det rette tilbud Tilbud er kendt Rette kunder skal udvælges Kunde er kendt Rette tilbud/budskab skal returneres

10 SAS Real-Time Decision Manager Floweksempel Decision Nodes: Udfører forskellige aktiviteter for at bestemme beslutningen Response Node: Sender web service-responsen tilbage til kanal og opdaterer intern kundehistorik vent: Web service interface imod kanal for decision request Start Node: Modtager web service request fra kanal, som inkluderer eventuel ny kundeinformation

11 Overview of Real-Time Decision Manager Channels Internet Request decision W B Real-Time Decision Manager xecute Decision Flow Analytical Insight Analytical Models Mobile Call Center ATM Receive response S R V I C V N T Apply Business Rules, Filtering Rules, Analytical Models and Assign Offers Offer Arbitration Business Rules Real-Time Data Store Customer Profile Preoptimized Offers Contacts & Responses

12 Data Streams Network Transactions Payments Billing ibeacons obs??? Pub Overview of Real-Time Decision Manager med vent Stream Processing vent Stream Processing Continous Query Rule xecution Maintain Individual aggregated customer record with calculated information Sub W B S R V I C V N T Real-Time Decision Manager xecute Decision Flow Apply Business Rules, Filtering Rules, Analytical Models and Assign Offers Offer Arbitration Analytical Insight Analytical Models Business Rules Real-Time Data Store Customer Profile Preoptimized Offers Contacts & Responses

13 DMO

14 DMO ibeacons Teknologi og brand fra Apple Udsender et Bluetooth-signal, smartphones kan opfange Signalet indeholder et unikt ID, der vha. ens app gør en smartphone i stand til at vide helt præcist, hvor den er App kan f.eks. give tilbud til loyalitetskunder, der befinder sig et specifikt sted på et specifikt tidspunkt eller kommer ofte Send tilbud og rabatter til en kunde, når denne er i nærheden af en vare eller en bestemt hylde

15 DMO

16 Tak for i dag Jan Thomas Løwe, , [email protected] Læs mere: SAS Support SAS Homepage You react so quickly! Do you have SP? Understanding Data Streams in IoT White Paper

17 SP KY TCHNICAL CHARACTRISTICS PRFORMANC Continuous in-memory processing Threaded pool & clustering Linux & Windows native app. Linear scalability Fastest SP on the market NTRPRIS CLASS High availability Guaranteed delivery Latency perf. measures Publish/subscribe Lightweight embedding technology FLXIBILITY Dataflow centric modeling Drag & drop visual modeler XML & C++ modeling 30+ out of the box connectors Public Publish & Subscribe API (Java or C) STRAMING ANALYTICS SAS Text Analytics SAS Data Quality SAS Analytics DataStep2 SAS LASR In-Memory Analytic Server

18 SP KY ARCHITCTUR TAKAWAY SAS vent Stream Processing is a stand-alone engine The SAS vent Stream Processing ngine can be installed on any single or distributed environment No dedicated hardware needed SP Studio Installs optionally with the SP ngine Runtime web server (tcserver) is provided Linux and Windows SP is very efficient CPU-wise vents memory retention may need a lot of RAM Medium configuration is 16 cores, 192Gb RAM

19 PUBLISH & SUBSCRIB CONNCTORS & ADAPTRS PUB/SUB API Connect to any system with Java or C Public, documented and easy to use Adapters are stand-alone processes and can be networked Publish to SP Source windows Subscribe to any SP window All Connectors & Adapters are built using the Pub/Sub API OUT OF TH BOX File/Socket XML / JSON Database (odbc) SAS LASR Hadoop SAS Dataset SAS HDAT JMS IBM WebSphere MQ Tibco RendezVous Syslog * Network Sniffer* HTTP RSTful OSIsoft PI Axeda Teradata SMTP ** SP to SP SP Project RabbitMQ Solace Tervela Google Protobuff Twitter* *Publish only **Subscribe only