Week 4: Embedded Predictive And Machine Learning Unit 1: Intelligent .
Week 4: Embedded Predictive and Machine LearningUnit 1: Intelligent Processes in SAP S/4HANA –Overview
Intelligent processes in SAP S/4HANA – OverviewWhy do we care so much about intelligence in SAP S/4HANA?External challengesInternal challenges Dynamic environment and globalcompetition Quick fix for broken and legacyprocesses Automation for differentiation vs.operation High maintenance of projectpatchwork Talent scarcity and meaningful workWhy intelligent processesin SAP S/4HANA? Address common process challenges Native integration into SAP S/4HANA Designed with E2E business process inmind Scale beyond proof of concept Increased automation and actionableinsights Expertise, trust, and reliability of SAP Focus on higher value and expert tasks Defined models coming to life with yourdata1 Limited success scaling proof ofconcepts1 Built-in lifecycle managementAccenture (2019) – AI: Built to Scale 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC2
Intelligent processes in SAP S/4HANA – OverviewIntelligent technologies assist, adapt, and automate end-to-end business processesContinuous learning from business data leads tocontinuous improvement of business processesCore capabilities Assist data-driven decision-making Adapt business processes in real time Automate processes within and between systemsKey principles Scalable enterprise-grade AI Tangible business outcomes Trusted data and intelligent recommendations Integrated technologies and processes 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC3
Intelligent processes in SAP S/4HANA – OverviewMachine learning in SAP S/4HANAEmbed in SAP S/4HANA Embedded machine learning,predictive analytics “Simple” cases like trending orforecasting Algorithms with low CPU–RAM–data demand such as regression,clustering, classification, timeseries, and so on SAP HANA, SAP Analytics CloudConsume from SAP BTP Side-by-side machine learning Resource-intensive cases likeimage or language processing Neural networks with highCPU–RAM–data demand such asimage recognitionExtend to SAP Analytics Cloud Explorative requirements forbusiness users Predictions based on SAPS/4HANA CDS views can beachieved using smart servicesfunctionality of SAP Analytics Cloud Based on SAP BusinessTechnology PlatformLearn from custom-specific history and exceptions to predict, support, automate, and optimize business user decisions 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC4
Intelligent processes in SAP S/4HANA – OverviewDemo 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC5
Intelligent processes in SAP S/4HANA – OverviewResources to help you get startedIntelligent scenario lifecycle management (ISLM)References ISLM in SAP S/4HANA Cloud SAP TechEd 2020 Replay ISLM in SAP S/4HANA SAP Community Webinar ISLM Community ISLM Blog SeriesTrial optionsIntelligent ERP Community SAP S/4HANA Fully Activated Appliance( pilot extended ISLM features) Intelligent ERP Community 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC6
Intelligent processes in SAP S/4HANA – OverviewKey takeaways SAP S/4HANA transforms end-to-end businessprocesses into intelligent business processes Over 300 intelligent capabilities available forSAP S/4HANA (and that number is growing) Moderate machine learning requirements such asforecasting can be handled embedded inSAP S/4HANA (using PAL and APL) 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC7
Thank you.Contact information:open@sap.com
Follow all of SAPwww.sap.com/contactsap 2021 SAP SE or an SAP affiliate company. All rights reserved.No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission ofSAP SE or an SAP affiliate company.The information contained herein may be changed without prior notice. Some software products marketed by SAP SE and itsdistributors contain proprietary software components of other software vendors. National product specifications may vary.These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation orwarranty of any kind, and SAP or its affiliated companies shall not be liable for errors or omissions with respect to the materials.The only warranties for SAP or SAP affiliate company products and services are those that are set forth in the express warrantystatements accompanying such products and services, if any. Nothing herein should be construed as constituting an additionalwarranty.In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document orany related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation,and SAP SE’s or its affiliated companies’ strategy and possible future developments, products, and/or platforms, directions, andfunctionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reasonwithout notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, orfunctionality. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differmaterially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, and theyshould not be relied upon in making purchasing decisions.SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registeredtrademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. All other product and service namesmentioned are the trademarks of their respective companies.See www.sap.com/trademark for additional trademark information and notices.
Week 4: Embedded Predictive and Machine LearningUnit 2: Machine Learning and Predictive Analytics:Architecture and Concepts
Machine learning and predictive analytics: architecture and conceptsAgenda1. Decision tree and approaches2. Architecture overview3. Embedded models4. Side-by-side models 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC2
Machine learning and predictive analytics: architecture and conceptsDecision tree – predictive analytics and machine learning with SAP S/4HANAS/4 – SAP S/4HANACDS – Core Data ServicesSAC – SAP Analytics CloudPAL – Predictive Analysis LibraryAPL – Automated Predictive LibraryDI – SAP Data IntelligenceWhat isyour usecase?Simple ML scenario usingclassic algorithms, low CPU &RAM, no external dataUnforeseen, exceptional andirregular ML scenarioCDS viewavailable in S/4?1. Use S/4 data tobuild MLmodels in SAC2. Leverageembedded SACor publishmodels back toS/41. Acquire S/4 data inSAC or live connectwith S/4 data2. Build ML models inSAC automatically3. Visualize predictionswith SACExplorative Predictive Analytics 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLICWhich MLlibrary isrequired?1. Access S/4 data withHANA APL2. Build ML modelsautomatically3. Generate API forconsumption1. Access S/4 data withHANA PAL2. Build ML modelsprogrammatically3. Implement API forconsumptionEmbedded Machine LearningComplex ML scenario usingdeep learning, high CPU &RAM, with external dataWhich MLlibrary isrequired?1. Access S/4 data withAI Business Services2. Build ML modelsautomatically3. Integrate API forconsumption1. Access S/4 data withSAP DI2. Build ML models usingPython etc.3. Implement API forconsumptionSide-by-Side Machine Learning3
Machine learning and predictive analytics: architecture and conceptsApproachesEmbedding predictive algorithms in SAP S/4HANA(embedded)Consuming predictive and ML services fromSAP Business Technology Platform (side-by-side)21SAP Business Technology PlatformSide-by-side ML using SAP Data Intelligence solution (ISLM*)Embed ISLMPAL, APL, R, Python PAL and APLLeveraging predictive analytics with SAP AnalyticsCloud (explorative analytics with side-by-side)Businessintelligence3EnterpriseSAP AnalyticsplanningCloudIntelligent decisionsSmart predictand smart assistAugmentedanalyticsSide-by-side ML using SAP AIBusiness Services (ISLM*)Enhancing and extending predictive analyticsand ML services (extensibility of the models)SAP Analytics Cloud(smart predict)SAP BTP(SAP DI ML models)4ExtendingmachinelearningSAP S/4HANA(ISLM with PAL)SAP BTP(AI foundation hybrid ML models)SAP S/4HANA – CDS viewsSAP S/4HANA(ISLM with APL)Best practices of leveraging predictive analytics and machine learning with SAP S/4HANA 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLICISLM – intelligent scenario lifecycle management; BTP – Business Technology PlatformPAL – Predictive Analysis Library; APL – Automated Predictive Library; CDS – core data services4
Machine learning and predictive analytics: architecture and conceptsArchitecture overview: SAP S/4HANA, the intelligent ERPSAP S/4HANAon-premise cloudSAP Business Technology PlatformAutomationremote controlsEnd userSAP CoPilotMicro ChartsProposalsEmbeddedAnalyticsUIsSAP FioriUISAP IntelligentRPABusinessRulespowered byBusinessEventsIS LifecyleManagementSituationHandlingVirtual DataModelApplicationHEMiPALAPLSide-by-side MLAPIsEventsstore historical situation dataSAP HANA MLBig DataServicesSAP AnalyticsCloudliveconnectionSAP HANADatabaseCitizen DataScientistsEmbedded ML 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLICWorkflowSAP DataSAPIntelligence Conversational/ AI nal Data5
Machine learning and predictive analytics: architecture and conceptsEmbedded predictive models in SAP S/4HANABuilt-InConsumerPROCESS THE ALGORITHMSWHERE THE DATA IS:ExplorativeConsumerODataLOW TCO & OPTIMALPERFORMANCEInA, MDXISLMServicesSAP S/4HANAAnalytical EngineCDS ViewModeling &AdministrationCDS View for MLSASLEAD BACK PREDICTIVEANALYTICS TO CDS VIEWS:CONTENT & CONCEPT REUSEISLMRepositorySQL ViewApplicationTableML ModelSAP HANA 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC6
Machine learning and predictive analytics: architecture and conceptsSide-by-side ML models on SAP BTPIntelligent SAP Fiori /Conversational AISAP S/4HANA ML AppML ServiceConsumptionSAP S/4HANASAP Data IntelligenceML ServiceConsumptionBusiness LogicMachine Learning ClientPipelineEngineBusiness LogicModelRepository 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLICData Integrationfor Model TrainingDataScienceToolsDeepLearning/ GPUMonitor /OperateBusiness Data Lake7
Machine learning and predictive analytics: architecture and conceptsSide-by-side models with explorative predictive analytics on SAP Analytics CloudSAP Fiori UIExplorative UI Create BI dashboardswith smart services Embed predictions intothe planning dashboards Data acquisition or liveconnection fromSAP S/4HANA Leverage SAP HANAAPL algorithmsSmartServicesSAP S/4HANAApplication 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLICApplication Content: Models/StoriesAutom. Predict.LibraryApplicationDataSAP Analytics nSmartInsightsSmartDiscoverSearchInsightBusiness Data Lake8
Machine learning and predictive analytics: architecture and conceptsKey takeaways Bring the algorithms to the data to avoid datareplication Model training is TCO-relevant Data model of SAP S/4HANA is based on core dataservices (CDS technology) SAP S/4HANA supports multiple deployment options– on-premise, private cloud and public cloud 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC9
Thank you.Contact information:open@sap.com
Follow all of SAPwww.sap.com/contactsap 2021 SAP SE or an SAP affiliate company. All rights reserved.No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission ofSAP SE or an SAP affiliate company.The information contained herein may be changed without prior notice. Some software products marketed by SAP SE and itsdistributors contain proprietary software components of other software vendors. National product specifications may vary.These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation orwarranty of any kind, and SAP or its affiliated companies shall not be liable for errors or omissions with respect to the materials.The only warranties for SAP or SAP affiliate company products and services are those that are set forth in the express warrantystatements accompanying such products and services, if any. Nothing herein should be construed as constituting an additionalwarranty.In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document orany related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation,and SAP SE’s or its affiliated companies’ strategy and possible future developments, products, and/or platforms, directions, andfunctionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reasonwithout notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, orfunctionality. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differmaterially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, and theyshould not be relied upon in making purchasing decisions.SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registeredtrademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. All other product and service namesmentioned are the trademarks of their respective companies.See www.sap.com/trademark for additional trademark information and notices.
Week 4: Embedded Predictive and Machine LearningUnit 3: Embedded Machine Learning with ISLM
Embedded machine learning with ISLMAgenda1. Overview2. Evolution of ISLM3. Personas and ML models4. Demo 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC2
Embedded machine learning with ISLMOverviewStandardized consumption and operation ofmachine learning scenarios for both flavorsEmbedded scenario:Machine learning provider (for example, MLwith Automated Predictive Library andPredictive Analysis Library in SAP HANA)runs in same stack as business application(SAP S/4HANA) 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLICSide-by-side scenario:Machine learning provider runs in differentstack (for example, the SAP DataIntelligence solution) than the businessapplication (SAP S/4HANA)3
Embedded machine learning with ISLMEnd-to-end lifecycle managementHarmonized framework in basis SAP software layerSuccessor of SAP Predictive Analytics integratorStandard to train, deploy, activate even for remote ML providersSupport for all phases (readiness, first usage, life cycle operations, deletion, decommissionLifecycle management of ML servicesprovisioned as a serviceCommon consumption model for applicationintegration for SAP S/4HANA 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC4
Embedded machine learning with ISLMManaging the lifecycle of SAP S/4HANA Machine Learning ScenariosIntelligent scenario lifecycle management closes the gap between business app (e.g. SAP S/4HANA)and the used machine learning artifact as it offers lifecycle management of the machine learning artifact inthe context of the intelligent application consuming it.Customer segments are:Migrated “PAi”scenariosApprox. 20 shippedscenarios &partner/customerscenarios migrated toISLM 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLICNew SAP S/4HANAIntelligent Scenariosintegrated inbusiness solutionCustom developedscenariosbased onside-by-side MLCustom developedscenariosbased on embeddedSAP HANA MLBased on HANA ML(APL, PAL), SAP DI,AIF, AI BUS, ML offered in SAP DI,Predictive scenariosbased on HANA ML(APL/PAL)5
Embedded machine learning with ISLMSAP Predictive Analytics integrator evolution into ISLMEnhanced&EvolvedISLM offered as part of basis layerISLM delivers feature compatibility with predictive analytics integrator functionality to support: Smooth migration for existing Predictive Analytics integrator use cases and artifacts Side-by-side use cases: AI API based, SAP DI, AI Business Services, AIF/AI core, Google AI (PoC)etc. Enhanced features: Creation of Intelligent scenarios of all typesOne central cockpit to integrate Scenarios based on libraries provided by SAP HANA, such as Automated Predictive Library (APL) and Predictive AnalysisLibrary (PAL) Remote scenarios based on SAP Data Intelligence 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC6
Embedded machine learning with ISLMPersonas involved in development, consumption, and operationSAP S/4HANABusiness applicationEnhance businessapplication with MLInference consumptionUtilize ML inferenceBusiness userABAP developerIntelligent scenario ownerCreate and publishintelligent scenarioEnable, train, deployML scenarioEmbedded ML in AMDP, CDSBusiness administratorSAP HANA (APL, PAL)Side-by-side ML scenario viaRest APIsDevelop ML artifactsData science developer 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLICSAP BTP or other MLplatformsSet up and configuretechnical sidesTechnical administrator7
Embedded machine learning with ISLMCreate intelligent scenario 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC8
Embedded machine learning with ISLMKey takeaways ISLM enabling efficient lifecycle management of machine learningscenarios in SAP S/4HANA New harmonized framework in basis SAP software layer(no additional license required) No ticket-based approach ISLM, the successor of Predictive Analytics integratorfunctionality New entity: intelligent scenarios (predictive scenarios MLscenarios) Common consumption model for application integration ofSAP S/4HANA – to ensure stable APIs for developers Management of remote models especially for ML servicesprovisioned as a service Support for all phases (readiness, first usage, lifecycle operations,deletion, decommission) Released with SAP S/4HANA 2020 First cloud shipment with SAP S/4HANA Cloud 2011 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC9
Thank you.Contact information:open@sap.com
Follow all of SAPwww.sap.com/contactsap 2021 SAP SE or an SAP affiliate company. All rights reserved.No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission ofSAP SE or an SAP affiliate company.The information contained herein may be changed without prior notice. Some software products marketed by SAP SE and itsdistributors contain proprietary software components of other software vendors. National product specifications may vary.These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation orwarranty of any kind, and SAP or its affiliated companies shall not be liable for errors or omissions with respect to the materials.The only warranties for SAP or SAP affiliate company products and services are those that are set forth in the express warrantystatements accompanying such products and services, if any. Nothing herein should be construed as constituting an additionalwarranty.In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document orany related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation,and SAP SE’s or its affiliated companies’ strategy and possible future developments, products, and/or platforms, directions, andfunctionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reasonwithout notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, orfunctionality. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differmaterially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, and theyshould not be relied upon in making purchasing decisions.SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registeredtrademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. All other product and service namesmentioned are the trademarks of their respective companies.See www.sap.com/trademark for additional trademark information and notices.
Week 4: Embedded Predictive and Machine LearningUnit 4: Leveraging Predictive Services fromSAP Analytics Cloud
Leveraging predictive services from SAP Analytics CloudSAP Analytics CloudCOMPLETECONTEXTUALCERTAINImprove decisionmaking with all analyticscapabilities in one placeGain instant insights andtake action in context ofbusiness processesMake smarter and fasterdecisions with artificialintelligence (AI)driven insights 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC2
Leveraging predictive services from SAP Analytics CloudSAP Analytics Cloud – augmented analyticsCatalogMobile AppCentralized PortaliOS & AndroidDigital BoardroomStoriesBusinessIntelligenceData ExplorationDashboards & VisualizationsEnterprise ReportingPLATFORM SERVICES 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLICAnalytic ted AnalyticsPredictive AnalyticsData ConnectivityData PreparationData ModelingMS Office IntegrationEnterprisePlanningEvents & WorkflowsSharing & SimulationPredictive PlanningContent TranslationLifecycle MgmtAuditing & MonitoringSchedulingCollaborationAPIs and SDKs3
Leveraging predictive services from SAP Analytics CloudMake decisions faster with AI-driven insights1. Conversational2. Automated3. PredictiveAsk questions in a conversationalmanner with instant resultsexplained in natural languageDetect drivers of a KPI and take thenext best action using automatedmachine learning that discoversunknown relationships in dataPredict potential outcomes,generate forecasts, and automatepredictive planning 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC4
Leveraging predictive services from SAP Analytics CloudA faster way to find better answers – conversational analytics Ask questions in naturallanguage and instantlygenerate the bestvisualizations Enhance visualizations within-context explanations Recognize important trendsand drivers at the click of abutton 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC5
Leveraging predictive services from SAP Analytics CloudSearch to insight what’s happening in my business?User enters naturallanguage searchAuto-completeand NLP assistthe userUser selectsquery fromgeneratedproposalsQuery executesautomaticallyAutomaticallygeneratedchart providesthe results As questions are easy to ask, analysis can happen on an ad-hoc basis in meetings, etc. Auto-complete and natural language processing aid you in finding the information you need Save time when building stories with automatically generated visualizations 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC6
Leveraging predictive services from SAP Analytics CloudSmart insights what’s behind this number?User selects data pointSAP Analytics Cloud findscontributorsUser can embed insight inchart or find additionalinsights Find out what contributes to an interesting data point or variance The contributors often prompt you as to what question to ask next Answer follow-on questions with a single click Add depth to visualizations with contextual explanations 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC7
Leveraging predictive services from SAP Analytics CloudSmart discovery why did this happen?User selects a figure oroutcomeSAP Analytics Cloudautomaticallyanalyzes the dataPredictive modelreveals patterns andrelationshipsA story is generatedto drive accelerateddata exploration Automated story-building and data exploration Builds a story automatically that provides multiple perspectives on your data incredibly quickly Natural language and visualization explain the reasons behind key figures or outcomes 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC8
Leveraging predictive services from SAP Analytics CloudSmart predict in BI and planning workflowsTraditional AnalyticsDatapreparationBI & planningmodelingStory design& consumptionAugmented Analytics with Smart PredictDatapreparationPrepare data withadditional attributes 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLICSmart predictBuild predictivemodel in a few clicksBI & planningmodelingEnrich BI and planningmodels with outcomesStory design& consumptionVisualize new insights inBI and planning stories9
Leveraging predictive services from SAP Analytics CloudNo data science skills needed automated ML process to choose the best modelInputdatasetEncodedataTrainmodelsOptimal modelselected automaticallyBestmodelSimpledebriefVladimir Vapnik-----Statistical Learning Theory1998 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC10
Leveraging predictive services from SAP Analytics CloudExplorative analytics using SAP Analytics Cloud – smart predict, smart assist Build predictive models using SAC smart predictand smart assist functionality Leverage the SAP S/4HANA whitelisted CDS views Acquire data into SAC Visualize in SAC 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC11
Leveraging predictive services from SAP Analytics CloudDemoA quick overview of the smart predict functionality in SAC 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC12
Leveraging predictive services from SAP Analytics CloudKey takeaways Reduced time to benefit Lower costs with one integrated solution Scale to your needs with easy extensibility Rapid innovation with AI-driven insights 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC13
Thank you.Contact information:open@sap.com
Follow all of SAPwww.sap.com/contactsap 2021 SAP SE or an SAP affiliate company. All rights reserved.No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission ofSAP SE or an SAP affiliate company.The information contained herein may be changed without prior notice. Some software products marketed by SAP SE and itsdistributors contain proprietary software components of other software vendors. National product specifications may vary.These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation orwarranty of any kind, and SAP or its affiliated companies shall not be liable for errors or omissions with respect to the materials.The only warranties for SAP or SAP affiliate company products and services are those that are set forth in the express warrantystatements accompanying such products and services, if any. Nothing herein should be construed as constituting an additionalwarranty.In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document orany related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation,and SAP SE’s or its affiliated companies’ strategy and possible future developments, products, and/or platforms, directions, andfunctionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reasonwithout notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, orfunctionality. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differmaterially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, and theyshould not be relied upon in making purchasing decisions.SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registeredtrademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. All other product and service namesmentioned are the trademarks of their respective companies.See www.sap.com/trademark for additional trademark information and notices.
Week 4: Embedded Predictive and Machine LearningUnit 5: Machine Learning Services Consumedfrom SAP Business Technology Platform
Machine learning services consumed from SAP Business Technology PlatformIntelligent Enterprise eInsightinto actionIncreasedresilienceMachinelearningRobotic processautomation 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC2
Machine learning services consumed from SAP Business Technology PlatformOverviewBest practices integrated intoyour business processesFast time tobusiness valueFlexibility to serve yourneeds and standardsSAP AIBusiness ServicesSAP Business Technology Platform 2021 SAP SE or an SAP affiliate company. All rights reserved. ǀ P
Machine learning and predictive analytics: architecture and concepts Embedded predictive models in SAP S/4HANA PROCESS THE ALGORITHMS WHERE THE DATA IS: LOW TCO & OPTIMAL PERFORMANCE LEAD BACK PREDICTIVE ANALYTICS TO CDS VIEWS: CONTENT & CONCEPT REUSE SAP S/4HANA SAP HANA Analytical Engine S s ISLM Repository Modeling & Administration SAS OData .
(prorated 13/week) week 1 & 2 156 week 3 130 week 4 117 week 5 104 week 6 91 week 7 78 week 8 65 week 9 52 week 10 39 week 11 26 week 12 13 17-WEEK SERIES* JOIN IN MEMBER PAYS (prorated 10.94/week) week 1 & 2 186.00 week 3 164.10 week 4 153.16 week 5 142.22 week 6 131.28 week 7 120.34
Week 3: Spotlight 21 Week 4 : Worksheet 22 Week 4: Spotlight 23 Week 5 : Worksheet 24 Week 5: Spotlight 25 Week 6 : Worksheet 26 Week 6: Spotlight 27 Week 7 : Worksheet 28 Week 7: Spotlight 29 Week 8 : Worksheet 30 Week 8: Spotlight 31 Week 9 : Worksheet 32 Week 9: Spotlight 33 Week 10 : Worksheet 34 Week 10: Spotlight 35 Week 11 : Worksheet 36 .
28 Solving and Graphing Inequalities 29 Function and Arrow Notation 8th Week 9th Week DECEMBER REVIEW TEST WEEK 7,8 and 9 10th Week OCTOBER 2nd Week 3rd Week REVIEW TEST WEEK 1,2 and 3 4th Week 5th Week NOVEMBER 6th Week REVIEW TEST WEEK 4,5 and 6 7th Week IMP 10TH GRADE MATH SCOPE AND SEQUENCE 1st Week
predictive analytics and predictive models. Predictive analytics encompasses a variety of statistical techniques from predictive modelling, machine learning, and data mining that analyze current and historical facts to make predictions about future or otherwise unknown events. When most lay people discuss predictive analytics, they are usually .
Year 4 negative numbers. digit numbers by one digit, integer Year Group Y4 Term Autumn Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 10 Week 11 Week 12 Number – place value Count in multiples of 6, 7, 9. 25 and 1000. digits using the formal writt
WRM –Year 6 –Scheme of Learning 2.0s Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 10 Week 11 Week 12 tumn Number: Place Value N
Year 11 HSC Assessment Policy 2019 An information guide for parents and students. 2 Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 10 Week 11 . Anc History English Studies Physics Std English Adv English Drama CAFS Std Maths Adv Maths Ext Maths Visual Arts PDHPE Dance
(e.g. Kerala, Goa, Andhra Pradesh, Gujarat) N/a 95% average 90% average 85% average . Description / Offer making : . (with or without Maths), Social Studies, Arts or Science. Students normally take English plus an Indian language and a range of elective subjects. Exeter’s recognition is normally on the basis of a group of 5 or more subjects excluding the Indian language and subjects like .
