run() ANP104 Massive Predictive Analytics

Transcription

1 run() ANP104 Massive Predictive Analytics Public

2 Speakers Las Vegas, Sept Erik Marcadé - Vice President, Advanced Analytics Products Bangalore, October 5-7 Paul Pallath, Chief Data Scientist, Advanced Analytics Products Barcelona, Nov 8-10 Erik Marcadé - Vice President, Advanced Analytics Products 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 2

3 Disclaimer The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the permission of SAP. Except for your obligation to protect confidential information, this presentation is not subject to your license agreement or any other service or subscription agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or any related document, or to develop or release any functionality mentioned therein. This presentation, or any related document and SAP's strategy and possible future developments, products and or platforms directions and functionality are all subject to change and may be changed by SAP at any time for any reason without notice. The information in this presentation is not a commitment, promise or legal obligation to deliver any material, code or functionality. This presentation is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. This presentation is for informational purposes and may not be incorporated into a contract. SAP assumes no responsibility for errors or omissions in this presentation, except if such damages were caused by SAP s intentional or gross negligence. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions SAP SE or an SAP affiliate company. All rights reserved. Public 3

4 Agenda Predictive Analytics and Machine Learning Overview What is Massive Predictive Analytics? A Small Word on Automation Some Examples 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 4

5 Predictive Analytics and Machine Learning Overview Public

6 User Engagement There is no such thing as an analytics continuum! Chasm!!! Prescriptive Analytics Predictive Analytics What should I do? Raw Data Cleaned Data Standard Reports Ad Hoc Reports & OLAP Agile Visualization Self Service BI Why did it happen? What will happen? What happened? Maturity of Analytics Capabilities 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 6

7 User Engagement There is no such thing as an analytics continuum! Chasm!!! Prescriptive Analytics Raw Data Humans make decision Data is aggregated for visualization UI integration at best Cleaned Data Standard Reports Ad Hoc Reports & OLAP Agile Visualization Self Service BI What happened? Predictive Analytics Why did it happen? What will happen? What should I do? Maturity of Analytics Capabilities 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 7

8 User Engagement There is no such thing as an analytics continuum! Chasm!!! Predictive Analytics Prescriptive Analytics Machines propose/make decision Data is de-normalized, flattened, fine grain Process integration at last What should I do? Raw Data Cleaned Data Standard Reports Ad Hoc Reports & OLAP Agile Visualization Self Service BI Why did it happen? What will happen? What happened? Maturity of Analytics Capabilities 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 8

9 Worldwide Market Sizes (Guesstimates) $10B $3B $1B Query Reporting Agile Viz Analytics Advanced/ Predictive Analytics Content/ Unstructured Analytics 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 9

10 Solving real world problems by optimizing resources and improving margins SALES & MARKETING OPERATIONS FRAUD AND RISK FINANCE AND HR OTHER SECTORS Churn Reduction Customer Acquisition Lead Scoring Product Recommendation Campaign Optimization Customer Segmentation Next Best Offer/Action Predictive Maintenance Load Forecasting Inventory/Demand Optimization Product Recommendation Price Optimization Manufacturing Process Opt. Quality Management Yield Management Fraud and Abuse Detection Claim Analysis Collection and Delinquency Credit Scoring Operational Risk Modeling Crime Threat Revenue and Loss Analysis Cash Flow and Forecasting Budgeting Simulation Profitability and Margin Analysis Financial Risk Modeling Employee Retention Modeling Succession Planning Life Sciences Health Care Media High Education Public Sector / Social Sciences Construction and Mining Travel and Hospitality Big Data and IoT 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 10

11 What is Massive Predictive Analytics? Public

12 What is Massive Predictive Analytics? M A S S I V E PREDICTIVE FACTORY P R E D I C T I V E FOR THE MASSES! 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 12

13 Major Investment Areas Functional Delivery P The Predictive Factory High and Low Touch UX s </> Predictive IP A B C Cloud Big Data On Premise Embedded in Processes and Apps 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 13

14 Crucial Need: Managing a Massive Number of Models P The Predictive Factory No coding, just configuration! Full predictive lifecycle Modeling automation Inclusive 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 14

15 More Users through Predictive Automation.. Open to Data Scientists! </> Low and High Touch User Experiences Low touch user interface using wizard-based approach and automated High touch user interface supporting open languages Interoperability between both 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 15

16 More Models With Generic/Specialized IP. Monetize your IP. A B C Predictive Intellectual Property Generic proprietary algorithms Niche proprietary algorithms Niche predictive IP to be available via a marketplace Open to data science standards and available resources 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 16

17 Massive Consumption through Cloud. Extend the Native Capabilities. Cloud All-in-one SAP BusinessObjects Cloud Guided Machine Discovery HCP, Predictive Services targeting partners and integrators 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 17

18 Massive Number of Models on Massive Data Volumes Big Data Data Preparation compatible with ultra-wide data sets Distribution of algorithms on scale-out architectures Integration into Big Data streaming environments Time on Hadoop/Spark PA 2.4 PA 2.5 PA SAP SE or an SAP affiliate company. All rights reserved. Public 18

19 Massive Deployment requires a Simplified Product Design Desktop Evolutions Predictive Factory - Fiori Automated UI5 scheduling app Automated Java Swing Client Expert (HTML/Java) KxShell Client Automated Java Swing Client, KxCORBAShell Predictive Factory - Fiori Automated & Expert UI5 app (successor authoring) SDK HTML/services Client Automated Java Swing Client (legacy features), KxHTMLShell Existing On premise, HANA (XSA) SDK (CORBA) Server Unmanaged APL Server BIP managed APL Predictive Analytics 3.x Sapphire 2016 Predictive Analytics 4.x Future 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 19

20 Predictive for the Masses through Integration Capabilities Embedded in Processes and Apps Predictive Analytics Integrator Leveraging powerful predictive libraries (APL, PAL, R) in HANA Included in every deployment of the Integrating app Out-of-the-box lifecycle management of predictive models (retrain, score, test) 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 20

21 A Small Word on Automation Public

22 Traditional Approach Problem Identified Aggregate & prepare data Identify relevant variables Derived features & encode variables Develop models Debrief models Write code for database execution Business Results What competition does for automation: Stack several algorithms and hope for the best 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 22

23 Value of SAP BusinessObjects Predictive Analytics Automation Problem Identified Aggregate & prepare data Identify relevant variables Derived features & encode variables Develop models Debrief models Write code for database execution Business Results Data Manager Generate SQL for HANA, Hadoop, Hive, SparkSQL, and all major databases 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 23

24 Value of SAP BusinessObjects Predictive Analytics Automation Problem Identified Aggregate & prepare data Identify relevant variables Derived features & encode variables Develop models Debrief models Write code for database execution Business Results Auto-algorithms Auto-Algorithms make this section obsolete 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 24

25 Value of SAP BusinessObjects Predictive Analytics Automation Problem Identified Aggregate & prepare data Identify relevant variables Derived features & encode variables Develop models Debrief models Write code for database execution Business Results Auto-algorithms Numbers, strings, dates Categorical, continuous, textual Date parts Composite variables (example: position from latitude and longitude) 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 25

26 Value of SAP BusinessObjects Predictive Analytics Automation Problem Identified Aggregate & prepare data Identify relevant variables Derived features & encode variables Develop models Debrief models Write code for database execution Business Results Auto-algorithms Classification, regression, clustering, times series, key influencers Link analysis, recommendations HANA (APL) Hadoop (Scala) 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 26

27 Value of SAP BusinessObjects Predictive Analytics Automation Problem Identified Aggregate & prepare data Identify relevant variables Derived features & encode variables Develop models Debrief models Write code for database execution Business Results Auto-algorithms All descriptive statistics available Key influencers, decision trees, segments, optimal binning and banding Communities 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 27

28 Value of SAP BusinessObjects Predictive Analytics Automation Problem Identified Aggregate & prepare data Identify relevant variables Derived features & encode variables Develop models Debrief models Write code for database execution Business Results In-Database Apply: Automated SQL generation Optimized with data manager HANA: Streaming (CCL) Hadoop: Streaming (Java) 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 28

29 Some Examples Public

30 Some Examples Large video provider Chemical company High tech company Transportation company ~1600 models retrained every month for product appetency 400 models in 11 families for more than 6 years for demand forecasting 400 models for sales pipeline accuracy improvement (built in 5 days ) 15,000 models for objects routing 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 30

31 SAP TechEd Online Continue your SAP TechEd education after the event! Access replays of Keynotes Demo Jam SAP TechEd live interviews Select lecture sessions Hands-on sessions 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 31

32 Further information Related SAP TechEd sessions: ANP101 - SAP BusinessObjects Predictive Analytics What You Really Need To Know 1hr Lecture ANP105 - Turning Big Data and IoT into Intelligence You Can Actually Use 1hr Lecture ANP108 - Predictive Business Intelligence: Give Your BI the Gift of Foresight 1hr Lecture ANP160 - SAP BusinessObjects Predictive Analytics 101: Discovery Session 2hrs Hands-On Workshop ANP205 - SAP BusinessObjects Cloud Brings Predictive Tools to the Business Analyst 1hr Lecture ANP260 - Massively Automate Predictive Models with Predictive Factory and SAP HANA 2hrs Hands-On Workshop ANP270 - SAP BusinessObjects Planning and Consolidation with Predictive Analytics 2hrs Hands-On Workshop ANP360 - Integration and Scripting with SAP BusinessObjects Predictive Analytics 2hrs Hands-On Workshop ANP600 - Start developing with the SAP HANA Cloud Platform predictive services 1hr CodeJam ANP806 - Road Map Q&A: SAP BusinessObjects Predictive Analytics 1hr Session SAP Public Web scn.sap.com/community/predictive-analytics sap.com/predictive SAP Education and Certification Opportunities Watch SAP TechEd Online SAP SE or an SAP affiliate company. All rights reserved. Public 32

33 Feedback Please complete your session evaluation for ANP104 Contact information: Erik Marcadé VP Advanced Analytics Products 2016 SAP SE or an SAP affiliate company. All rights reserved. Public 33

34 2016 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 of SAP SE or an SAP affiliate company. SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. Please see for additional trademark information and notices. Some software products marketed by SAP SE and its distributors 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 or warranty of any kind, and SAP SE or its affiliated companies shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP SE or SAP affiliate company products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty. In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document or any 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 platform directions and functionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reason without notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. All forwardlooking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions SAP SE or an SAP affiliate company. All rights reserved. Public 34