Data Science Automation: The Next

Frontier

Doug Freud

Associate Vice President, Innovation, Data Science, & Data Strategy

If you do not wake up everyday and

think about how your company is

going to disrupt your industry you

can bet that one of your competitors

is already doing it.

Amazon’s Digital Disruption of Retail World

In the Beginning……

15 years ago A/B tests ruled!

Amazon.com’s high upsell cart

Add an item to your cart and get a whole

page of product recommendations

SVP at the time said, “No way. Do not test it.

Anything that

distracts shoppers from

checkout will hurt our

conversion rate.”

Greg Linden said, “Okay

I’ll test it.” Generated $7m

attributable sales a day in 2004.

First Generation Recommendation Engine

Today the Recommendation Engine

Accounts for 35% of Sales

Revenue

ML is the New BI

BI:

Powered by

humans for human

consumption.

Understanding

what has happened

Exploratory Analysis: Powered by advanced

techniques

(Statistical/Machine

Learning/Data Mining) for

human consumption. Ad-

Hoc / R&D approach. Why

did it happen and how to

improve and optimize

ML: Machines/Systems are

making decisions or

recommendations that

are powered by ML

algorithms. The

probabilities or rules

are consumed by

software or processes,

and automatically

continue to learn and

improve.

“Interconnected” Data is Growing Exponentially

*** Gartner says the “The Internet of Things” install base will grow to 26 billion units by 2020 ** How Much Data Is Generated Every Minute On Social Media?

26B Connected things by 2020***

3.5 B Google search per day*

“Data is the new oil, but in order to monetize it requires predictive analytics”

IOT • expected to be a $1.9 billion market by

2020, according to Gartner.

• 90 percent of all data generated by IOT is never analyzed or utilized

in business decision processes. • Sensors & Computer logs

Consumer Internet • Internet Surfing, email, Social media • 1.4 Billion active Facebook users,

Twitter 21 million tweets per hour, 300 Million active Instagram users, &

290,728 Tinder matches per minute • Text & Web Logs

Challenges for the Chief Analytics Officer

Shortage of

Analytical

Talent

Complicated

Data

Management

Shorter

Decision

Cycles

Keeping Pace Requires Automation: A Factory Approach

Models Per Month

Source: Adopted from Factory Analysis vs.

Craftsman Analysis, Gartner, 2010

2005 2010 2015 2020

Factory Automation:

• Creating Analytical Data Sets

• Automation around Model Building

• Deployment

• Model Management

works with Lucy to make

more accurate expert

models works with Frederick to gather

the data he needs.

works with Susan

on data mining

tasks.

ETL

Champion

Predictive

Model

Manager

Platform

Architect

Data

Scientist

Sets business requirements and

sponsors project

Data Science is a Team Sport

Dynamically Creating Analytical Data Sets

Automating Modeling Process

Automating Model Management

17 © 2016 SAP AG or an SAP affiliate company. All rights reserved.

Fleet Level Information

Machine Level Information

PdMS Application shows insights about health

score of machines and business information

ERP + MRS

Maintenance Schedules & Financial Information

Action

~10% Reduction in Maintenance Costs

Machine Learning for SAP’s digital core, cloud and networks

18

• CV matching

• Freelancer matching

• EE scoring with NLP

• Employee Lifetime Value

• Career path recommender

• Employee Churn Prediction

• Service Finder

• Decision Support

• Predictive Maintenance

• Smart Forecasting Model

• Failure Detection and

Prediction

• Maintenance Planning

Optimization

• Invoice matching

• Cash flow forecasting • Travel virtual agent

• Vendor matching

• Pay Me Now solution

• Procurement recommenders

• Semantic product understanding

• Procurement risk diversification

• Product recommender

• Customer Lifetime Value

• Social sentiment analysis

• Automated sales forecasting

• Cart abandonment prediction

• Marketing action recommender

27 INDUSTRIES • SAP Big Data Margin Assurance • XM Exchange Media Video Advertising recommender

SAP HANA

CLOUD

PLATFORM

• Clustering

• Regression

• Classification

• Anomaly detection

• Reinforcement

learning

© 2016 SAP SE or an SAP affiliate company. All rights reserved. 19 Internal

A B C

The Predictive Enterprise

The Predictive Factory Improve bottom line through managing 000’s of

data sets and models

Predictive IP Generic and specialized algorithms

Big Data Make economical sense of more

data collected

Embedded in Processes

and Apps Cloud Easy to consume apps and micro services

On Premise In tandem with SAP HANA and SAP BI

P

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High and Low Touch UX’s For all data scientists: citizens and experts

Functional

Delivery

© 2016 SAP SE or an SAP affiliate company. All rights reserved.

Thank You!

Doug Freud

Associate Vice President

Doug.Freud@sap.com