Unleash the Value of Big Data through Predictive Analytics with SAP HANA

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Unleash the Value of Big Data through Predictive Analytics with SAP HANA

Philip Mugglestone

September 10-13, 2012

Orlando, Florida

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• New market forces are changing the landscape and

offering new opportunities

• Predictive analysis can be for everyone in the

business

• SAP HANA is the cornerstone of SAP’s vision for

predictive analytics

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Agenda

The Predictive Analytics Landscape

Predictive Analytics with SAP HANA

Customers Benefit from Predictive Analytics with SAP HANA

Predictive Applications for SAP HANA

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Agenda

The Predictive Analytics Landscape

Predictive Analytics with SAP HANA

Customers Benefit from Predictive Analytics with SAP HANA

Predictive Applications for SAP HANA

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What if…

. . . You could identify hidden revenue opportunities

within your customer base through predictive

analytics?

. . . You could retain your high-value

customers/employees/vendors/partners with the

right retention offers?

. . . Your call center agents could delight customers

with the best next-step recommendations?

. . . You could increase cross-sell and up-sell

effectiveness through cross-channel

coordination?

. . . You could build long-term

customer/employee/vendor/partner relationships

with intelligent interactions?

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Extend Your Analytics Capabilities

C

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Sense & Respond

Predict & Act

Raw Data Cleaned Data Standard Reports Ad Hoc Reports & OLAP Generic Predictive Analytics Predictive Modeling Optimization What happened?

Why did it happen?

What will happen?

What is the best that could happen?

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Predictive analysis encompasses a range of analytic techniques

… the exploration and analysis, by automatic or semi-automatic

means, of large quantities of data in order to discover meaningful

patterns and rules.”

Gordon Linoff and Michael Berry

Authors of “Data Mining Techniques”

“

… the process of discovering meaningful new correlations, patterns

and trends by sifting through large amounts of data stored in

repositories, using pattern recognition technologies as well as

statistical and mathematical techniques.”

Gartner Group

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Challenges

Forecasting

Key

Influencers

Trends

Anomalies

Relationships

How do historical sales, costs, key performance metrics, and so on,

translate to future performance? How do predicted results compare with goals?

What are the main influencers of customer satisfaction, customer churn, employee turnover, and so on, that impact success?

What are the trends:

historical / emerging, sudden step changes, unusual

numeric values that impact What are the correlations

in the data? What are the cross-sell and up-sell opportunities? What anomalies

might exist and conversely what groupings or clusters might exist for specific analysis?

Predictive Analytics

Examples

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Data mining and predictive have been around for decades.

But new market forces are changing the landscape and offering new opportunities…

Increased business

interest

Now that BI users know what happened, they are asking why and what’s likely to happen next Explosive demand from sales, marketing, and call center analyses… fraud, and government intelligence/security agencies

Increase

d data value (e.g., Big Data)

Exploding data volume Expanding data varieties

Increasing technology performance

Parallel processing, faster CPUs, and

in-memory technologies reduce time and cost of data processing

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Big data matters

Transformational business value from data

Drive Better Profit Margins New Strategies and Business Models Operational Efficiencies Business Value

Velocity

Volume

Variety

Mobile

CRM Data

Planning Opportunities

Transactions

Customer Sales Order Things Instant Messages Demand Inventory

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Database to Decision Predictive Analytics

In-database predictive and R integration

Intuitive predictive modeling

Advanced data visualization and easy to use exploration

Harnessing Powerful Big Data Analytics

Real-time on massive amounts of structured and unstructured data Complex questions answered in-memory, lightning fast

Deep Hadoop integration with built-in text analysis

SAP Predictive Analytics Vision

For Everyone in the Business

Seamlessly embedded in business user applications Extended into BI clients and reports

Insight into events instantly delivered to dashboards, alerts, and mobile devices

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Predictive Analysis - User Personas

SAP PA designer SAP HANA PAL & R IQ SAP PA visualization Embedding Predictive Analysis

Industry applications LOB applications BI client tools Number of users SAP PA wizard 5 / 20 Large number 50 / 100 500 / 5,000 User personas Business Analyst

Professional Data Analyst

Predictive Analysis process designer / author

Business Analyst / Interactive Consumer Application End User

• Information Consumer

• Interactive Consumer

All personas

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Agenda

The Predictive Analytics Landscape

Predictive Analytics with SAP HANA

Customers Benefit from Predictive Analytics with SAP HANA

Predictive Applications for SAP HANA

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Predictive Analytics with SAP HANA

Transforming the Future with Insight Today

Unleash the value of Big Data

through the power of SAP HANA

• Employ in-database predictive algorithms

• Access 3,500+ open-source algorithms

via R integration for SAP HANA

Intuitively design and visualize

complex predictive models

• SAP Predictive Analysis software

Bring predictive insight to everyone

in the business

• Embed within business applications

• Extend into BI and reports

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SAP HANA In-Memory Predictive Analytics

Predictive Analysis Library (PAL)

Native predictive algorithms

In-database processing for powerful and fast results

Quicker implementations

Support for K-Means, K-Nearest Neighbor, C4.5 Decision

Tree, Multiple Linear Regression, Apriori, ABC Classification,

Weighted Score Tables

R Integration for SAP HANA

Enables the use of the R open source environment (> 3,500

packages) in the context of the HANA in-memory database

R integration enabled via high performing parallelized

connection

R script is embedded within SAP HANA SQL Script

Combine the depth and power of in-memory analytics within SAP HANA with the

breadth of R to support a variety of advanced analytic and predictive scenarios

Y

X

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SAP HANA In-Memory Predictive Analytics

Predictive Analysis Library (PAL)

Clustering

K-Means

Classification

K-Nearest Neighbor C4.5 Decision Tree

Multiple Linear Regression

Association

Apriori

Classification

ABC Classification Weighted Score Tables

Association

Lite Apriori (A -> B)

Classification

Exponential / Geometric / Logistic / Natural Logarithmic Regression

CHAID Analysis

Time Series

Single / Double / Triple exponential smoothing

Preprocessing

Outlier Detection (Inter-Quartile Range)

SAP HANA SPS3

SAP HANA SPS4

The Predictive

Analysis Library

(PAL) is part of the

Business Function

Library

It resides in the

Calculation Engine

and consists of

functions executing

at the database

layer and is written

in C++

Additional native predictive analysis functions provide for deeper insights and

faster analytic implementations as well as results

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R Integration for SAP HANA

What is R?

R is a software environment for statistical

computing and graphics

Open Source statistical programming language

Over 3,500 add-on packages; ability to write your own

functions

Widely used for a variety of statistical methods

More algorithms and packages than SAS + SPSS + Statistica

Who’s using it?

Growing number of data analysts in industry, government,

consulting, and academia

Cross-industry use: high-tech, retail, manufacturing, CPG,

financial services , banking, telecom, etc.

Why do they use it?

Free, comprehensive, and many learn it at college/university

Offers rich library of statistical and graphical packages

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R Integration for SAP HANA

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R Integration for SAP HANA

Functionality Overview

R integration for SAP HANA enables the use of the R open source

environment in the context of the HANA in-memory database

Establishes a communication channel between HANA and R for fast data exchange

Improved data exchange mechanism supports transfer of intermediate database tables

directly into vector oriented data structures of R

Performance advantage over standard tuple-based SQL interfaces with no need for data

duplication on the R server

Supported by providing the R-operator as a custom operator in the calcModel of the

calculation engine

This allows the application user to embed R script within SQL script and submit entire query

to the HANA database

As the plan execution reaches R-node, a separate R runtime is invoked using Rserve and

input tables of R node passed to R process using improved data transfer mechanism

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Predictive Analytics Process in SAP HANA

Step1

Data Loading

Step 2

Data Pre-Processing

Step 4

Visualization

1. Understand the business and figure out the problems

2. Load the SAP or non-SAP

data into SAP HANA

1. Data selection 2. Data cleansing

3. Data transformation 1. Train Predictive Model

(clustering / classification / association / time series etc.)

1. Visualize the model for

better understanding

2. Store the model and

results in SAP HANA

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Agenda

The Predictive Analytics Landscape

Predictive Analytics with SAP HANA

Customers Benefit from Predictive Analytics with SAP HANA

Predictive Applications for SAP HANA

Demo

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Mitsui Knowledge Industry

Healthcare – Speed Research & Improve Patient Support

Business Challenges

Reduce delays and minimize the costs associated with new drug discovery by optimizing the process for genome analysis

Improve and speed decision making for hospitals which conduct cancer detection based on DNA sequence matching

Technical Implementation

Leveraged the combination of SAP HANA, R, and Hadoop to store, pre-process, compute, and analyze huge amounts of data Provide access to breadth of predictive analytics libraries

Benefits

For pharmaceutical companies, provide required new drugs on time and aid identification of “driver mutation” for new drug targets Able to provide a one stop service including genomic data

analysis of cancer patients to support personalized patient therapeutics

408,000x

faster than traditional disk-based systems in a technical PoC

216x

faster by reducing genome analysis from several days to only 20 minutes making real-time cancer/drug screening possible

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Cisco Systems, Inc.

High-Tech – Deliver Predictive Insight in Near Real-Time

The HANA platform at Cisco has been used to deliver near real-time insights to our execs, and the integration with R will allow us to combine the predictive algorithms in R with this near-real-time data from HANA. The net impact is that we will be able to take the capability which takes weeks and months to put together, and deliver just-in-time as the business is changing.

Business Challenges

Provide Cisco sales with real-time insights to make better decisions Better data delivery decisions to improve the business - for

optimization and to drive topline growth

Lack of understanding of underlying sales performance drivers and the seasonality of buying patterns

Technical Challenges

Unable to transform the results of statistical analysis into actionable insights

Benefits

Better respond to customers and deliver tangible business value Reduce time to transform information into insights and improvement in the quality of decision-making on those insights

Ultimately drive higher profitability and growth

5 seconds

Seasonality analysis with any selected filters including country, segments and sales levels

2 seconds

Cluster analysis across multiple quarters for a

combination of sales level and quarter to determine sales achievement level

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Bigpoint

Gaming Industry - Predictive Game Player Behavior Analysis

Business Challenges

Increase conversion rates from free paying player Increase the average revenue per paying player Decrease churn – keep paying players playing longer

Technical Challenges

Leverage real-time data processing in SAP HANA and

classification algorithms with R integration for SAP HANA to deliver personalized context-relevant offers to players

Analyze vast amounts of historical and transactional data to forecast player behavior patterns

Benefits

Real-time insights

Per player profitability analysis and increased understanding of player behavior

Increase data volume and processing capabilities to communicate personalized messages to players

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5,000

events per second loaded onto SAP HANA (not possible before)

10-30%

increase in revenue per year

Interactive

data analysis leading to improved design thinking and game planning

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Agenda

The Predictive Analytics Landscape

Predictive Analytics with SAP HANA

Customers Benefit from Predictive Analytics with SAP HANA

Predictive Applications for SAP HANA

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SAP HANA Predictive Ecosystem

SAP HANA Platform

Predictive Analysis Library

(PAL)

SAP HANA Studio

SAP and Custom Applications R Integration for SAP HANA Business Intelligence Clients

R

SAP Predictive Analysis

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SAP HANA – Hadoop Support in SAP Data Services 4.1

Extend the “Big Data” Ecosystem to SAP HANA

Files

Web & Others Databases

SAP HANA, Sybase IQ, other

Target Systems

SAP Data Services

SAP HANA can integrate with Hadoop via SAP Data Services 4.1

Ability to load and read large volumes of data into and out of SAP HANA from/to

Hadoop via SAP Data Services 4.1

Reading from and loading into Hadoop

Hive Support (table-like access to Hadoop data) Direct HSFS file support through PIG scripts

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Intuitively design complex predictive models

Visualize, discover, and share hidden insights

Unleash Big Data with SAP HANA’s power

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• Identify energy consumption pattern that can be used for Customer Segmentation • Smart meter data volume is

huge

Using SAP HANA + PAL

K-Means algorithm

Challenge

Solution

Results

• Clustering of smart meter data applying the k-means clustering to >20 million x 96-dimensional

vectors

• High performance clustering computation

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Customer Analytics

Customer Revenue Performance Management

Simulation and Business Advice

Perform what-if scenarios to see the impact of pricing and discount changes

What:

Combination of financial and sales data to

get visibility of profitability and margins of a customer, a customer deal or group

Margin visibility – decomposition of margin

to highlight areas of improvements

Comprehensive customer revenue analysis Call for action – take focus customers and

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Customer Analytics

Predictive Customer Segmentation & Targeting

Real-time simulation and segment building

More granular targeting leveraging predictive analytics

Improved alignment amongst Sales, Marketing and Product Development to focus on target Customers

What:

Segmentation on a wider and more granular

set of data not requiring SAP CRM

Tracking of successful implementation of

initiatives out of segmentation

All levels of sales can use segmentation

features to define own target customers to improve sales

Predictive segmentation by identifying

common characteristics within a given group

ALERTS

SEGMENTATION SIMULATE FEED SEARCH PERSONALIZE ADMINISTRATOR

?

CRPM

OVERVIEW SEGMENT

All customers with revenue greater than 55 milions Explore

1.503 Search Results: „All customers with revenue greater than 55 milions“

Customer Class A Save Query ATTRIBUTES Customer (0/6) Product (1/8) Type (2/5) Type 2 (0/15) Type 3 (1/45) S u b ty p e 3 .2 (4 ) Attribute 4 Attribute 5 Attribute 6 Attribute 7 Product Attribute 2 Attribute 3 Attribute 1 Customer Label 3 Label 4 Label 5 Status Label 1 Class Label 2 Group 4 Group 2 Group 3 Group 1 Type Group 5 Group 6 Type 5 Type 2 Type 3 Type 1 Type 4 Type 6 Subtype 2.5 Subtype 2. 2 Subtype 2.3 Subtype 2.1 Subtype 2.4 Subtype 3.5 Subtype 3.2 Subtype 3.3 Subtype 3.1 Subtype 3.4 Save Query ATTRIBUTES

Product Group (0/7) Sales Area (1/8)

Distribution Chain (2/5) DChain 2 (0/15) DChain3 (1/45) D C h a in 3 .2 (4 ) Sales Group Customer Attribute 6 Attribute 7 Sales Area Country Quarter Sales Group Product Group PGroup 5 PGroup 6 PGroup 7 PGroup 2 PGroup 3 PGroup 1 PGroup 4 Area 5 Area 2 Area 3 Distribution Chain Area 4 Area 6 Area 7 DChain5 DChain 2 DChain 3 Sales Org DChain 4 DChain6 DChain 2.5 DChain 2. 2 DChain 2.3 DChain 2.1 DChain 2.4 DChain 3.5 DChain 3.2 DChain 3.3 DChain 3.1 DChain 3.4

Customer Class Revenue Margin Purchasing Bu... Country Region

Customer N... A $ 25.534...20 % $ 555.555.999... USA Wash...

All Manufacture Customers 30 %

10% 20%

0

50,000 M Class A Class B Class C

S o m e M e a n in g fu l L a b e l

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Performance and Insight Optimization Services

Enabling complex use cases with SAP HANA

Back end

Sophisticated aggregation and cleansing algorithms High volume industry specific data relationship algorithms

Industry-specific predictive modeling

Proprietary models for retail, banking, utilities, manufacturing, and beyond

Industry-specific optimization

Algorithms and processes

Examples of innovative

business solutions advanced by

SAP HANA:

Tax Compliance and

discovery engine for public

sector

Affinity insight and

forecasting for retail

High performance

compliance engine for

chemical companies

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Startups Powered by SAP HANA

Predictive and Analytics / Security

AlertEnterprise Security Convergence solutions combine Situational Intelligence with Command and Control capabilities for Critical Infrastructure Protection.

Geospatial & Visual

Analytics

Next generation geospatial and visual analytics solutions transform massive volumes of real-time disparate data into intuitive visual displays. Space-Time Insight’s situational intelligence software helps visualize operations with absolute clarity, analyze the cause of a problem and

determine how to prevent another occurrence, and act instantly to address any situation.

Predictive and Analytics / Financial

The Taulia Invoicement® Suite includes a Dynamic Discounting module and self-service vendor portal. Together, these tools reduce Accounts Payable support overhead, improve supplier relations and generate significant cash savings for corporations.

Social and Predictive Analytics

From campaigns to communities, #NextPrinciples empowers anyone to monitor, manage and act on social media interactions across channels.

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Agenda

The Predictive Analytics Landscape

Predictive Analytics with SAP HANA

Customers Benefit from Predictive Analytics with SAP HANA

Predictive Applications for SAP HANA

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Companies can no longer focus solely on delivering the

best product or service. To succeed, they must:

• Uncover hidden customer / employee / vendor /

partner trends and insights

• Anticipate behavior and take proactive action

• Empower your team with intelligent next steps to

exceed customer expectations

• Create new offers to increase market share and

profitability

• Develop and execute a customer-centric strategy

• Target the right offers to the right customers through

the best channels at the most opportune time

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• New market forces are changing the landscape and

offering new opportunities

• Predictive analysis can be for everyone in the

business

• SAP HANA is the cornerstone of SAP’s vision for

predictive analytics

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Thank you for participating.

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mobile application.

SESSION CODE: 0212

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