SAP HANA Cloud Platform predictive services · 2019-11-12 · © 2015 SAP SE or an SAP affiliate...

SAP HANA Cloud Platform

predictive servicesOctober 15, 2015 Public

© 2015 SAP SE or an SAP affiliate company. All rights reserved. 2Public

Agenda

1. Exploratory Analytics – Why, what, who

2. An example of the process to use a predictive service

3. List of SAP HANA Cloud Platform predictive services and architecture

4. Developing with predictive services – Key Influencers workflow

5. The other services


What is SAP HANA Cloud Platform predictive services?

A collection of ready-to-be-integrated web

services that delivers predictive analytics

insights

Highly specific web services that respond

to specific business needs

1 service returns 1 type of insight. All the data

mining process is packaged inside the service and is

hidden from the user.

Services are available on HCP to allow any

existing or new applications on HCP to

embed predictive analytics features.

Simple to use

• SAP HANA Cloud Platform predictive services are

based on APL(*)

• 1 call 1 business need

• Usage of APL is embedded into services

Simple to exploit

• Results are understandable


Advantages to use SAP HANA Cloud Platform predictive

services?

Lower TCO

REST Web Services easy to understand and to use

Reduced development cycle. Data analysis possible with a single service call. You don’t

have to code it yourself from scratch.

Operational Support - SAP HANA Cloud Platform predictive services

• Provide Synchronous or Asynchronous(*) model execution.

• Take advantage of the infrastructure and services of the underlying HANA Cloud platform.

Flexible Data Access

• Ability to upload new datasets,

• Execute predictive models on data created or uploaded by other applications and

services, or on dataset streams.


Who will use SAP HANA Cloud Platform predictive

services?

Business Consultant

Person who expresses the business needs

Doesn’t need to have a lot of data mining skills

In order to choose the most appropriate services, needs to understand : what drives each

service and what is the value generated by each service

1. What is the objective of each service and what kind of business question each service

answers

2. What kind of data is necessary

3. How to interpret and use the results

4. What is the value/profit created for his customers?

Developer

• Doesn’t need to have data mining skills

• Needs to have programming experience with Web services


Which kind of customers can use SAP HANA Cloud

Platform predictive services?

SAP Internal

• Uses SAP applications and needs improvements and/or new features (examples: finance

to detect potential fraud, CRM to detect churn, HR to understand and analyze results of

survey, …)

• SAP runs SAP

SAP Partners

Build custom HCP applications for their customers

Customers

• Use SAP HANA Cloud Platform predictive services to generate answers and solutions to

their specific problems.


Agenda



3. List of SAP HANA Cloud Platform predictive services and

architecture




An example of the process to use a SAP HANA Cloud

Platform predictive service

Lucy is a business analyst. She would like

to boost the revenues of X Travel Agency.

.

.

Lucy asks Dave to build an Exploratory

Analytics app. She would like an app that

will provide her various kinds of insights

that she could use to increase revenues

on travel bookings.

Dave develops the Exploratory Analytics app

using the HCP platform. Among other kinds of

services, he integrates the Key Influencers

Service to identify variables which

influence high value travel bookings.

Dave shows the first version of the app to Lucy.

She comes up with various improvements to

make and Dave integrates these changes

before redeploying the app. They continue

iterating on it until Lucy is satisfied.

After a week, the Exploratory Analytics App is

operational. The insights provided by the app are a

great help for Lucy to come up with plans to

increase revenues.


Agenda




architecture




Description of Predictive Services

Service Description

Dataset Provide a series of functions to manage datasets

• Register/unregister a dataset to the SAP HANA database schema for the

application

• Retrieve dataset and variable information

Forecast Predict next values of a time series from a reference date.

Key Influencers Return the variables which have an influence on a specified target.

• Have a better understanding of the profile of the target population

• Identify the drivers of success and learn how to improve performance

Outliers Identify the odd profiles of a dataset whose target indicator is significantly different

from what is expected

Scoring Equation Build a model to explain a target and exports it as a scoring equation which will be

applied in order to get a value of the target variable for new cases.


Architecture

HCP Services (admin, monitoring,

authorization, authentication,

…)

HCP

HCP account of customer

JDBC

Exploratory

Analytics

Applications

Key

Influencers

Scoring

EquationForecast

Dataset

ServicesOutliers

SAP HANA Cloud Platform predictive services

HANA Instance

Data Meta-Data

APL


Agenda




architecture




Develop with predictive services

Services are deployed on each HCP customer’ account.

To start the development of a HCP application, refer to the HCP developer

documentation.

Services are implemented using REST (Representational State Transfer) architecture

style:

• Web services are easy to leverage by most tools.

• Learning curve to use REST services is reduced. Developers prefer it and this saves time, which

saves money.

• REST is designed for use over Internet, use small message.

Implement the service calls either in synchronous or asynchronous mode

Mode Decription

Synchronous 1. Call the service with dataset ID and other parameters

POST /api/analytics/keyinfluencer/sync

Asynchronous 1. Create the job and retrieve its ID.

POST /api/analytics/keyinfluencer

2. Retrieve the job status using its ID.

GET /api/analytics/keyinfluencer/<jobID>/status

3. Retrieve the results in JSON format.

GET /api/analytics/keyinfluencer/<jobID>

4. Delete the job

DELETE /api/analytics/keyinfluencer/<jobID>

https://help.hana.ondemand.com/help/frameset.htm?3b0edd0b6aec4a68b8007e4f05162397.html


Key Influencers Predictive Service

Description

Analyze a dataset to identify the variables that have an influence on a specified target.

Services features

Identify the key influencers of a specified target

Get detailed information on how a variable influences the target

Show indicators on the quality of the results

Possibility of adjustment on the training process (variables’ descriptions, variables’ roles)

Applications Example

Have a better understanding of the profile of the population he targets

Identify the drivers of success and how to improve performances

Have leads on potential causes of a targeted event


Key Influencers workflow

Register a dataset

Input: a CSV file uploaded into HANA table or

a HANA table

Output: a dataset ID

POST /api/analytics/dataset/sync"hanaURL": "C4PA_SAMPLES/CENSUS_ORDERED"

Results"id": 156,

"name": "CENSUS_ORDERED",

"rows_number": 48842,

"columns_number": 16,

"variables": [

{

"rank": 1,

"name": "age",

"storage": "integer",

"value": "continuous"

},

…

{

"rank": 15,

"name": "class",

"storage": "integer",

"value": "nominal"

}



Register a dataset


a HANA table


Create key influencer job

Inputs: Dataset ID and name of target variable

Output: A job ID and a status

POST /api/analytics/keyinfluencer"datasetID": 156,

"targetColumn": "class"

Results"ID": 1353,

"status": "PROCESSING",

"type": "key_influencer",

"input": numberOfInfluencers :null,

targetKey :null,

autoSelection :null,

datasetID :156,

targetColumn :class,

skippedVariables :null,

weightVariable :null,

variableDescription :null



Register a dataset


a HANA table





Check status of the job

Input: Job ID

Output: Status of the job: Processing, Failed,

Successful

GET /api/analytics/keyinfluencer/1353/status

Results"ID": 1353,

"status": “PROCESSING",

"type": "key_influencer"

After a while"ID": 1353,

"status": "SUCCESSFUL",

"type": "key_influencer"



Register a dataset


a HANA table






Input: Job ID

Output: Status of the job: Processing, Failed,

Successful

Retrieve the key influencers

Input: Job ID

Output: Model performance indicators and key

influencers

GET /api/analytics/keyinfluencer/1353

ResultsmodelPerformance:

"predictivePower": 0.8091,

"predictionConfidence": 0.9952,

"qualityRating": 5,

"confidenceIndicator": 1,

Influencers:

"contribution": 0.24391355161624884,

"variable": "marital-status",

"groups": [

"group": "{Divorced}",

"significance": -0.10312004005736641,

"normalProfit": -0.13866835617242768,

"frequency": 0.13545532008465958,

"targetMean": 0.10085227272727272,

"groupDefinition": {

"categories": ["Divorced"],

"higherBound": null,

"higherBoundIncluded": null,

"lowerBound": null,

"lowerBoundIncluded": null,

"kxmissingIncluded": 0

ConfidenceIndicator is computed from the predictionConfidence:

If predictionConfidence >= 0,95 Then 1

Else 0

PredictivePower < 0,2 < 0,3 < 0,5 < 0,6 < 0,8 >= 0,8

qualityRating 0 1 2 3 4 5

KI

KR



Register a dataset


a HANA table






Input: Job ID

Output: Status of job: Processing, Failed, Successful

Retrieve the key influencers

Input: Job ID

Output: Model performance indicators and key

influencers

Delete the jobs and unregistrer dataset

Input: Job ID or dataset ID

Output: The HTTP status of the query is 200 other it is

400 if it fails.

For the Key Influencer job

DELETE /api/analytics/keyinfluencer/1353

Result:

HTTP status: 200

For the dataset

DELETE /api/analytics/dataset/156

Result:

HTTP status: 200


Agenda



3. List of SAP HANA Cloud Platform predictive services and architecture




Dataset Service

Provide a list of features to manage datasets to be used by the SAP HANA Cloud

Platform predictive services to get insights.

Register a dataset in the application database schema

Retrieve registered dataset information

Get dataset Information

Get variables information

Unregister a dataset


Forecast Cloud Service

Description

Analyze a time series and predicts its future next values.

The prediction is based on the trend, periodicities and fluctuations detected in the time

series along with context information represented by extra-predictive variables when

available.

The granularity of the predictions is the same as the granularity used in the dataset.

Service features

Analyze a time series and generate forecasts based on identified patterns

Get confidence intervals computed for each forecast

Possibility to define the analysis and forecasts periods

Provide indicators on the reliability of the results

Applications examples

Estimate how much visitors to expect in the next days

Estimate how many products to order depending of expected consumption


Outliers Cloud Service

Description:

Detect the outliers contained in a dataset, that is, the odd profiles whose target indicator is

significantly different from what would be expected.

Services features:

Identification of outliers contained in a dataset

Reasons explaining why an outlier is odd

Outliers are sorted from most interesting to less interesting

Shows performance indicators on the quality of the model which identified the outliers

Possibility of adjustments of the modeling process (variable descriptions, variables roles)

Application Example

• Identification of odd profiles, potential frauds, point of interests


Scoring Equation Service

Description

Build a predictive model from a dataset and export its scoring equation for later use outside of

the cloud services

Services features

Build a predictive model and export its scoring equation

Get indicators on the performance of the predictive model

Possibility of adjustment on the training process (variables’ descriptions, variables’ roles)

Available export format : SQL HANA, CSV

Application Examples :

Integrate the predictive model inside an application

Use the predictive model as many times as desired

Apply the predictive model on new data as soon as they come

© 2015 SAP SE or an SAP affiliate company. All rights reserved.

Thank you

Contact information:

Idea Place : https://ideas.sap.com/PredictiveAnalytics

SCN Predictive Analytics

Starter Kit page for SAP HANA Cloud Platform predictive services

HCP Web site

https://ideas.sap.com/PredictiveAnalytics

http://scn.sap.com/community/predictive-analytics

http://scn.sap.com/docs/DOC-68204

http://hcp.sap.com/index.html


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