Accelerating Big Data & Analytics Innovations through Public – Private Partnerships: Experiences and Results

Accelerating Big Data & Analytics Innovations through Public – Private Partnerships: Experiences and Results

Prof. Dr. Alexander Mädche, University of MannheimDr. Hendrik Meth, BorgWarner IT Services Europa GmbH

Walldorf, September 11th 2015

SAP University Alliance EMEA Conference

Agenda

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Agenda

1 Public Private Partnerships for Big Data Innovations (Mädche)

2 Innovation Prototyping: BW on HANA Performance Analysis (Meth)

3 Experiences & Lessons Learned (Mädche)

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Different Types of Big Data & Analytics Innovations

SAP HANA Platform for

Big Data

Extend Existing Transactional & Analytical Stack of SAP

Develop Innovative Intelligent Applications

Other Big Data (Analytics)

Technologies

Existing Transactional & Analytical Stack (ERP, DWH, …)

Custom DevelopAdd-on

RECAP SAP UA EMEA

CONFERENCE 2014, Berlin

Public – Private Partnerships in the context of Big Data Innovations have huge potentials: Universities get access to real-world problems and data, private organizations establish networks and get access to state-of-the-art knowledge.

Public – Private Partnerships have the potential to enable and establish new forms of networked innovations.

Public – Private Partnership (PPP) for Big Data & Analytics Innovations

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Public Private

Technology Providers

Consulting Service Providers

Corporate UsersBig Data Innovation Lab

Big Data Innovation Center

Extending and Building PPP Innovation Networks: The SAP Big Data Innovation Lab

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In the last year we have extended and accelerated the innovation network with a consulting service provider and first corporate users:

Public Private

Technology Providers

Consulting Service Providers

Corporate UsersBig Data Innovation Lab

Big Data Innovation Center

• We established a cooperation with a well-known consulting service provider.

• We have carried out first innovation projects with corporate users. Results of a finalized innovation project in cooperation with BorgWarner will be presented.

Cooperation Concept with Consulting Service Provider

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• Leverage Big Data & Analytics infrastructures to extend the existing SAP stack as well as to deliver analytics pilot innovation applications with real-world data in cooperation with consulting service provider clients.

• Execute dedicated research projects in cooperation with consulting service provider and its clients and deliver joint publications in the form of research and white papers

Research &

Innovation

• Embed „Analytics Challenge“ into M.Sc. lecture on Business Intelligence

• Run joint bachelor / master thesis projectsEducation

Agenda

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Agenda

1 Public Private Partnerships for Big Data Innovations (Mädche)

2 Innovation Prototyping: BW on HANA Performance Analysis (Meth)

3 Experiences & Lessons Learned (Mädche)

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Introduction

• BorgWarner is one of the leading automotive suppliers in the world.

• Engine and Drivetrain Systems

• Worldwide operations and customer base

• Large SAP Business Warehouse 7.01 implementation, following layered scalable architecture (LSA), e.g. see Sales Architecture:

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• Challenges:

- Data Loading performance

- Reporting performance

Innovation Project: Setup-1

• Main research question behind the study: Can the potential performance improvements of SAP HANA be realized in a data and modelling and reporting setup comparable to BorgWarner’s system landscape ?

• Compare three variants with regards to data loading / reporting performance - Model-A: SAP BW 7.3 on relational database using LSA modeling approach- Model-B: SAP BW 7.3 on SAP HANA database using LSA modeling approach- Model-C: SAP BW 7.3 on SAP HANA database leveraging HANA-optimized

modelling

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Innovation Project: Setup-2

• Create a data model similar to our existing environment

• Utilize real-world data from BorgWarner along three cases:

- Case A: 1 million records

- Case B: 2 million records

- Case C: 3.5 million records.

• Create different types of representative queries (for reporting)

• Run 5 different iterations

• Provide infrastructures in Big Data Innovation Center Magdeburg (BW on HANA / BW on relational database) and run evaluation in controlled lab environment.

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Innovation Project: Selected Results*:

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Data Loading Performance

Reporting Performance (simple / mid-complex queries):

* for Case C – 3.5 million data sets):

Agenda

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Agenda

1 Public Private Partnerships for Big Data Innovations (Mädche)

2 Innovation Prototyping: BW on HANA Performance Analysis (Meth)

3 Experiences & Lessons Learned (Mädche)

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Experiences & Lessons Learned

• Private-Public Partnerships leveraging a partner network covering different roles and competencies help to drive big data innovations forward.

• Various types of legal, security and compliance aspects remain the key inhibitor for running big data innovation projects => Template contracts, tool support (e.g. for data randomization), etc. is required

• Big Data Innovation extension scenarios may require complex system landscapes (HANA, ABAP Stack, BW, …); costs tend to become higher than expected

• Professional installation / delivery support from Big Data Innovation Center is really required and very helpful.

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Prof. Dr. Alexander MädcheUniversity of Mannheim | Business School | Institute for Enterprise Systems (InES)L 15, 1-6 | 4th floor | 68131 Mannheim | GermanyPhone +49 621 181-3606 | Fax +49 621 [email protected] | http://eris.bwl.uni-mannheim.de http://ines.uni-mannheim.de

Thank you for your attention!

Dr. Hendrik MethManager Business Warehouse Competence CenterBorgWarner IT Services Europe GmbH, Marnheimer Straße 85/8767292 Kirchheimbolanden / GermanyTel.: +49 63 52-403-5243 [email protected]