SAP Academic Conference Americas 2013 Analytics: From Big Data to Insight Bjarne Berg, Lenoir-Rhyne...

SAP Academic Conference Americas 2013Analytics: From Big Data to Insight

Bjarne Berg, Lenoir-Rhyne UniversityAdrian Gardiner, Georgia Southern UniversityFebruary 2013

Influence Next-Gen Leaders

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Agenda

A Tipping Point? The rise of big data and nearly infinite computing power

Implications for Business Education Why educators need to get on board

SAP and Analytics Outlining SAP’s analytic software stack

Teaching Using SAP HANA SAP HANA will be a ‘game changer’ for business computing SAP University Alliances’ curriculum in SAP HANA

Teaching Analytics SAP University Alliances’ curriculum in: SAP NetWeaver Business Warehouse,

SAP Crystal Reports, SAP Crystal Dashboard Design, & SAP BusinessObjects 4.0

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Innovation Starts Here

SAP University Alliances provides curriculum aligned with SAP’s Innovation Platform…including Analytics, Mobile, and SAP HANA…so students are

prepared with skills needed by industry.

Powered by SAP HANA

MobileAnalytics CloudDatabase & Technology

Applications

SAP HANA Powers Innovation Across SAP’s Solutions

A Tipping Point?The rise of big data and nearly infinite computing power

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A Tipping Point?

2012: a tipping point in business technology?

Gartner: “Nearly there or have now arrived”

Analytic insight and computing power are nearly infinite and cost-effectively scalable.

Big data and global scale computing at small prices. Gartner's 2012 Hype Cycle for Emerging Technologies

Applications powered by SAP HANA

Recent SAP HANA benchmark: 100 billion records analyzed in 300ms.

SAP Business Suite powered by SAP HANA.

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Google Trends

Key term: Analytics

Key term: Big Data

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Big Data

The amount of business data is increasing exponentially. We are entering the age of ‘big data.’ It has been estimated that 90% of all data is less than two years old. IBM 2012: Bringing Big Data to the Enterprise

Some foresee a ‘revolution’ in management. Harvard Business Review, Oct. 2012: ‘Big Data: The

Management Revolution’

Micro-case: Social media Klout publishes measures of online influence. Analyzes 1 - 12 billion data points daily.

October 2012

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Analytics

Discovery and communication of meaningful patterns in data.

Applied to business data, to describe, predict, and improve business performance.

Analytic applications often favor data visualization to communicate insight.

Intelligent data

Behavioral data, sensor data, transactional data, market research, …

Questions (e.g., marketing):

Who are my core customers?

What drives their behavior?

Can I predict change?

Can I segment?

What has led up to this point?

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What is Holding us Back?

Disk speed is growing slower than all other hardware components, while the need for speed is increasing

Implications for Business EducationWhy educators need to get on board

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Implications for Business Education

“The United States alone could, by 2018, face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.” McKinsey & Co., 2011

“If you are looking for a career where your services will be in high demand, you should find something where you provide a scarce, complementary service to something that is getting ubiquitous and cheap. So what’s getting ubiquitous and cheap? Data. And what is complementary to data? Analysis. So my recommendation is to take lots of courses about how to manipulate and analyze data: databases, machine learning, econometrics, statistics, visualization, and so on.” Hal Varian, Chief Economist at Google and emeritus professor at the University of

California, Berkeley

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Implications for Business Education

Departments are changing their names

e.g. University of Sydney’s Dept. of Business Analytics (formerly: Operations Management and Econometrics).

Innovative degree programs are being launched

e.g., MS in Predictive Analytics (Northwestern University); MS in Analytics (NCSU)

“Now nobody has a data-science department; in 30 years every school on the planet will have one.”• Pat Gelsinger, CEO, EMC Corp., 2012

Something big indeed is going on!

SAP and AnalyticsOutlining SAP’s analytic software stack

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SAP Analytics Software Stacksimplified

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SAP Analytics Software Stack

Data Foundation Layer

Data provisioning

Information Access Layer

Supporting end-user analysis, modeling and decision making

Tools for generating & communicating insight

Teaching Using SAP HANASAP HANA will be a ‘game changer’ for business computing

SAP University Alliances’ curriculum in SAP HANA

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Teaching Using SAP HANA

We are in ramp-up mode of the SAP HANA curriculum, and had a workshop with 20 professors this fall as part of the first course offerings.

Today, we have material available for exercises involving data loading, table creation, building views and reporting in SAP HANA.

These are step-by-step instructions that students can complete in a guided manner.

Professors can quickly learn the material by doing the exercises themselves, or by attending the SAP HANA workshop tomorrow

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Teaching Focus for SAP HANA

SAP HANA can be taught from many perspectives:Analytics (Business Intelligence) Predictive modeling, data mining, data visualization, reporting, analysis, enterprise

performance management, scorecarding, benchmarking, dashboards etc.

Data Warehousing Dimensional modeling, ETL, data cleansing, data architecture, administration.

Technical and Database design May include as part of a database class to learn how to model and organize data in-

memory (row and column stores), creating indexes, views and loading data.

Or simply as a part of a business, CS or IS course.

Professors and students are encouraged to explore

learning resources at saphana.com

http://www.saphana.com/community/resources/hana-academy

SAPHANA.com

Also:

• Use Cases• Test

Drive/Demos• More on

HANA’s architecture

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Quick Demo of a SAP University Alliances’ SAP HANA Exercise for Students

In this short 4 min. demonstration, we show how a student can complete one of the SAP HANA exercises

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Demo of Analytics on SAP HANA – 780 million rows

In this short 5 min. demonstration, we show 3 dashboard examples running on SAP HANA

HANA Textbook Resources

In Memory Data Management: Technology and Applications – Hasso Plattner

SAP HANA Essentials – Jeffrey Word

SAP HANA: An Introduction - Bjarne Berg & Penny Silvia For desk copies: SAP Press – Jon Kent (jon.kent@sap-press.com)

Teaching AnalyticsSAP University Alliances’ curriculum in: SAP NetWeaver Business Warehouse,SAP Crystal Reports, SAP Crystal Dashboard Design, & SAP BusinessObjects 4.0

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Teaching Data Foundation with SAP BW

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Teaching Data Foundation with SAP BW

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The Value of Learning SAP NetWeaver Business Warehouse

Curriculum promotes understanding of:

System aspects of data foundation• Architecture: data flow into, within, and out of the data warehouse; ETL

The need for data warehousing: • Vis-à-vis SAP ERP’s reporting capabilities

Data for decision making usually comes from many sources

Importance of data quality & data transformation

Data modeling

OLAP

Role of metadata

Query design: BEx Query Designer

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Teaching Experiences: SAP NetWeaver Business Warehouse

SAP University Alliances’ curriculum is mature

SAP NetWeaver Business Warehouse can be technical

Ideally attend summer workshop

Target group: more technical students – e.g., IS, CS

Students ideally have completed a course in SAP ERP

Tight integration of data/metadata between SAP ERP and SAP BW

Database knowledge not absolutely necessary

But may wish to spend time on understanding OLAP concepts – star schema

Never actually see database (BW provides a layer of abstraction over database technology)

SAP NetWeaver Business Warehouse has data mining functionality

See ‘Analytics Applications and Global Bike, Inc.’ workshop

Predictive Analysis may be coming shortly

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Teaching the Information Access Layer

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Information Access

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Different Tools for Different User Groups

Crystal ReportsCrystal Reports

GuidedInteractive Experience, ResponsivenessLimited

Professionally Informed

Technically Capable

InformationConsumers

Executives & Managers

Business Analysts

Targ

et g

roup

Source: Kramer, R. (2011). SAP Business Intelligence.

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SAP Crystal Reports

Sophisticated report formatting

Pixel perfect reports

Templates and wizards speed up report creation

Secure, large scale distribution of reports

Connectivity to any data source

Teaching:

Enterprise reporting

Understanding links to data foundation

Encourages power-user DIY approach

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Different Tools for Different User Groups

Crystal ReportsCrystal Reports

Guided

Dashboards &

Visual Intelligence

Dashboards &

Visual Intelligence

Interactive Experience, ResponsivenessLimited

Professionally Informed

Technically Capable

InformationConsumers

Executives & Managers

Business Analysts

Targ

et g

roup

Source: Kramer, R. (2011). SAP Business Intelligence.

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SAP Crystal Dashboard Design

Personalised Flash-based dashboards

Pre-built components, skins, maps, charts, gauges, and selectors

Empower business users with interactive information

Teaching:

Eye-candy for students: leads to broader discussion of visualization

Monitor KPIs, metrics & exceptions

Powerful “what if” analysis

Ability to drill down

Understanding linkage to data foundation

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Different Tools for Different User Groups

Web Intelligence

Web Intelligence

Crystal ReportsCrystal Reports

Guided

Dashboards &

Visual Intelligence

Dashboards &

Visual Intelligence

Interactive Experience, ResponsivenessLimited

Professionally Informed

Technically Capable

InformationConsumers

Executives & Managers

Business Analysts

Targ

et g

roup

Source: Kramer, R. (2011). SAP Business Intelligence.

© 2013 SAP AG. All rights reserved. 35

SAP BusinessObjects Web Intelligence

Self service analysis and reporting

Flexible formatted reports with built-in analysis features

Aimed at business users

Report designers with limited technical expertise

Interactive report creation

Connectivity to any data source

Universe design

Teaching:

Answering ad-hoc questions

Role of semantic universes

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Different Tools for Different User Groups

Web Intelligence

Web Intelligence

Crystal ReportsCrystal Reports

Guided

Dashboards &

Visual Intelligence

Dashboards &

Visual Intelligence

Interactive Experience, ResponsivenessLimited

Professionally Informed

Technically Capable

InformationConsumers

Executives & Managers

Business Analysts

Analysis(BEx)

Analysis(BEx)

Targ

et g

roup

Source: Kramer, R. (2011). SAP Business Intelligence.

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Analysis - OLAP/Office (Excel, Powerpoint and Web)

Explore multi-dimensional data sets & drill down into details

Comprehensive range of business and time calculations

Visualization, exception highlighting

Teaching:

Heavily integrated with SAP BW & Query Designer (teach together)

Replacing older BEx

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Different Tools for Different User Groups

Web Intelligence

Web Intelligence

ExplorerExplorerCrystal ReportsCrystal Reports

Guided

Dashboards &

Visual Intelligence

Dashboards &

Visual Intelligence

Interactive Experience, ResponsivenessLimited

Professionally Informed

Technically Capable

InformationConsumers

Executives & Managers

Business Analysts

Analysis(BEx)

Analysis(BEx)

Targ

et g

roup

Source: Kramer, R. (2011). SAP Business Intelligence.

© 2013 SAP AG. All rights reserved. 39

SAP BusinessObjects Explorer

Search and navigation tool for casual users to access business data

About quickly finding an answer to a pressing question, rather than generating intricate multi-dimensional charts

Search, explore and visualise large data volumes via BWA / SAP HANA

Guided analysis and smart visualisations

Limited training required

US Government is using to improve transparency • e.g., Recovery.gov

Teaching:

Dimensionality

Links to data foundation

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Different Tools for Different User Groups

Pick one or two tools to teach first. Keep it simple

Opinion of the authors

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SAP HANA – What does it look like?

The SAP HANA system is hosted and your University does not need to maintain HANA hardware.

Thank You!

Contact information:

Bjarne BergAssociate Professor, Computer Sciencebergb@lr.edu828-328-7258

Adrian GardinerAssociate Professor, Information Systemsagardine@georgiasouthern.edu912-4787479