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SAP Academic Conference Americas 2013Analytics: From Big Data to Insight
Bjarne Berg, Lenoir-Rhyne UniversityAdrian Gardiner, Georgia Southern UniversityFebruary 2013
Influence Next-Gen Leaders
© 2013 SAP AG. All rights reserved. 2
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
© 2013 SAP AG. All rights reserved. 3
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
© 2013 SAP AG. All rights reserved. 5
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.
© 2013 SAP AG. All rights reserved. 6
Google Trends
Key term: Analytics
Key term: Big Data
© 2013 SAP AG. All rights reserved. 7
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
© 2013 SAP AG. All rights reserved. 8
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?
© 2013 SAP AG. All rights reserved. 9
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
© 2013 SAP AG. All rights reserved. 11
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
© 2013 SAP AG. All rights reserved. 12
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
© 2013 SAP AG. All rights reserved. 14
SAP Analytics Software Stacksimplified
© 2013 SAP AG. All rights reserved. 15
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
© 2013 SAP AG. All rights reserved. 17
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
© 2013 SAP AG. All rights reserved. 18
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
© 2013 SAP AG. All rights reserved. 20
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
© 2013 SAP AG. All rights reserved. 21
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 ([email protected])
Teaching AnalyticsSAP University Alliances’ curriculum in: SAP NetWeaver Business Warehouse,SAP Crystal Reports, SAP Crystal Dashboard Design, & SAP BusinessObjects 4.0
© 2013 SAP AG. All rights reserved. 24
Teaching Data Foundation with SAP BW
© 2013 SAP AG. All rights reserved. 25
Teaching Data Foundation with SAP BW
© 2013 SAP AG. All rights reserved. 26
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
© 2013 SAP AG. All rights reserved. 27
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
© 2013 SAP AG. All rights reserved. 28
Teaching the Information Access Layer
© 2013 SAP AG. All rights reserved. 29
Information Access
© 2013 SAP AG. All rights reserved. 30
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.
© 2013 SAP AG. All rights reserved. 31
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
© 2013 SAP AG. All rights reserved. 32
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.
© 2013 SAP AG. All rights reserved. 33
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
© 2013 SAP AG. All rights reserved. 34
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
© 2013 SAP AG. All rights reserved. 36
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.
© 2013 SAP AG. All rights reserved. 37
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
© 2013 SAP AG. All rights reserved. 38
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
© 2013 SAP AG. All rights reserved. 40
Different Tools for Different User Groups
Pick one or two tools to teach first. Keep it simple
Opinion of the authors
© 2013 SAP AG. All rights reserved. 41
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 [email protected]
Adrian GardinerAssociate Professor, Information [email protected]