Slides from BrightTALK webinar; listen here: http://bit.ly/1rpVkov Understand how popular open source and vendor provided technologies integrate well, all making key contributions to a successful big data technology. But more important than technology is the business goals you define and aim to achieve. - See many examples in this deck and online presentation. Lastly, how do you bridge the digital implementation gap between in-house capabilities and the market demands driving endless new technologies. - How can you test drive and prototype without owning and committing to all these new technologies? Listen to the full webcast to find out how: http://bit.ly/1rpVkov

1. Swen Conrad
CEO, Ocean9
June 8, 2016
The Big Data decision path
incorporating SAP landscapes –
A process driven by business
needs

2. • Love technology that enables business results and enjoy
building a bridge from technology to business
• Focus on big data, cloud, IT management and SAP
• Passionate about
– SAP HANA and big data simplification, automation and operation
– Customer success
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 2
My experiences

3. Big Data technology for real-time processing
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 3
What is SAP HANA?
Diagram source: SAP
• Columnar in-memory
database for OLTP and OLAP,
fully ACID compliant
• Extreme high-performance
due to data residing in RAM
• Out of the box integration
with Hadoop and Spark
(HANA Vora)

4. Out of the box integration of Spark and SAP HANA
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 4
SAP HANA Vora
• SAP HANA
Smart Data Access for
Hadoop
• SAP HANA Vora
In-memory query
engine to extend
Spark execution
framework
Source: http://www.slideshare.net/SAPTechnology/spark-usage-in-enterprise-business-operations?

5. Most companies owning/using several Big Data
solutions
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Do Hadoop, Spark & HANA fit together?
Apache Projects
Hadoop
• Low cost, highly distributed storage
and processing – very large datasets
• Clusters build on commodity
hardware
• Excellent price/performance ratio
Spark
• Hadoop related project
• Many data sources
• 10 – 100x faster than Map Reduce
+
SAP Big Data
SAP HANA
• Extreme high performance across
many use cases enabling real-time
business
• Certified infrastructure only
• Optimized for SAP use cases
SAP HANA Vora
• In-memory query engine for Spark
execution framework
• Integrates corporate big data
with transactional ERP data
• Seamless big data tiering
between HANA and Hadoop
• Enriched analytics in distributed
clusters

6. Optimize or Innovate? – Business reqs drive the
choice
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Two groups of Big Data patterns
• Targeted operational data marts
• Data warehouse optimization
• 360 degree customer view
• Real-time offering management
• Smart store, smart arena, smart
everything
• IoT
Business Innovation
Optimize Existing Process

7. Big Data Use Cases
What if … ?
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 7

8. From logistics operations to strategy: Many use cases!
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Logistics and transportation
• Sensor based predictive
maintenance
• Route optimization
– Scheduling
– Real-time updates
– Crowd sourced delivery
• Strategy & operational
planning
• New business models
– Market intelligence for 3rd parties
– Address verification
– Environmental intelligence
Source: DHL

9. Smart Arena … smart everything
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 9
San Francisco 49ers
• A next generation fan experience
– 360 degree view of fan
– Location awareness
– Highly mobile
• Other sports related big data use cases
– Live on field data collection
– Globalization of home town teams
• Other consumer business
– Smart stores
– Mobile assistants … and more

10. Transportation-as-a-Service
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 10
Automotive industry
• Industry upset by new entrants
• Entirely new business models
– Self driving
– Car and ride sharing
– Service upsell within a digitized automobile
• What is the right Big Data
technology?

11. Use case drives
technology choice!
What drives
implementation speed and
success?
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 11

12. Cloud and X-as-a-Service key to overcoming gap!
• New kinds of services
with rapid innovation
• Fast prototyping
– Try before you buy
– Pay-as-you go
• Cloud elasticity for usage
based services in the new
digital world
See: BMW AWS show case
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 12
The implementation gap
Market forces and
business needs
Big Data and IoT
infrastructure reality
Rapid Technology Evolution
Time & Cost
Skills gap

13. No investment risk – highly secure and resilient
SAP HANA on AWS, powered by Ocean9

14. An aviation example for IoT and predictive
maintenance
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 14
EMR (Hadoop), SAP HANA and S3

15. Concept car IOT implementation – see blog post*
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 15
Echo, Alexa, Lambda, Ocean9 and HANA
* http/ocean9.io/post/from-amazon-echo-to-sap-hana-on-aws

16. How to achieve great Big Data results?
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 16
Summary
ONE
TWO
THREE
Inspire –> Talk business outcome first
Fail fast and often –> Cloud based
POCs
Roll-out quickly –> With cloud

17. The operating system for big data
• Enable enterprise class big data at controlled cost
Secure, reliable and dedicated cloud service offering w/ public cloud
economics
• Drive customer speed and agility in a governed fashion
Business agility through automation, continuous innovation and cloud elasticity
• Provide push button simplicity with intelligent guidance
Deployment configuration support and planning powered by machine learning
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 17
Ocean9 solution

18. Presenter: Frank Stienhans, CTO Ocean9
• Nov. 9th, 9am Pacific
• Register here:
https://www.brighttalk.com/webcast/929
3/208935
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 18
Ocean9 at November Big Data Summit
Frank is an early cloud innovator with key architecture and
operations contributions to SAP On Demand starting in
2005.
In 2007, he was first to recognize the power of AWS for SAP
use cases: His team built a self-service platform that allowed
simple deployment of any kind of complex SAP solution on
AWS, launching more than 10k servers per month. Gaining
tremendous operational expertise, SAP’s then CTO Vishal
Sikka challenged Frank to build a fully unattended SAP
HANA service on AWS, which resulted in 96% cost savings.
In 2013 Frank joined AWS Professional Services. He has
helped many large SAP customers to leverage the full
power of the AWS platform.
Frank is considered the leading expert in his field and is the
holder of 18 cloud related patents.

19. Topics at the intersection of Business, AWS, and SAP
June 15, 2016 © Copyright, 2016, Ocean9, Inc., All Rights Reserved 19
Check out the Ocean9 Blog
http://ocean9.io/blog

20. Thank you!
Q&A?
Swen Conrad, Ocean9
swen@ocean9.io
650 889 9876
20