Keynote: The Disrupting Effects of SAP HANA and in-Memory Databases Dr. Bjarne Berg Comerit

Introduction – Dr. Berg

This Presentation Comprises: Introductions Why HANA The World is becoming Visual Untraditional use of in-memory databases HANA Can Save Lives Conclusion

Data is Created Everywhere 4 Total number of hours spend on facebook each year: 108 billion hours Data sent and received by mobile platforms and phones: 1.7 Exabytes per day Number of s sent each day: 211 billion s Data processed by Google each day: 8.9 Petabytes Videos uploaded to YouTube each day: 1.09 million hours Data consumed by each world’s household each day: 902 MB (growing fast)! Number of tweets send each day: 500+ million Number of products sold on Amazon each hour: 568,000 products In 2016 we create 1,152,921,504,606,850,000 bytes of data every day! (that is one Zetabyte) Source: Annual Cisco® Global Cloud Index In 2016 we create 1,152,921,504,606,850,000 bytes of data every day! (that is one Zetabyte) Source: Annual Cisco® Global Cloud Index

Where is the data Located and What Drives the Growth? Source: Cisco® Global Cloud Index Today, 73% of data stored on client devices resides on PCs. By 2017, global smartphone traffic (201 EB per year) will exceed the amount of data stored (179 EB per year) on those devices – necessitating the need for greater storage capabilities via the cloud. By 2019, 55% of the residential Internet population will use personal cloud storage and the majority of stored data (51%) will move to non-PC devices

Data is growing everywhere s 1970s 1980s 1990s 2000s 2010s

More Data is coming - The Internet of Things (IoT) Source: Syed Hoda, 2015 An History Lesson: Devices such as sensors, CCTV, TVs, cars, refrigerators, home security systems, dishwashers, Air-conditioners, power meters, toll road systems, facial recognition and much more is being connected through the IoT. Enormous amounts of data is collected by these devices

Hard Drives What is Holding us Back? Disk speed is growing slower than all other hardware components, while the need for speed is increasing Focus Improvement Addressable Memory 291,271x 5,825 MB/$ 0.02 MB/$ Memory 8264 x MIPS/$ 0.05 MIPS/$ CPU Technology 690 MBPS 5 MBPS 138x 2,000 x 200 Gbps 100 Mbps Network Speed x Source: 1990 numbers SAP AG, 2016 numbers, Dr. Berg Source: BI Survey of 534 BI professionals, InformationWeek,

Why Change to In-Memory Processing? 9 File systems were created to manage hard disks Traditional Relational Databases were made to manage file systems Application Servers were created to speed up applications that ran on a database. Therefore: Hard drives are DYING! Traditional relational databases are DEAD (they just don’t know it!) Application Servers will become less important

The Death of Storage Technology is Normal 10

Number of SAP HANA Customers is Growing Fast 11 HANA is no longer bleeding-edge technology, it is on track to almost 10,000 customers in 2016

The Rate of Change – Disruptive Technologies 12 Moore’s Law in technology: Processing Speed will double every 18 month Paradigm shifts: SAP HANA reads are executed times faster than on traditional relational databases such as Oracle 12g The rate of change in Paradigm Shifts is much faster than the incremental changes and a much lower cost

HANA Hardware Options 2016 

These HANA certified systems are based on E7 ivybridge processors with 15 cores per processor, or the newer Hartwell processors with 18 cores. HANA Hardware Options 2016  News: IBM’s Power8 system is now also SAP HANA certified

Sizing a BW system for HANA Using the BW Automated Sizing tool in the Migration Cockpit

SAP BW on HANA Sizing Tool for Existing BW Implementations SAP has released an updated tool that generates a report for sizing SAP BW. This program takes into consideration existing database, table types, and includes the effects of non-active data on the HANA system The higher precision you run the estimate at, the longer the program is going to run To increase speed, you can suppress analysis tables with less than 1 MB size This program is also referenced in SAP Notes and on the Service Marketplace

The SAP BW on HANA Sizing Result Since timeouts are common when running the sizing program, you can temporarily change the parameter in rdisp/max_wprun_time to 0 in BW transaction RZ11. Finally, you estimate the growth for the system as a percentage or as absolute growth. The output is stored in the file you specified and the file can now be ed to hardware vendors for sizing input and hardware selection

Sizing for BusinessSuite on HANA SAP also have programs to size the system for BusinessSuite on HANA In this example from July 2015, we see that a system of GB is required to migrate the ECC 6 box to HANA

HANA Demo with 1 billion 222 million rows

This Presentation Comprises: Introductions Why HANA The World is becoming Visual Untraditional use of in-memory databases HANA Can Save Lives Conclusion

The World is becoming Visual Today’s users are often people who grew up in the 1970s, 80s and 90s and who are most comfortable with text and number based reports and analytics. The next generation of users trusts computers to always be available, and are comfortable with more visualizations and less cluttered details

Data Visualizations Require faster systems such as SAP HANA 22 Big data is being generated from micro and macro levels. From human DNA for each person to the content of billions of stars in galaxies. Internet usage Map by protocol Computer based human interaction is getting more common and generating terabytes of data each second A Map on the Whole Internet Data visualizations are get more prominent – can computers keep up?

This Presentation Comprises: Introductions Why HANA The World is becoming Visual Untraditional use of in-memory databases HANA Can Save Lives Conclusion

New Big-Data Innovation – Company War Rooms 24 In a multi-national company, data is created and consumed everywhere. With SAP HANA you can create a corporate war-room to track customer demand, shipments, marketing success and business intelligence This picture is from Sprint phone company’s war-room to track usage and transition issues during system mergers and product launches.

New Big-Data innovation – Scientific Discovery 25 The hadron super collider center CERN, creates over one PetaByte every second it operates. The Spectre R telescope of Russia has 1000 times higher resolution than Hubble, generating billions of bytes of data.

New Big-Data Innovation in Safety and Security 26 Thousands of hours of video is taken at airports, banks, casinos, borders and other sensitive areas. Facial recognition software can identify wanted criminals. SAP HANA can store that data and process the information.

New Big-Data Innovation – Weather and Fishery tracking 27 Tracking whether and execute predictive models require significant number of data points with high data volume Modeling resources such as fisheries and specie movements also require significant data volumes and data points on catch information across the globe

New Big-Data Innovation – Pollution Tracking 28 Geo data from pollution, data modeling and tracking creates hundreds of Terabytes. SAP HANA can assist in storing and retrieving this data With Predictive modeling and data visualization you can build sophisticated models on HANA. You can even use the R-statistical library in HANA With Predictive modeling and data visualization you can build sophisticated models on HANA. You can even use the R-statistical library in HANA

This Presentation Comprises: Introductions Why HANA The World is becoming Visual Untraditional use of in-memory databases HANA Can Save Lives Conclusion

HANA Can Save Lives 30 CAT scans and X-Rays create an large amount of data that doctors have to review and access X-Ray of Cancer Patient CAT Scan of Tumor Patient In-memory databases, such as SAP HANA, can store this and provide high volume and provide instant access to hundreds of Terabytes of data

HANA Can Save Lives 31 CT-Scans use ionized radiation which have increased cancer risks, but are much faster to process in an emergency room. MRI use magnetism and has less risk, but takes longer to process L1 and L2 images and is therefore less used in emergency rooms. With faster data processing, MRI can start using higher resolutions and much faster imaging, thereby saving lives In-memory databases, such as SAP HANA, may revolutionize data processing in emergency rooms and render much of CT-scanning useless

This Presentation Comprises: Introductions Why HANA The World is becoming Visual Untraditional use of in-memory databases HANA Can Save Lives Conclusion

Reference to More Comprehensive Information SAP HANA: An Introduction (3rd Edition) SAP Press Hardcover Dr. Bjarne Berg & Penny Silvia (ISBN ) SAP HANA High Availability and Disaster Recovery Essentials Dr. Bjarne Berg, Jonathan Haun, Kehinde Eseyin, Ned Falk, Irene Hopf, Rahul Urs, Christian Savelli, Michael Vavlitis The SAP BW to HANA Migration Handbook Dr. Bjarne Berg, Robert Frye & Joe Darlak

5 Key Insights All databases will be in-memory in the next 5-7 years If you are a SAP customer you will move to HANA In-memory databases are the norm and an overall industry trend Netezza, Hadoop, IBM-blue, Exadata and many more databases exists in addition to SAP HANA, but SAP applications such as S/4, business Suite (SoH) and BW 7.5 are optimized to take advantage of HANA. In-memory databases are a paradigm shift with substantial better storage capabilities and performance – you need to be imaginative to take advantage of these capabilities

Questions? How to contact me: Dr. Bjarne Berg