ITELLIGENCE - HANA ÜZERİNDE ERP VE ANALİTİK - SAP Forum 2013

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Global "HANA Live" ramp-up iş ortağı itelligence, HANA ile etkileşimli analitikler ve suite on HANA alanlarında, global tecrübelerini sizlerle buluşturuyor. Itelligence Global İş Analitikleri Direktörü Christian Schmidt ile yapacağımız
sunuma, HANA Live Browser (HTML5) ile canlı deneyimler için sizleri bekliyoruz.

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ITELLIGENCE - HANA ÜZERİNDE ERP VE ANALİTİK - SAP Forum 2013

  1. 1. SAP FORUM İSTANBUL Gelecek Bugün Konuşmacı Adı : Christian Schmidt & Serdal Mermer Firma Adı : itelligence Innovation through Suite on HANA and HANA Live
  2. 2. © 2013 SAP AG. All rights reserved. 2 itelligence Analytics Intelart which is started to operate as an Elsys Group company and offers business analytics & technology solutions, continues its services as itelligence Analytics from July 2012  Industrial knowledge  End to end, integrated corporate solutions  Experienced consulting team  SAP BA&T Solutions  Fast and ready to use analytics  Technology solutions, SAP HANA 9/10/2013 © itelligence2
  3. 3. © 2013 SAP AG. All rights reserved. 3 itelligence Analytics References
  4. 4. © 2013 SAP AG. All rights reserved. 4 Agenda  Business Challenges  Innovation  Suite on HANA@itelligence  Analytics and HANA
  5. 5. © 2013 SAP AG. All rights reserved. 5 Agenda  Business Challenges  Innovation  Suite on HANA@itelligence  Analytics and HANA
  6. 6. © 2013 SAP AG. All rights reserved. 6 Buckle yourself up for the Business challenges! Online Shopping Immediate access to information in real time becomes an ever more important success factor! Fast innovation cycles Ebit Revenue Customer segmentation Capabilities Industry requirements Global requirements Market recognition Positioning Global markets Ever faster reaction times Cost effectivity „Always-on“- society Social Media Society Competition Globalization Financials international competitors Global customers
  7. 7. © 2013 SAP AG. All rights reserved. 7 And the same applies to IT business… Big Data Mobile Collaboration Mobility Capabilities Cloud Global requirements Solution platform Methodology Market recognition Outsourcing Application support RolloutsSaaS Self Service BI Social (Collaboration) BI
  8. 8. © 2013 SAP AG. All rights reserved. 8 … while data volume increases: Pope nomination 2005… 9/10/2013 © itelligence8
  9. 9. © 2013 SAP AG. All rights reserved. 9 … and 2013 9/10/2013 © itelligence9
  10. 10. © 2013 SAP AG. All rights reserved. 10 Agenda  Business Challenges  Innovation  Suite on HANA@itelligence  Analytics and HANA
  11. 11. © 2013 SAP AG. All rights reserved. 11 What do these things have in common? Traditional Business Software Analog Communication Devices Traditional Cargo VesselsPropeller Driven Airplanes
  12. 12. © 2013 SAP AG. All rights reserved. 12 This is what they have in common… 10.09.2013 © itelligence1  They were state of the art  They were the vehicle of choice for the relevant purpose  They enabled businesses to be stable and profitable  They reached their limits with respect to  the technology that was used  their capacity  They were all replaced by (r)evolutionary innovations
  13. 13. © 2013 SAP AG. All rights reserved. 13 Innovations enable progress… Modern Jet Airplanes Modern Container Ships Digital Communication and Internet In Memory Computing SAP HANA™
  14. 14. © 2013 SAP AG. All rights reserved. 14 In-Memory-Computing using SAP HANA - a (r)evolution! Leveraging state of the art Database Technology Running on modern Hardware In-Memory Computing SAP HANA™  Dedicated and certified hardware  Everything runs in memory leveraging multiple CPUs  Hard drives are only used for backup purposes  New technology optimized to run on the HANA hardware  Designed to process large amounts of data in a very fast and flexible way simulatiously  Column and row oriented  Shift load intensive and time consuming processes back into the database  Allows processes to become agile, flexible and more transparent (again)
  15. 15. © 2013 SAP AG. All rights reserved. 15 In-Memory Computing SAP HANA™ Let‘s look at some success stories… John Deere # of employees 60000 Annual revenue €26bn Nongfu Springs # of employees 10000 Annual revenue €1.25bn Big Point # of employees 800 Annual revenue €300m Big Point, the German Online Game Provider is able to offer thousands of its customers offers in real time through apps that are based on SAP HANA™ (previously it took 6-24 hours to do this), leading to a 30% increase of revenue. The farming equipment manufacturer leverages SAP Business Suite on HANA™ to start a new line of business: predictive maintenance and preventitve services for farming equipment. Nongfu Springs, the Chinese beverage manufacturer uses SAP HANA™ to optimize the delivery process of their goods. Transport costs make up 15% of the total revenue (€187m) and €66m can now be cut from the distribution costs.
  16. 16. © 2013 SAP AG. All rights reserved. 16 In-Memory-Computing using SAP HANA - a (r)evolution!  HANA goes way beyond farther and faster. It is also about going higher, achieving more and exploring new opportunities  HANA powers information, goods, and processes everywhere  HANA enables new, highly flexible processes in real time  HANA allows companies to explore new markets  HANA is the foundation for new and better business decisions  If you invest in SAP HANA today, you can benefit from it… … like organizations that were early adopters of containers, digital communication and modern jet aircraft!
  17. 17. © 2013 SAP AG. All rights reserved. 17 Agenda  Business Challenges  Innovation  Suite on HANA@itelligence  Analytics and HANA
  18. 18. © 2013 SAP AG. All rights reserved. 18
  19. 19. © 2013 SAP AG. All rights reserved. 19
  20. 20. © 2013 SAP AG. All rights reserved. 20 How long does it take to read and display 110.000 sales orders out of SAP ERP? 258 6,3 0 50 100 150 200 250 300 old (non)HANA: VA05n new HANA: VA05 seconds time from start (F8) until display of results (sec) Example for the performance of non HANA and HANA ERP transactions Test results measured by Wolfgang Möller on the EH1 system. Both reports read the same data (110.000 sales orders, created via LSMW) and were listed with identical layout settings
  21. 21. © 2013 SAP AG. All rights reserved. 21 New HANA transactions - List of sales orders – classic vs. HANA 110.000 sales orders VA05N - Classic VA05 – HANA optimized
  22. 22. © 2013 SAP AG. All rights reserved. 22 Key Findings There were only minor issues with the migration (missing license keys) All functionality, regardless if SAP standard or itelligence coding worked without problems The GUI reaction times are significantly better, providing a better user experience Reports and functions specifically designed for HANA gain tremendous performance increase, allowing new business scenarios (Unchanged) SAP reports and functions show almost always a better performance Our own IP works without errors but performance on HANA is not consistent: Custom Coding needs to be analyzed and optimized
  23. 23. © 2013 SAP AG. All rights reserved. 23 Agenda  Business Challenges  Innovation  Suite on HANA@itelligence  Analytics and HANA
  24. 24. © 2013 SAP AG. All rights reserved. 24 What is HANA Live?  A set of virtual views that turn the 90,000+ tables into consumable information  Running either in an integrated SoH scenario or in a sidecar approach (using SLT and ECC on “any DB”)  Real-time information intended for operational reporting and operational applications  Extendable by the customer  Available for ERP, CRM, SCM and GRC  Open Architecture, can be consumed via  SQL / MDX  HANA XS Engine (HTML5) Out-of-the-Box Custom-built Open Interface Customer Extensions Personalized Views Private Views Reuse Views Physical Tables SAP- delivered Query Views (Standard) SAP HANA Live Virtual Data Model
  25. 25. © 2013 SAP AG. All rights reserved. 25 How do the EDW and HANA Live work together SAP ECC HANA EDW (BW) HANA Live SAP HANA Live • Operational data • Real-time • Lightweight modelling • Extensible EDW • Strategic and Tactical data • Integration and harmonisation cross systems • Data lifecycle management • Data governance • Historical truth • Complex logic ETL Real-time Examples • Sales Performance Dashboard • Month end management pack • Weekly flash report Examples • Work Order listing • Open Order Items • GR/IR cockpit • Month end fast close
  26. 26. © 2013 SAP AG. All rights reserved. 26 A closer look at HANA Live – HANA Studio
  27. 27. © 2013 SAP AG. All rights reserved. 27 A closer look at HANA Live – HANA Studio
  28. 28. © 2013 SAP AG. All rights reserved. 28 A closer look at HANA Live – View Browser
  29. 29. © 2013 SAP AG. All rights reserved. 29 A closer look at HANA Live – View Browser
  30. 30. © 2013 SAP AG. All rights reserved. 30 A closer look at HANA Live – View Browser
  31. 31. © 2013 SAP AG. All rights reserved. 31 A closer look at HANA Live – View Browser
  32. 32. © 2013 SAP AG. All rights reserved. 32 A closer look at HANA Live – View Browser
  33. 33. © 2013 SAP AG. All rights reserved. 33 A closer look at HANA Live – View Browser
  34. 34. © 2013 SAP AG. All rights reserved. 34 A closer look at HANA Live – View Browser
  35. 35. © 2013 SAP AG. All rights reserved. 35 A closer look at HANA Live – View Browser
  36. 36. © 2013 SAP AG. All rights reserved. 36 A closer look at HANA Live – GRIR Monitor
  37. 37. © 2013 SAP AG. All rights reserved. 37 A closer look at HANA Live – GRIR Monitor
  38. 38. © 2013 SAP AG. All rights reserved. 38 HANA Live and SAP Business Objects (IDT)
  39. 39. © 2013 SAP AG. All rights reserved. 39 HANA Live and SAP Business Objects (IDT)
  40. 40. © 2013 SAP AG. All rights reserved. 40 HANA Live and SAP Business Objects (IDT)
  41. 41. © 2013 SAP AG. All rights reserved. 41 HANA Live and SAP Business Objects (WebI)
  42. 42. © 2013 SAP AG. All rights reserved. 42 HANA Live and SAP Business Objects (WebI)
  43. 43. © 2013 SAP AG. All rights reserved. 43 HANA Live and SAP Business Objects (WebI)
  44. 44. © 2013 SAP AG. All rights reserved. 44 HANA Live and SAP Business Objects (WebI)
  45. 45. © 2013 SAP AG. All rights reserved. 45 HANA Live and SAP Business Objects (Lumira)
  46. 46. © 2013 SAP AG. All rights reserved. 46 HANA Live and SAP Business Objects (Lumira)
  47. 47. © 2013 SAP AG. All rights reserved. 47
  48. 48. © 2013 SAP AG. All rights reserved. 48 How HANA Live and SAP BW can work together… FI-GL Line Items P&L Plan Virtual P&L Actual P&L Actual HANABSEG FAGLFLEXA ECC HANA Live AnyDBBSEG ECC FAGLFLEXA HANA FAGLFLEXA HANA Live BSEG SLT BW
  49. 49. © 2013 SAP AG. All rights reserved. 49 HANA Live Data in SAP BW
  50. 50. © 2013 SAP AG. All rights reserved. 50 HANA Live Data in SAP BW
  51. 51. © 2013 SAP AG. All rights reserved. 51 HANA Live Data in SAP BW
  52. 52. © 2013 SAP AG. All rights reserved. 52 Setting it straight – HANA Live and SAP BW HANA is not just a fix for performance problems HANA is not just about Big Data HANA Live will NOT replace SAP BW HANA Live and SAP BW complement each other HANA Live for real time, operational reporting SAP BW for strategic and tactical EDW requirements The combination of both stacks helps addressing all analytic scenarios HANA brings IT and Business together – How? Business has immediate access to all operational data to make operational and transactional decisions Business creates tactical reports leveraging the entire EDW, fast and enhancing with their own logic and data IT provides faster reporting projects that meet expectations IT spends more time in agile, data enabled prototyping workshops with the business
  53. 53. © 2013 SAP AG. All rights reserved. 53 Open Platform for Innovating Without Disruption User-driven experience SAP UI HTML5 Mobile SAP Business Objects™ Business Intelligence Solutions Real-Time Interactions Real-Time Platform SAP HANA™ & SAP HANA™ Live SAP NW Business Ware- house New Apps, Non SAP Apps & Data- sources SAP NW Business Warehouse SAP NW Business Suite SAP ECC SAP SCM SAP SRM SAP PLM SAP CRM Real-Time Execution Real-Time Planning Real-Time Reporting and Analysis SAP HANA Platform
  54. 54. © 2013 SAP AG. All rights reserved. 54 Past, Present & Future Historical Realtime Predictive  Delay  Realtime only for transactional scenarios  Direct integration of operational reporting in workflow  Shorter / Proactive reaction times (Google feeling: get the answers while still typing)  Simulations  Internet of things  Text analytics  Machine generated data  Self service analytics Business Challenge  Structured Data from Business Application  Limitations in RAM  Mainly Structured data from business applications  Partly unstructured possible  Many sources  Structured data  Unstructured data (for example text mining)  AdHoc queries  Many different sources, including Social Sources Data  Classical BI / SBOP  Layered architecture  Separation OLTP / OLAP  ETL / Data Warehouses  In memory  Mixed scenarios possible  Now ready for enterprise computing  Hadoop / Map Reduce / No SQL / R  Originally for storing and indexing of websites Technology
  55. 55. Teşekkürler! İletişim Bilgileri: Serdal Mermer itelligence Analytics Genel Müdürü Serdal.mermer@itelligence.com.tr Christian Schmidt itelligence Global, İş Analitikleri Direktörü christian.schmidt@itelligence.de

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