1. HANA Overview and Capabilities
Dr. Bjarne Berg

2. Why In-Memory Processing?
Technology
Focus
1990
2012
Improvement
0.05
MIPS/$
304.17
MIPS/$
6083x
CPU
0.02
MB/$
52.27
MB/$
2614x
Memory
216
264
248x
Addressable Memory
100
Mbps
100
Gbps
1000 x
Network Speed 5
MBPS
620
MBPS
124x
Disk
Data Transfer
Source: 1990 numbers SAP AG, 2012 numbers, Dr. Berg
Source: BI Survey of 534 BI professionals, InformationWeek, 2010
Disk speed is growing slower than all other hardware components, while the need for speed is increasing.

3. In Memory Processing — General Highlights — BWA
BWA = SAP BW Accelerator

4. SAP HANA — In Memory Options
SAP HANA is sold as an in-memory appliance. This means that both Software and Hardware are included from the vendors
Currently you can buy SAP HANA solutions from Cisco, Dell, Fujitsu, IBM, and Hewlett-Packard
SAP HANA currently indexes the data from a variety of sources, including ERP and BW and store the result on a dedicated server
The future of SAP HANA is to replace the databases of ERP and BW and run these on the in-memory platform
Source SAP AG,2011
SAP HANA has the potential to radically change the way databases operate and make systems dramatically faster.

5. The Different Editions of HANA

6. Looking Inside SAP HANA — In-Memory Computing Engine (IMCE)
AAAA
Metadata Manager
Authorization
Manager
Transaction
Manager
Persistence Layer
Disk Storage
Relational Engine
-Row Store
-Column Store
SQL Script
SQL Parser
Data Volumes
Page Mgmt.
Session Manager
Calculation
Engine
MDX
Logger
Log
Volumes
Load Controller
Replication Server
BusinessObjects Data Services
Inside the Computing Engine of SAP HANA we have many different components that manage the access and storage of the data. This include MDX and SQL access, as well as Load Controller (LC) and the Replication Server.

7. Row based index

8. Row- vs. Column-Based Indexing (cont.)
As we can see, there are only 7 unique states and 3 unique customer classes in the data. This allows SAP HANA to compress this data set significantly
By including the Row ID in the column-based index in SAP HANA, the “ownership” of the values in the index can still be mapped back to the record
Column-based indexes on fields with repeated values often leads to better compression ratios and thereby lower size of the indexes (as we can see, there are few values repeated in the rows).

9. SAP HANA — Virtual Marts and Applications
Virtual data marts and new applications were built that run on SAP NetWeaver BW, which is again enabled by SAP HANA in-memory processing
Applications developed by SAP
Planning & consolidation
Customer revenue performance mgmt
Predictive segmentation & targeting
Trade promotion management
Merchandise & assortment planning
Sales & operations planning (SOP)
Demand signal repository
Profitability analysis
Dynamic cash management
Strategic workforce planning
Smart meter analytics (power companies)
Enterprise Data Warehouse – SAP BW
HANA (in-the works)
BI Solutions
ERP
Virtual
Data
Marts
Virtual
Data
Marts
Database
Applications
Virtual
Data
Marts
Virtual
Data
Marts
Databases
Files
This provides much tighter integration with the source system (less data latency) and much faster query response time for high-volume analysis

10. The Hardware – IBM Example

11. Client Demo

12. SAP HANA — Loading the Application and Performance
You can load the application based on the logs in the source system, ETL-based (Extract Transform and Load) loads, and SAP trigger-based replication
Tool Purpose
BusinessObjects Data Services – ETL-based replication
Sybase replication server & Load Controller – Log-based replication
SAP Landscape Transformation (LT) – Trigger-based replication
Log based replication is possible on IBM DB 2 LUW/UDB, MSFT SQL Server Enterprise Edition, Oracle Enterprise Edition, and Sybase ASE

13. Opening HANA Admin

14. Adding New System in HANA

15. Adding New System in HANA

16. Creating HANA system connection

17. Setup HANA Security Authentication

18. Changing a HANA password

19. Creating HANA Security questions

20. Creating HANA Security questions

21. Your HANA System in the Navigator

22. Searching for a table in HANA

23. The table definition
inside HANA

24. All HANA tables

25. Open a
HANA table

26. Browsing data in
a HANA table

27. Opening HANA Admin

28. HANA memory usage

29. Creating a New HANA Table

30. Creating a New HANA Table

31. Creating a New Products
HANA Table

32. Defining a new Sales
HANA table

33. Accessing Data Services to Load data to HANA

34. Accessing Data Services to Load data to HANA

35. Linking Data Services to HANA datastores

36. Linking Data Services to HANA datastores

37. Linking Data Services to HANA datastores

38. Our new Data Services HANA repository

39. Data Services HANA repository objects

40. Importing HANA table definitions

41. Importing HANA Customer table definition

42. Importing HANA Sales table definition

43. Linking data files to load to HANA

44. Linking data files to load to HANA

45. Defining file format for loading data to HANA

46. Defining data file format for HANA data load

47. Saving file formats

48. Customer file for HANA data load

49. Replicating
Product file for
HANA data load

50. Product file for HANA dataload
Replicated
Product file for HANA dataload

51. Sales file for HANA data load
Replicating
Sales file for HANA data load

52. Replicated Sales file format loading data to HANA

53. Create a Project for Data Services

54. Create a Project for Data Services

55. Create a Batch job for HANA
data loads

56. The new batch job for a HANA
data load

57. A new dataflow for HANA data load

58. Making HANA tables the data target

59. Creating data mapping to load data to HANA

60. Creating data mapping to load data to HANA

61. Detailed data mapping to load data to HANA

62. Detailed data mapping to load data to HANA

63. Execute a HANA data load

64. Execute a HANA data load

65. Execute a HANA data load

66. HANA
data load log

67. Opening HANA Studio

68. Opening HANA Studio

69. Opening our
Customer table in
HANA

70. Our Customer table in HANA

71. What can you do with HANA and BO Explorer?
The system looks at the data and formats it based on implied hierarchies (i.e., time, geography, customer) as well as measures. Users may navigate and change measures, graphs, and tables.

72. Measures used on any graph can be calculated “on-the-fly.”
New Calculations
Any data panel can be sorted in many ways
We can also add our own measures
In our example we are adding the measure “Margin Per Unit” as total margin divided by “quantity sold”
Measures used on any graph can be calculated “on-the-fly.”

73. HANA Optimized InfoCubes

74. Data Store Objects (DSO) In HANA
The DSO in HANA is a ‘closed’ object where you can do:
Index reads (snapshots)
Delta reads for updates
Activate data
Querying
Read delta, between snapshot 1 and 2
Index Read
Delta Index
Main Index
Activation
Insert
Only Index
History Index
PS! a table, an analytic or calculation view in a HANA schema can be accessed via a BW DataSource. This is based on ‘DB connect’ using a second DB connection to the underlying HANA DBMS.
Source: T. Zurek, SAP AG
Data Load

75. SAP HANA — Test Drive
You can see demos and do a test drive at:
This site contains a lot of great information and you can also try the Information Composer and see recorded demos.

76. Register and Take a Free BI Test Drive with SAP HANA
You can register for a free test drive at:
You can also upload your own data and try the tool to see if it is something for your organization. There is even quick guides, videos, and wizards to get you started.

77. Questions and Answers
Dr. Berg