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HANA SITSP 2011

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My HANA Overview Presentation on SAP Inside Track São Paulo 2011

My HANA Overview Presentation on SAP Inside Track São Paulo 2011

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  • Columnar data store benefitsOptimizes load of data to CPUHigh data compressionVery fast data aggregationMakes use of real-life fill of tables (few fields filled, few updates)
  • 4 minutesResponse time and throughput – HANA aka IMCE is sitting on top of the heap here. We have orders of magnitude increase in speed while maintaining high levels of throughput. Because what it does is implement all of the features of the legacy data storage mechanisms IN MEMORY. The only reason we use disk is for recovery and restart. We are the fastest.Before we get into those features, lets position and differentiate HANA with what is out there.Disk based:By the time you position the disk head to read the first block, we have already returned.Traditional DBMS – db2, 11g, mssql, aseNextGen Traditional DBMS –exadata, madison, teradata, nz, really start to blur the line with caching/disk/network optimizationMemory CacheTraditional – memcache, persistence, tangasol, CICS buffer poolsBI Based – MSTR, qlicktech, don’t let those vendors come out equal (yeah we have in memory) NO THEY DON”TWhile the NextGen Traditional DBMS does introduce further memory usage through appliance structures (Exadata for example), this will require deciding which data to store in memory and get good performance on. HANA includes all data in-memory and takes a different approach to ensure good performance on the full dataset.
  • Of the components displayed on this slide, not all are part of HANA. Business Objects Enterprise, the ERP system, the clients etc. are optional components whose presence in the system landscape depends on the customer scenario.The components listed here are: The in-memory computing engine itself, which hosts the actual data stores, a persistence layer, a calculation/execution engine, interfaces and other components The in-memory computing studio which is a front-end delivered with HANA which enables administration of the in-memory computing engine and modeling for the engine. An ERP system in which a replication agentis installed to enable data transfer from ERP to HANADatabase clients (JDBC, ODBC, ODBO) which allow client tools to connect to HANA.Optional components - a NetWeaver BW system or third party systems which can be connected to HANA via SAP BusinessObjects Data Services- a BusinessObjects Enterprise system with Data Services installed.Client tools for reporting off HANA, e.g. MS Excel, SAP BusinessObjectsAnalysis Office, SAP BusinessObjects BI reporting tools. These tools might need components in a BusinessObjects Enterprise system (such as Information Design Tool).In the following slides we take a look at several usage aspects of HANA such as data loading, modelling and reporting and discuss which parts of this setup are important for these aspects.
  • At the top is the connection and session management which creates and manages sessions and connections for the database clients. For each session a set of parameters is maintained such as e.g. auto commit settings or the curernt transaction isolation level.The client requests are analyzed and executed by the set of components summarized as „Request Processing and Execution Control“. Once a session is established, database clients typically use SQL statements to communicate with the in-memory computing engine. For analytical applications the multidimensional query language MDX is supported in addition.Features such as SQL Script, MDX and planning operations are implemented using a common infrastructure called calc engine.At the heart of the in-memory computing engine are two relational engines. The row and the column store. These relational engines act as databases. Both are in-memory databases, that is, their primary data persistence is based in RAM.The row store stores data in row based way. In this respect it behaves like traditional relational databases: data is stored and retrieved in records. A major diffenrence to traditional databases is that all data is always kept in RAM.The column store is a relational column based in-memory data engine. That means data is stored and retrieved in columns. This is an optimal concept for analytical queries. The concept is known e.g. From SAP netweaver BW Accelerator (BWA) where this technology has already demonstrated its potential.Even though the relational engines are memory based, a persistence on less volatile media is required for reasons of data safety. Otherwise a power cut or OS reboot would permanently erase all data in the database. The persistency layer handles page management and logging (redo and Undo logs) and permanently stores data in a disk storage. This storage has seperate volumes for data and log.The engine also has a component called transaction management. Transaction management is required in order to provide consistent views of the data at any given point in time (an ongoing transaction must only see that part of the data that was committed before that transaction was started).Replication Server and Load Controller arethe engine-side part of the Sybase replication manager.
  • One of the promises of HANA is to deliver real-time analytic insight on vast data volumes.For the real-time aspect, data provisioning in real time is required. This is the task of Sybase Replication Server. Tables from the ERP system are initially loaded into HANA. All subsequent changes to these ERP tables are immediately replicated into the HANA server. To this end, replication server makes use of the database logs in the ERP system.There is a tool that helps selecting the tables to be loaded and replicated. This tool is integrated into the In-Memory Computing Studio.Replication Server only allows connecting one SAP ERP system to HANA. Some additional requirements apply regarding the ERP system such as server OS, DBMS system, ERP version, SAP kernel and unicode state (only unicode is supported). Note: 1513496 gives information about Hana restrictions.Systems not fullfilling these requirements can be accessed via data services. This requires a BusinessObjects installation, with a data services server and data services designer on the client. Note 1522554 NetWeaver Support Package requirement for Data Services SAP Extractor support .Note: for practical purposes it will probably not be reasonable to connect to several ERP systems with one HANA box (one via replication, the other(s) via data services) for obvious reasons (same tables existing in all the ERP systems etc).Note: Loading from NetWeaver BW into HANA via data services technically is an application of OpenHub.
  • The High‐performance ANalytic Appliance (HANA) is a hardware and software combination that integrates a number of SAP components (for example, NewDB, Modeler, Data Services) delivered as an optimized hardware appliance in conjunction with leading hardware partners.HANA provides a flexible, data source agnostic, multi‐purpose appliance that has many deployment options. For example, customers can directly analyze large volumes of SAP ERP, SAP BW, or non‐SAP data in “real real‐time” without having to create any form of materialized views. This is possible because the software intelligently leverages the native multi‐core support and massively parallel processing capability of the appliance to provide a data source agnostic high performance analytical engine.
  • Notes: This is a example......
  • Once tables are created in HANA and loaded from the source system, the semantic relationships between the tables need to be modeled.In an ERP system, these relationships are modeled via database views and ABAP code. In HANA, these relations initially do not exist at all.Modeling can be done in several places (bottom-up description): If data services is used to create and fill the table, first modeling decisions can be made here. Data models can be created within the In-Memory Computing Engine. Models are stored in form of views and associated metadata in the engine. The front-end tool to create these models in the In-Memory computing Studio (Information Modeler within that tool). Depending on the front-end tool used to retrieve data from the In-Memory Computing Engine, further modeling decisions can be made in universes (SAP BusinessObjects Information Design Tool) or other semantic layers.
  • In reporting, client tools create queries against the database. Where the actual query is generated depends on the tool used. This slide list some of the possible reporting tools.BusinessObjects Explorer will directly create a call against a HANA interface. Excel will also directly request data via MDX. Front-end tools which report against Universes will have the SQL request against HANA created in the universe layer. BI4 Analysis reports against BICS.Please note that at the time of creating these transparencies, it is not yet decided which front-end tools will be supported in combination with HANA. The front-end tools listed in these slides are candidates.The following client side drivers are delivered with HANA: JDBC ( SQL) ODBC ( SQL) ODBO (short for OLEDB for OLAP  MDX)Which of the drivers will be used depends on the front-end tool used (and sometimes even the way in which the front-end tool is used).
  • Various connectivities exist : (O|J)DBC / ODBC (MDX) / SQL DBC (native lib for NewDB = newDB SDK (data, but also users rights, system management Here we can see BOBJ BI 4.0 client for Reporting, Crystal Report, 2 versions: * CR Enterprise include in BI 4.0 with connectivity though BI 4.0 (aka make usage of the CSL (or DSL as you like)) (C for Common, D for Dynamic) * CR 20xx standalone reporting tool, connectivity through ODBC (ODBO and MDX)BI4.0 Enterprise system will not be discussed here but separate training is available. Please contact SAP Education for further details.
  • Veryclassic BOBJ productpositionningslide, once again, positioning BI products, no good slide show withoutthisslide:ExplorerExplorer is a new BI paradigm: youcan explore your business and findanswerswhenyoudon’tknownwhich question to ask. Indeed, youdon’tneed to understand how the data isstructured, how yourqueries are built. Explorer searchesdirectly on the pre-indexed data in a very intuitive way.This tool is for “Casual User”, “Information workers who are seeking easier self-service environment” or “Users who are involved in day-to-day decisions”Web IntelligenceWeb intelligence is one of the mostadvanced ad-hoc reporting solution on the market. It lets end-users design and analyzetheirown reports and queries. This tool is the one to use for Reporting & Analysis goals, especially for the casual business users. During this webinar, we will only focus on Web Intelligence, connecting to a SAP BW data source.XcelsiusXcelsius bridges the gap between data analysis and visual presentation in a very sexy way. The Target audience is mostly for business users.Crystal ReportsCrystal Reports allowsyou to createOperational or pixel-perfect reportsThe Target audience is IT department for report authoring. It is the tool as well for most business usersfor report consumption.(** not here **)Voyager / Bex Web (=Pioneer)This is a powerful web-based OLAP analysis tool, for analyst users. It can help you to gain insight into business data and make intelligent decisions that impact corporate performance.
  • For Administration of the HANA, the In-Memory Computing Studio has an administration component. Tasks offered by the studio include (but are not limited to): Starting/stopping the In-Memory Computing Engine (upon start, the in-memory stores are reconstructed from the persistence layer) User administration including creating/deleting users and authorizations Table administration, including creating indexes or some part of the configuration for data replication Creating or replaying a backup
  • According to a current survey, 28 percent of IT managers in North America have snooped, and 44 percent of those in Europe, the Middle East, and Africa have done so, too. Around 20 percent of respondents in North America and 31 percent in EMEA say one or more of their co-workers have used administrative privileges to reach confidential or sensitive information.See http://www.darkreading.com/insider-threat/167801100/security/client-security/229401640/it-temptation-to-snoop-too-great.html
  • Auditing does not directly increase the security of the system. But wisely designed, it can help: Uncover security holes Show security breaches and privilege misuses Protect the system owner against accusations of security violation and data misuse The system owner meet their security standards In the current version of the SAP In-Memory Database, security logging and tracing is supported using the standard database log files. The features described in the following sections are supported in SAP HANA 1.0 SPS2, only.
  • Auditing in SPS02: Extensible auditing infrastructureAudit trail is stored using syslog Audit logging of authorization changes
  • The actual message that is written to the syslog is in CSV (comma-separated values) format so that it can be easily parsed and imported into other systems. The CSV format is as follows:<Event Timestamp>;<Service Name>;<Hostname>;<SID>;<Instance Number>;<Port Number>;<Policy Name>;<Policy Type Name>;<Audit Level>;<Audit Action>;<Active User>;<Target Schema>;<Target Object>;<Privilege Name>;<Grantable>;<Role Name>;<Target Principal>;<Success Status>;<Component>;<Section>;<Parameter>;<Old Value>;<New Value>;<Comment>;<Executed Statement>;It is possible to alter the audit configuration so that the audit trail is written to a text file. This must not be used on production systems. The text file writer has severe limitations. For example, it is not written in a thread-safe manner so that multiple entries, being written at the same time, can yield unexpected results. However, this can be very useful during testing the audit policies, as it is much easier to see the results of a policy in action.
  • Transcript

    • 1. HANA – Overview & Roadmap
      Henrique Pinto
      Consultor de Soluções, SAP Brasil
      Outubro de 2011
    • 2. Introduction to HANA
      Core Functionalities
      Use cases
      A Typical SAP Landscape Discussion
      HANA Roadmap
    • 3. Columnar
      In-Memory
      “By 2012, 70% of Global 1000 organizations will load detailed data into memory as the primary method to optimize BI application performance.”
      - Gartner
    • 4. SAP High-Performance Analytic Appliance (SAP HANA)
      SAP HANA is a data source agonistic in-memory appliance that enables organizations to analyze business operations in real-time based on large volumes of data
      Who is it for?
      Analyst
      Business User
      Executive
      Analyze large volumes of operational data in real-time
      Access, model, and analyze operational data in a single environment without affecting existing applications or systems
      Provide a high performance technological foundation for business analytics
      What is it for?
    • 5. SAP HANASAP High-Performance Analytic Appliance
      Preconfigured Analytical Appliance
      • In-Memory software + hardware(HP, IBM, Fujitsu, Cisco)
      In-Memory Computing Engine Software
      • Data Modeling and Data Management
      • 6. Real-time Data replication for SAP ECC
      • 7. Data Integration for 3rd Party Systems
      Capabilities Enabled
      • Analyze information in real-time at unprecedented speeds on large volumes of non-aggregated data
      • 8. Create flexible analytic models based on real-time and historic business data
      • 9. Foundation for new category of applications (e.g., planning, simulation) to significantly outperform current applications in category
      • 10. Minimizes data duplication
      Other Applications
      SAP BusinessObjects
      SAP
      HANA
      MDX
      SQL
      BICS
      In-Memory Computing Engine
      SAP NetWeaver
      BW
      In-Memory
      Computing
      Calculation and Planning Engine
      3rd Party
      Data Management Service
      SAP
      Business Suite
      Admin and Data Modeling
      Real–Time Replication Services
      Data Integration Services
    • 11. ROW-BASED Storage
      Tuple 1
      Tuple 2
      Tuple 3
      Tuple 4
      Column 1
      Column 4
      Column 3
      Column 2
       OPTIMIZED for current HW
       EasilyCOMPRESSABLE
      COLUMN-BASED Storage
      AVOID Bottlenecks – Data Storage
    • 12. Classical Approach
      Calculation
      APPLICATION
      LAYER
      DATABASE
      LAYER
      MOVEcalculations into database
       Only transferRESULTS
      Calculation
      Future Approach
      AVOID Bottlenecks – Data Transfer
    • 13. In-Memory Computing – The Time is NOWOrchestrating Technology Innovations
      HW Technology Innovations
      SAP SW Technology Innovations
      Row and Column Store
      Multi-Core Architecture (8 x 8core CPU per blade)
      Massive parallel scaling with many blades
      One blade ~$50.000 = 1 Enterprise Class Server
      Compression
      Partitioning
      64bit address space – 2TB in current servers
      100GB/s data throughput
      Dramatic decline in price/performance
      No Aggregate Tables
      Insert Only on Delta
    • 14. Response Time
      In-Memory
      HANA
      microseconds10-6
      Disk-Based DBMS with Memory Cache
      Or
      Solid-State DBMS
      milliseconds10-3
      Disk-Based DBMS
      seconds
      100
      1,000
      10,000
      100,000
      Throughput (transactions per second)
    • 15. Introduction to HANA
      Core Functionalities
      Use cases
      A Typical SAP Landscape Discussion
      HANA Roadmap
    • 16. Architecture OverviewSAP HANA Appliance and Surroundings
      SAP HANA Studio
      Clients
      MS Excel
      BI4 Explorer
      Modeling
      Administration
      SAP BI4 universes (WebI,...)
      Dashboard Design
      BI4 Analysis
      ERP
      SAP HANA Appliance
      Replication Agent
      SLT Add-on
      SAP HANA Database
      Session Management
      Log
      ERP DB
      Transaction Manager
      Request Processing / Execution Control
      Replication Server
      SQL Parser
      MDX
      Authorization Manager
      SAP Business Objects BI4
      SQL Script
      Calc Engine
      Load Controller
      Relational Engines
      SBO BI4 Information Design Tool
      Data Services Designer
      Metadata Manager
      Row Store
      Column Store
      Persistence Layer
      Logger
      Page Management
      SBO BI4 servers ( program for client)
      Data Services
      Disk Storage
      Data Volumes
      Log Volumes
      Other Source Systems
      SAP NetWeaver BW
      3rd Party
    • 17. SAP HANA Studio
      Clients
      MS Excel
      BI4 Explorer
      Modeling
      Administration
      SAP BI4 universes (WebI,...)
      Dashboard Design
      BI4 Analysis
      ERP
      SAP HANA Appliance
      Replication Agent
      SLT Add-on
      SAP HANA Database
      SAP HANA Database
      Session Management
      Session Management
      Log
      ERP DB
      Transaction Manager
      Transaction Manager
      Request Processing / Execution Control
      Request Processing / Execution Control
      Replication Server
      SQL Parser
      SQL Parser
      MDX
      MDX
      Authorization Manager
      Authorization Manager
      SAP Business Objects BI4
      SQL Script
      SQL Script
      Calc Engine
      Calc Engine
      Load Controller
      Relational Engines
      Relational Engines
      SBO BI4 Information Design Tool
      Data Services Designer
      Metadata Manager
      Metadata Manager
      Row Store
      Row Store
      Column Store
      Column Store
      Persistence Layer
      Persistence Layer
      Logger
      Logger
      Page Management
      Page Management
      SBO BI4 servers ( program for client)
      Data Services
      Disk Storage
      Disk Storage
      Data Volumes
      Data Volumes
      Log Volumes
      Log Volumes
      Other Source Systems
      SAP NetWeaver BW
      3rd Party
      Architecture OverviewThe engine itself
    • 18. Architecture OverviewLoading Data into HANA
      SAP HANA Studio
      Clients
      MS Excel
      BI4 Explorer
      Modeling
      Administration
      SAP BI4 universes (WebI,...)
      Dashboard Design
      BI4 Analysis
      ERP
      SAP HANA Appliance
      Replication Agent
      SLT Add-on
      SAP HANA Database
      Session Management
      Log
      ERP DB
      Transaction Manager
      Request Processing / Execution Control
      Replication Server
      SQL Parser
      MDX
      Authorization Manager
      Business Objects Enterprise
      SQL Script
      Calc Engine
      Load Controller
      Relational Engines
      SBO Information Design Tool
      Data Services Designer
      Metadata Manager
      Row Store
      Column Store
      Persistence Layer
      Logger
      Page Management
      Data Services
      SBO BI4 servers ( program for client)
      Disk Storage
      Data Volumes
      Log Volumes
      Other Source Systems
      SAP NetWeaver BW
      3rd Party
    • 19. SAP BusinessObjects Data Services 4.0 and HANA
      Metadata
      SAPERP
      Modeler
      Server
      Repository
      BW
      In-Memory Computing Engine(ICE)
      Data Load
      Open Hub
      Designer and Management Console
      SAP BusinessObjectsData Services 4.0
      HANA
      Any Source
      © SAP AG 2011
    • 20. HANA Modeling leveraging Data Services(Simplified Example using RFC_READ_TABLE)
      © SAP AG 2011
      Create a new DataStore of type “SAP Applications” with specific connection details
    • 21. Setup Information Modeler to communicate with Data Services (Configure Import Server)
      © SAP AG 2011
      Click “Import” to import meta data via Data Services or use the menu
    • 22. LT Replication Concept: Trigger-Based ApproachArchitecture and Key Building Blocks
      SAP HANA Database
      Source system
      LT Replication Server
      DB Trigger
      Write Modules
      DBConnection
      RFCConnection
      LoggingTables
      Read Modules
      Controler Modules
      Application Tables
      LT replication server does not have to be a separate SAP system and can run on any SAP system with SAP NetWeaver 7.02 ABAP stack (Kernel 7.20EXT)
      Application Tables
      Efficient initialization of data replication based on DB trigger and delta logging concept (as with NearZero downtime approach)
      Flexible and reliable replication process, incl. data migration (as used for TDMS and SAP LT)
      Fast data replication via DB connectLT replication functionality is fully integrated with SAP HANA Studio
    • 23. SAP HANA Appliance – Real Time Replication
      Landscape Option 1: (SAP ERP 4.6c or SAP ECC 6.0 on a NW release below NW ABAP 7.02)
      • For any customers on SAP ERP 4.6c, utilizing SLT will require setting up an intermediary system with at least NW ABAP 7.02 load controller for replication into HANA
      • 24. For example, a solution manager system could be used for the SLT Add-on
      • 25. Supports Non-Unicode or MDMP systems for SAP ERP as long as SLT is installed on a NW 7.02 Unicode system
      Landscape Option 2: (SAP ECC 6.0+, running on at least NW ABAP 7.02)
      • For any customers on SAP ECC 6.0+ running on NW ABAP 7.02 (must be fully Unicode), utilizing SLT can be done directly for replication into HANA
    • Technical Requirements and System Set-Up Information for LT Replication Server
      LT replication server can run on any SAP system with SAP NetWeaver 7.02 ABAP stack (using SAP Kernel 7.20EXT), for example on Solution Manager 7.1 or the source system – it does not have to be a separate SAP system!
      SAP HANA system
      Source system
      LT Replication Server
      RFCConnection
      DBConnection
      Installation:
      • respective DMIS 2010 version
      • 26. Minimum support pack level: latest available
      Installation:
      • HANA SPS02: includes LT replication functionality fully integrated into the UI of the HANA modeler
      Installation:
      • Addon DMIS 2010_1_700
      • 27. Minimum support pack level: SP04 (planned with release of HANA SPS02)
      Basic Configuration:
      • Define RFC connection to source system- Define DB connection to HANA system- Define max. number of jobs to be used for data replication
      Basic Configuration:
      • Optional: define separate table space for logging tables
      • 28. Define RFC user with appropriate authorization
      Basic Configuration:
      - Create a DB user (if required)
      System Requirements:
      - SAP Basis: Netweaver 702 with Kernel 7.20EXT (currently limited platform availability) - Filesystem: 100 GB- RAM: 16-32 GB
      • CPU: 2-4 cores
      • 29. Recommended number of background jobs: 10
      System Requirements:
      • SAP Basis 4.6C and higher
      • 30. All data bases
    • Architecture OverviewData Modeling
      SAP HANA Studio
      Clients
      MS Excel
      BI4 Explorer
      Modeling
      Administration
      SAP BI4 universes (WebI,...)
      Dashboard Design
      BI4 Analysis
      ERP
      SAP HANA Appliance
      Replication Agent
      SLT Add-on
      SAP HANA Database
      Session Management
      Log
      ERP DB
      Transaction Manager
      Request Processing / Execution Control
      Replication Server
      SQL Parser
      MDX
      Authorization Manager
      Business Objects Enterprise
      SQL Script
      Calc Engine
      Load Controller
      Relational Engines
      SBO Information Design Tool
      Data Services Designer
      Metadata Manager
      Row Store
      Column Store
      Persistence Layer
      Logger
      Page Management
      Data Services
      SBO BI4 servers ( program for client)
      Disk Storage
      Data Volumes
      Log Volumes
      Other Source Systems
      SAP NetWeaver BW
      3rd Party
    • 31. Modeling for HANA 1.0Using In-Memory Computing Studio
      Step1: (Attribute View)
      Separate Master Data Modeling from Fact data
      • Build the needed master data objects as ‘Attribute Views’
      • 32. Join text tables to master data tables
      • 33. If required: join master data tables to each other (e.g. join ‘Plant’ to ‘Material’)
      Step 2: (Analytical View)
      Create Cube-like view by joining attributes view to Fact data
      • Build a ‘Data Foundation’ based on transactional table
      • 34. Selection of ‘Measures’ (key figures) ...
      • 35. Add attributes (docking points for joining attribute views)
      this is basically your ‘fact table’ (key figures
      and dimension IDs)
      • Join attribute views to data foundation
      • 36. Looks a bit like a star schema
    • Attribute Views...... are the reusable dimensions used for analysis. (Time, Account, Product)
      © SAP AG 2011
      • What is an Attribute View?
      Attributes add context to data.
      Can be regarded as Master Data tables
      Can be linked to fact tables in Analytical Views
    • 37. Modeling for HANA 1.0Using In-Memory Computing Studio
      Step 3: (Calculation View) / Optional
      If joins are not sufficient create a Calculation View that is something that looks like a View and has SQL Script inside
      • Composite view of other views (tables, re-use join, olap views)
      • 38. Consists of a Graphical & Script based editor
      • 39. SQL Script is a HANA-specific functional script language
      • 40. Think of a ‘SELECT FROM HANA’ as a data flow
      • 41. JOIN or UNION two or more data flows
      • 42. Invoke other (built in CE or generic SQL) functions
    • Analytical View… are the multidimensional views that analyze values from single fact table
      © SAP AG 2011
      • An Analytic View can be regarded as a “cube”
      • 43. Multidimensional reporting model
      • 44. Fact table (data foundation) joined against modelled dimensions (attribute views)
      • 45. Analytic Views do not store data
      • 46. Data is read from the joined database tables
      • 47. Joins and calculated measures are evaluated at run time
      • 48. Master data for MDX/BICS are stored in system tables
    • Modeling for HANA 1.0Using In-Memory Computing Studio
      Step 4: Analytic Privileges
      • Analysis authorizations for row-level security
      • 49. Can be based on attributes in analytic views
      • 50. Analytic privilege is always a concrete implementation
      • 51. I.e. Specific authorization for specified values of given attribute
      • 52.  you have to create privileges for each group of users
    • 2 Types of Calculation Views
      © SAP AG 2011
      GRAPHICAL
      SQL Script
      • Composite views, re-uses Analytical and Attribute views
      • 53. SQL / SQL Script / Custom Functions
      UNION
      Analytical View
      UNION
      Analytical View
    • 54. How to build content
      Recommended
      Not recommended
      Calculation View
      Analytical View
      Tables
      Attribute View
      © SAP AG 2011
    • 55. Architecture OverviewReporting
      SAP HANA Studio
      Clients
      MS Excel
      BI4 Explorer
      Modeling
      Administration
      SAP BI4 universes (WebI,...)
      Dashboard Design
      BI4 Analysis
      ERP
      SAP HANA Appliance
      Replication Agent
      SLT Add-on
      SAP HANA Database
      Session Management
      Log
      ERP DB
      Transaction Manager
      Request Processing / Execution Control
      Replication Server
      SQL Parser
      MDX
      Authorization Manager
      Business Objects Enterprise
      SQL Script
      Calc Engine
      Load Controller
      Relational Engines
      SBO Information Design Tool
      Data Services Designer
      Metadata Manager
      Row Store
      Column Store
      Persistence Layer
      Logger
      Page Management
      Data Services
      SBO BI4 servers ( program for client)
      Disk Storage
      Data Volumes
      Log Volumes
      Other Source Systems
      SAP NetWeaver BW
      3rd Party
    • 56. Reporting on HANA Client and connectivity options
      © SAP AG 2009
      Web Intelligence
      Crystal Reports
      for Enterprise
      Are part of SAP BusinessObjects BI 4.0
      Dashboards
      Analysis Office v1.1
      Semantic Layer (universe UNX)
      Excel
      Explorer
      Crystal Reports 2011
      BICS
      ODBC
      JDBC
      JDBC
      ODBC
      JDBC
      ODBO
      ODBC
      MDX
      SQL
      SQL
      SQL
      SQL
      SAP HANA
      SAP In-memory Computing Engine
    • 57. Reporting on HANA SAP BusinessObjects BI4.0 Reporting Clients
      © SAP AG 2009
      Professionally Informed
      Search &
      Exploration
      Dashboarding &
      Visualization
      EnterpriseReporting
      Ad-Hoc QRA
      Crystal Reports
      Dashboard Design (Xcelsius)
      Executives &
      Managers
      Explorer
      Web Intelligence (Interactive Analysis)
      InformationConsumers
      Business Analysts
      Technically Capable
      Guided
      Free
      Interactive Experience
    • 58. Reporting on HANANative Excel interface - Pivot Tables (ODBO)
      Multidimensional reporting is available via Excel Pivot Tables
      This has the advantage of „quick and dirty“ cross-tab style reporting via Excel
      Numerous disadvantages exist
      The report definition is only avalable locally (workarounds exist)
      Subject to performance limitations of the desktop machine where Excel runs
      Pivot Tables can be initiated numerous ways but primary entry point is via the Excel DATA menu option.
      © SAP AG 2009
    • 59. SAP BusinessObjects Analysis, Office Edition
      © SAP AG 2009
    • 60. SAP BusinessObjects Analysis, Office Edition
      Access Analytic and Calculation Views from Analysis Office (MS Excel or Powerpoint) via a locally defined ODBC connection
      © SAP AG 2009
    • 61. What is BusinessObjects Explorer?It’s search against BI…
      Use familiar key-word search to find business information
      • Answers “on-the-fly” and investigative questions
      Searches directly on pre-indexed data
      • No previous reports or metrics need exist
      • 62. Provides fast search and exploration
      Searches across all data sources
      • Any universe accessible source
      • 63. Any SAP NetWeaver BW Accelerator accessible source
      • 64. And of course any accessible HANA system
    • …and Then It’s Exploration Of the Results
      Intuitively explore on data
      • No data model or data knowledge required
      Automated relevancy of results
      • Most relevant information is displayed first
      • 65. Best chart type auto generated
      Share insights with others
      • Export to CSV or image
      • 66. Save it locally as a browser bookmark
      • 67. One-click to send a link to the results by email
    • Architecture OverviewAdministration
      SAP HANA Studio
      MS Excel
      BI4 Explorer
      Modeling
      Administration
      SAP BI4 universes (WebI,...)
      Dashboard Design
      BI4 Analysis
      ERP
      SAP HANA Appliance
      Replication Agent
      SLT Add-on
      SAP HANA Database
      Session Management
      Log
      ERP DB
      Transaction Manager
      Request Processing / Execution Control
      Replication Server
      SQL Parser
      MDX
      Authorization Manager
      Business Objects Enterprise
      SQL Script
      Calc Engine
      Load Controller
      Relational Engines
      SBO Information Design Tool
      Data Services Designer
      Metadata Manager
      Row Store
      Column Store
      Persistence Layer
      Logger
      Page Management
      Data Services
      SBO BI4 servers ( program for client)
      Disk Storage
      Data Volumes
      Log Volumes
      Other Source Systems
      SAP NetWeaver BW
      3rd Party
    • 68. MotivationThreats
      Internal Threats
      • 80-90% of all attacks/security breaches come from inside the intranet
      • 69. Examples
      • 70. Unauthorized access to data
      • 71. Employees looking at salary tables
      • 72. External consultants gaining access to sensitive internal information
      • 73. Unauthorized data changes
      • 74. Employees covering their own mistakes
      • 75. Privilege abuse Data Import/Export
      • 76. Most security breaches come from company-internal power users (DBAs)
      • 77. By assigning themselves additional privileges or roles, or
      • 78. Log on as different users
      External Threats
      • Hackers
    • MotivationTraceability
      Main requirement to audit a system
      • Traceability of actions performed in that system
      • 79. Who did or tried to do what when?
      • 80. Example of actions to be audited
      • 81. Changes of a users’ authorization
      • 82. Creation or deletion of database objects
      • 83. Authentification of users
      • 84. Changes of the system configuration
      • 85. Changes of the audit configuration
      • 86. Access to or alteration of sensitive information
    • Auditing infrastructure
      Extensible auditing infrastructure
      • Audit trails
      • 87. Currently stored via syslog
      • 88. Syslog is a standard mechanism for logging program messages on Unix/Linux
    • User ProvisioningHow to get Users into the System
      Creating Named Users in HANA
      Actual Database Users
      Create via SAP HANA Studio
      Or using standard SQL statements
      Authentication Methods
      User / Password
      Set up and manage passwords using SAP HANA Studio or SQL
      Kerberos Authentication
      Certificate-based
      Requires Named User in HANA DB
    • 89. Events that are audited
      Logging of successful and unsuccessful events
    • Audit TrailSyslog example
      • Preparation steps
      1. Create audit policy
      CREATE AUDIT POLICY policyAdministratePrincipals AUDITING ALL CREATE ROLE, DROP ROLE, CREATE USER, DROP USER LEVEL Critical;
      2. Activate audit
      ALTER AUDIT POLICY policyAdministratePrincipals ENABLE;
      3. As SYSTEM user, create new user TESTUSER3
      • Verifying the result in Syslog output
      • 103. Syslog output file: /var/log/messages
      • 104. Csv-compatible format
      May 30 11:57:06 LU00252616 HDB[5212]: 30.05.2011 09:57:06 641 Mon;indexserver;lu00252616;B01;01;30103;POLICYADMINISTRATEPRINCIPALS;CreateDropPrincipalEvent;Critical;CreateUser;SYSTEM;;;;NON GRANTABLE;;TESTUSER3;Successful;;;;;;;create user TESTUSER3 identified by XXXXXXXXXXXXX;
      Search keyword ‘HDB[‘ in syslog
    • 105. User ManagementUser and Role Concept
      User
      Roles allow grouping privileges
      Create roles for specific tasks, e.g.
      Create data models (on a given subset of the data)
      Activate data models
      Manage users
      Export/Import
      All types of privileges can be granted to a role
      Individual privileges
      Roles ( create a hierarchy of roles)
      Roles / privileges can be assigned to users
      User / Role management are closely related
      Reflected in almost identical editor
      Role: edit + activate
      Role: editmodel
      Role: activatemodel
      Package:activate
      SQL:writeruntimeobject
      Package:create/ editmodels
      SQL:select
    • 106. Introduction to HANA
      Core Functionalities
      Use cases
      A Typical SAP Landscape Discussion
      HANA Roadmap
    • 107. SAP HANA asAcceleratorfor SAP ApplicationsExample: CO-PA Accelerated by SAP HANA
      SAP ECC on legacy DB with secondary DB Connection into HANA
      BI 4.0 (optional)
      SAP GUI
      SAP ECC
      Analytics
      Drill-down reporting
      COPA Application
      Generate HANA model
      Aggregation Levels
      Read Interface
      Optional: LT Replication
      SAP HANA Database
      Calculation Engine
      Secondary DB connectionRead / write
      Primary DB connectionRead / write
      Aggregation Engine
      Analytic indexes
      DBMS
      Redundant copy of ECC tables
      • Data duplicatedinto SAP HANA
      • 108. Read interfacesaccesses SAP HANA ifavailable
      This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement.
    • 109. DBMS
      SAP HANA as Primary DB in Application ServerFirst example: BW 7.30 running on HANA …expected soon
      SAP NetWeaver BW as a HANA based system (with “built-in” BWA)
      SAP NetWeaver BW
      HANA
      DW Management
      Calculation Engine
      Aggregation Engine
      Analytic indexes
      Analytic
      Engine
      Includes SAP NetWeaver BW Accelerator functionality
      Data Store Objects
      Master Data
      Metadata
      InfoCube Index


      Single Data Management for Row- and Column based storage 
      DBMS
      • Integrated engine for data management and in-memory processing of analytical capabilities
      • 110. Pure DB conversion. No re-implementation required.
      This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement.
    • 111. Introduction to HANA
      Core Functionalities
      Use cases
      A Typical SAP Landscape Discussion
      HANA Roadmap
    • 112. Your SAP Environment Today
      SAP BW
      InfoCubes
      ODS
      Traditional DB
      Oracle, DB2, TD, SQL Server, ASE
      SAP ECC
      Other
      Non-SAP
      Traditional DB
      Oracle, DB2, SQL Server, ASE
      Traditional DB
      Oracle, DB2, SQL Server, ASE
    • 113. With SAP BWA and Explorer
      SAP BI 4.0
      SAP BW
      Explorer
      InfoCubes
      BWA
      ODS
      Traditional DB
      Oracle, DB2, TD, SQL Server, ASE
      SAP ECC
      Other
      Non-SAP
      Traditional DB
      Oracle, DB2, SQL Server, ASE
      Traditional DB
      Oracle, DB2, SQL Server, ASE
    • 114. Accelerate All BW Content with SAP BW 7.3
      SAP BI 4.0
      SAP BW
      Explorer
      InfoCubes
      BWA
      BWA
      ODS
      Traditional DB
      Oracle, DB2, TD, SQL Server, ASE
      SAP ECC
      Other
      Non-SAP
      Traditional DB
      Oracle, DB2, SQL Server, ASE
      Traditional DB
      Oracle, DB2, SQL Server, ASE
    • 115. Low Latency Operational ReportingSAP HANA
      SAP BI 4.0
      SAP BW
      Explorer
      InfoCubes
      BWA
      BWA
      Agile Data Mart
      ODS
      SAP HANA
      Traditional DB
      Oracle, DB2, TD, SQL Server, ASE
      SAP ECC
      Other
      Non-SAP
      Traditional DB
      Oracle, DB2, SQL Server, ASE
      Traditional DB
      Oracle, DB2, SQL Server, ASE
    • 116. In-Memory Applications with SAP HANA
      SAP BI 4.0
      SAP BW
      Explorer
      InfoCubes
      BWA
      BWA
      Agile Data Mart
      In-Memory
      Apps
      ODS
      SAP HANA
      1.0
      Traditional DB
      Oracle, DB2, TD, SQL Server, ASE
      SAP ECC
      Other
      Non-SAP
      Traditional DB
      Oracle, DB2, SQL Server, ASE
      Traditional DB
      Oracle, DB2, SQL Server, ASE
    • 117. SimplifySingle HANA Platform for All Analytical Apps
      SAP BI 4.0
      SAP BW
      InfoCubes
      Agile Data Mart
      In-Memory
      Apps
      ODS
      SAP HANA
      SAP ECC
      Other
      Non-SAP
      Traditional DB
      Oracle, DB2, SQL Server, ASE
      Traditional DB
      Oracle, DB2, SQL Server, ASE
    • 118. SimplifySingle HANA Platform for All Analytical Apps
      SAP BI 4.0
      Enterprise Data Warehouse
      Sybase IQ
      SAP BW
      InfoCubes
      Agile Data Mart
      In-Memory
      Apps
      ODS
      SAP HANA
      SAP ECC
      Other
      Non-SAP
      Traditional DB
      Oracle, DB2, SQL Server, ASE
      Traditional DB
      Oracle, DB2, SQL Server, ASE
    • 119. Simplify All SAP Applications
      SAP BI 4.0
      SAP BW
      InfoCubes
      Agile Data Mart
      In-Memory
      Apps
      SAP ECC
      ODS
      SAP HANA
      Other
      Non-SAP
      Traditional DB
      Oracle, DB2, SQL Server, ASE
    • 120. Introduction to HANA
      Core Functionalities
      Use cases
      A Typical SAP Landscape Discussion
      HANA Roadmap
    • 121. What’s New in HANA 1.0 GA
      Link to Main Presentation
      Improved supportability
      Error tracking & performance tracing
      Unified tracing capabilities
      Improved SQL Script support
      Unified stored procedure language ( SQL script V2)
      Procedural extensions to SQL script V2
      Improved optimizer
      Massively improved column/row optimization ( i.e. full outer join optimizations)
      All major functionalities are supported with “clean” SQL
      Extended model support for HANA appliance ( i.e. left outer join support in OLAP engine)
    • 122. What’s New in HANA 1.0 SPS 2
      Link to Main Presentation
      Distribution
      Distributed NewDB on one or multiple nodes
      Support of table and range-based partitioning
      Automatic landscape reorganization
      Back-up & Recovery and cold standby distributed scenarios
      Trigger-based Data replication
      Incorporation of SLT Basis
      Security Auditing
      • Extensible auditing infrastructure
      • 123. Auditing of authorization changes
    • What’s New in HANA 1.0 SPS 3
      Link to Main Presentation
      Text search engine
      Main memory text search engine available in NewDB
      Full SQL integration
      Freestyle & other search capabilities similar to TREX engine
      Strong cooperation with Enterprise Search and FuzzyLogic team
      BW support
      NewDB as database for BW on NW 7.30
      In-memory optimized DSO objects
      New C++ data load mechanism ( DSO activation)
      New “number range’ handling
      C++ version of BW data compaction
      In-memory optimized InfoCubes: Faster data loads and simplified modeling
      Piush down of OLAP engine into NewDB
      -> NewDB will be by far the fastest DB for a 7.30 BW system
      Information Composer
      Key user data manipulation and modeling
      System R integration
      Integrated LCM
      Live Update service
    • 124. What’s New in HANA 1.0 SPS 3
      Link to Main Presentation
      Live Cache Integration
      LifeCache integrated with full transactional consistency
      First version available mid of May
      Extended LC usage in later versions
      Disc tables
      Disc tables with limited functionality
      Used for aged data and rarely used data
      New implementation based on MaxDB knowledge and experience
      Business functions
      Currency/Unit conversion, calendar, fiscal period, number range
      Statistic functions
      Staging area
      Time dependant functionalities
      Planning engine
      Operations like Disaggregation, copy, write-back
      Supports BW – IP and ByD
      Includes linear equation solver
    • 125. What’s New in HANA 1.0 SPS 3
      Link to Main Presentation
      NGAP support
      Fast data exchange between appserver and database
      SQL script support in appserver
      Better data type compatibility ( text, GUID, decfloat, dates)
      Back-up & Recovery and Security
      Point-in-time recovery
      Log backups
      Additional auditing functions
      SSL connection encryption with certificates for client connections
      HANA-SAP IDM integration for user provisioning into IMDB
    • 126. “Innovation“
      Mid-Term (Plan)
      “Transformation”
      Longer-Term (Plan)
      “Renovation”
      SAP HANA 1.0
      Ramp-Up since Dec 2010
      One Store for Data and Analytics
      • SAP HANA only persistence layer for SAP Business Suite
      • 127. SAP Business Suite optimized for in-memory computing
      In-Memory Analytics
      • SAP HANA real-time operational analytics
      • 128. Complete BI Suite with BI 4 runs on SAP HANA
      Next-gen Applications
      • SAP BW fully running on SAP HANA
      • 129. SAP HANA platform for in-memory apps
      • 130. SAP Business Suite runs on SAP HANA
      • 131. Further optimization of BI 4 Suite for SAP HANA
      • 132. Industry and LOB Analytic Apps
      Capabilities
      • Flexible real time analysis of operations at non-aggregated level
      • 133. Real-Time operational planning and simulation capabilities: link to execution
      • 134. Primary persistence and optimized for SAP BW
      • 135. Reduced landscape complexity
      • 136. Value chain transformation
      Benefits
      SAP In-Memory StrategyProduct Strategy and Plan
    • 137. Obrigado!
      Contato:
      Henrique Pinto
      henrique.pinto@sap.com