SAP BW on HANA : Complete reference guide

Size: px
Start display at page:

Download "SAP BW on HANA : Complete reference guide"

Transcription

1 SAP BW on HANA : Complete reference guide Applies to: SAP BW 7.4, SAP HANA, BW on HANA, BW 7.3 Summary There have been many architecture level changes in SAP BW 7.4. To enable our customers to understand there is a need for complete overview about BW on HANA. Hence this article series will help you to explore BW on HANA and its unique features. It starts with BW, and then explores HANA, Finally explore BW on HANA. It gives a nutshell overview all important objects available in BW 7.4. This can be handy reference to major BW on HANA based project. Author: P. Manivannan Company: SAP Labs India Created on: 27 Aug 2015 Author Bio P Manivannan is currently working as BW Consultnat in SAP Labs India. He specializes in the BW Warehouse management area. Manivannan has very good knowledge in BW data modeling stratergies and reporting. He has been a working as lead in many end to end succesful SAP BW implementation across various industries. His overall expertise includes ABAP and other functional areas of SAP. He has also been in many complex CoE ( Center of Expertise ) projects in SAP Labs India for major global SAP customers. 1

2 Table of Contents SAP BW Overview... 3 The source of data for BW system... 4 Data flow in BI system... 5 SAP HANA Overview... 6 Exploring In-Memory analytics... 8 BW Powered by HANA The LSA and LSA++ layer LSA Layer An BW EDW with LSA is perceived as highly valuable but LSA++ Layer Open ODS layer EDW Data Propagation Layer in the LSA Architected Data Mart Layer in the LSA Virtual Data Mart Layer LSA to LSA SAP HANA Modeling in detail Data, View, Procedure and Analytic privileges overview Engines in SAP HANA BW on HANA Objects in detail Composite provider Open ODS InfoSets and HANA MultiProvider and HANA Advanced DSO New features in SAP BW Consuming HANA models in BW Transient provider Virtual provider Putting it all together, what will be the change!! Related Content Copyright

3 SAP BW Overview SAP BW is the name of DataWarehouse solution / Business intelligence / OLAP reporting product from SAP. It has various powerful features like flexible reporting tools, easy SAP ERP integration through the pre delivered business content across various application modules. It has planning functionalities and other essential features that made it one of the leading business intelligence tools in the market. The reporting, analysis, and interpretation of business data is of central importance to a company in guaranteeing its competitive edge, optimizing processes, and enabling it to react quickly and in line with the market. With Business Intelligence (BI), SAP NetWeaver provides data warehousing functionality, a business intelligence platform, and a suite of business intelligence tools with which an enterprise can attain these goals. Relevant business information from productive SAP applications and all external data sources can be integrated, transformed, and consolidated in BI with the toolset provided. BI provides flexible reporting, analysis, and planning tools to support you in evaluating and interpreting data, as well as facilitating its distribution. Businesses are able to make well-founded decisions and determine target-orientated activities on the basis of this analysis. The NetWeaver architecture and the positioning of BI in it is shown here. 3

4 The detailed BI Architecture can be seen here. The source of data for BW system Data can be extracted from SAP, Non SAP, DBMS, Web service and other flat files into BW to do analytical reporting. It can be seen here as below 4

5 Data flow in BI system When the data is extracted to BW, there are many layers to transform and cleanse the data as given below. InfoObjects: The basic building blocks in BW system and divided into characteristics & Key figures. Datasource: It is a structure which is created in the source system and replicated to the BW system InfoSource: A non-persistent structure consisting of InfoObjects for joining two transformations. Use PSA: Persistent staging area, it is the first inbound layer into BW Scheduler: It is used to schedule the BW extraction. It has options for Init, Full and delta extraction. InfoPackage: It is used to schedule a extraction from SAP Source system or Non SAP source system. Monitor: The data extraction status and result can be checked here. DSO: It is the InfoProvider that contains the data InfoCube: It is an InfoProvider which is modeled based in the extended star schema. DTP: It is used to extract data within the BW layer. Transformation: The transformation logic is done by this object and it exists between any two DTP Process chain: It is a BW tool to automate the extraction process Open hub destination: It is the object that allows you to distribute data from a BI system to non-sap data marts, analytical applications, and other applications Note: When you have any issues on the above warehouse management layer, raise an OSS incident in component BW-WHM-DST and its related fourth level sub component. The fourth level depends on BW object like DTP, Process chain etc etc. 5

6 SAP HANA Overview SAP HANA is an in-memory data platform that is deployable as an on premise appliance, or in the cloud. It is a revolutionary platform that's best suited for performing real-time analytics, and developing and deploying real-time applications. HANA is The Platform for Next-Generation Applications and Analytics SAP HANA converges database and application platform capabilities in-memory to transform transactions, analytics, text analysis, predictive and spatial processing so businesses can operate in real-time. By eliminating the divide between transactions and analytics, SAP HANA allows you to answer any business question anywhere in real time To learn more on HANA you can refer many official sites like hana.sap.com it is updated regularly.. What is the reason for performance degradation? To overcome the I/O bottleneck the platform is changed like this. This avoids the bottleneck between CPU and disks. The advantage of CPU Multicore, parallel processing helps in further performance gain. 6

7 So this helps to achieve all objectives equally broad and deep analysis along with real time and high speed computing put together in a simple method. That is the power of HANA. 7

8 So we get real time analytics of all real time application in a real time platform. This helps to transform customers business into a real time business. Exploring In-Memory analytics In Business intelligence (BI), in-memory analytics is a methodology used to solve complex and timesensitive business scenarios. It works by increasing the speed, performance and reliability when querying data. With SAP In-Memory technology there are various advantages as described below. It is a combination of real time analytics with speed and deep data. 8

9 SAP In memory database overview This combines the advantages of row store and column store technology. OLTP systems instantly record business events as they happen, such as the sale of a piece of inventory. As such, system designs focus on quickly handling large numbers of small, simultaneous transactions. OLAP systems provide analysis of the data provided by OLTP systems to support business decisions. They are designed to handle a relatively small number of often complex transactions. How data is stored in Row and column store database? In row storage, the data sequence consists of the data fields in one table row. In column storage, the data sequence consists of the entries in one table column. Columnar storage may be more efficient in the common case where a given column includes only a relatively Small number of distinct values. Consider this is as the table 9

10 How this table can be represented in Row and column store database? BW Powered by HANA This makes BW smarter, simpler and more efficient. Some of the advantages includes Alignment of database and application server to enable push-down of functionalities SAP HANA takes over processing of major data warehousing tasks Excellent performance in reporting and data loading Simplifies, increases agility, reduces complexity, and combines the strengths of SAP BW and SAP HANA In BW powered by HANA you can get the best of both worlds SAP BW contribution to architecture Manage complexity & semantics Govern the lifecycle SAP HANA contribution to architecture High performance on large data Maximum flexibility, agile modeling So how does the change look when you move to In-Memory based? 10

11 The LSA and LSA++ layer This is the part that you need to know importantly. This helps you to do effective data modeling in implementation projects. LSA Layer An BW EDW with LSA is perceived as highly valuable but Costly: building it, moving steadily data to and within the EDW Not flexible enough: EDW/LSA standards, central development, overall responsiveness to business needs (operational & agile BI) There was DTP and transformation, DSO and cube which were standard BW Objects. This layer was used prior to HANA 11

12 12

13 LSA++ Layer LSA++ inherits the service definitions of LSA EDW Layers that stand for reliability & Consistency: EDW Transformation Layer (Link between source-model and EDW-model) (EDW) Corporate Memory (Persistent ) (EDW) Propagation Layer (Persistent ) Business Transformation Layer (Link between EDW-model and Data Mart model) Architected Data Mart Layer (Persistent 13

14 Open ODS layer In the LSA++ for BW on SAP HANA, the Open ODS layer is used to integrate data into the Data Warehouse. This offers the same functionality as the classic data acquisition layer, but with more flexible data integration possibilities. This layer encompasses the classic BW data acquisition layer, but it also offers more extensive and more flexible options for data integration: everything from consuming and combining to physical integration. This allows data sources to be consumed virtually: the data sources are made known to the BW by means of a modeling object named Open ODS view. They can be used directly in BW for query purposes, for example, without needing for separate BW persistence. These data models can be located in an external schema (of the SAP HANA database in BW), which is not managed by BW. Alternatively, the models can be located in other databases, which are connected to the SAP HANA database in BW using SAP HANA Smart Data Access. EDW Data Propagation Layer in the LSA++ In the LSA++, the data propagation layer consists of SAP HANA-optimized DataStore objects. This offers the following advantages: Greater flexibility due to faster activation times and loading times Flexible modeling Greater flexibility as all data is visible in the data propagation layer Greater flexibility due to queries directly on the data propagation layer Architected Data Mart Layer in the LSA++ In the LSA++, the data propagation layer consists of SAP HANA-optimized InfoCubes and/or SAP HANAoptimized DataStore objects (in the Business Transformation layer). Virtual Data Mart Layer If you are using an SAP HANA database for your BW system, the virtual data mart layer replaces the virtualization layer. The virtual data mart layer contains all InfoProviders that combine data using join or union, without saving the result: MultiProvider, Composite Provider access data directly in the SAP HANA database, to allow queries on the data: Composite Provider, Open ODS View Open ODS View Open ODS views enable you to define BW data models for objects like database tables. database views or BW DataSources (for direct access). These data models allow flexible integration without the need to create InfoObjects. This flexible type of data integration makes it possible to consume external data sources in BW without staging, combine data sources with BW models and physically integrate (load) external data sources by creating DataSources. Advanced DSO The DataStore object (advanced) consists of a maximum three tables: the inbound table, the change log and he table of active data. You might not need all three tables. This depends on how you want to use the DataStore object. 14

15 Composite provider In a Composite Provider, you can merge data from BW InfoProviders with data from SAP HANA views using union and join, or just merge data from BW InfoProviders and SAP HANA views. The Composite Provider's join and union operations are performed in SAP HANA. You can run queries on Composite Providers just like on all other BW InfoProviders. You acquire SQL access to the data if you generate a SAP HANA view from the Composite Provider. ODP It is a data provisioning aspect that allows you to eliminate PSA as a staging area. It enables extract once deploy many architecture. It has unified configuration and monitoring for all provider and subscriber types. 15

16 LSA to LSA Migrate to HANA optimized object 2. Streamline EDW core ( Reduce number of persistent layer) 3. Enhance virtualization layer (Like using composite provider etc) 4. Introduce additional ++ layer ( Open ODS, Agile data mart, Work space) 5. Resulting LSA ++ ready SAP HANA Modeling in detail We have below modeling terminologies in HANA Data View Procedure Analytic privileges Data, View, Procedure and Analytic privileges overview Data Here we have Attribute and measures Attributes: It is a descriptive data; it is like characteristics in BW. We also have calculated attributes Measures: Data can be quantified and calculated, It is like Key figure in BW We have calculated measures and restricted measures. View We have below View Attribute View Analytic view Calculation view Attribute View: If you see like BW, Attribute view is like dimension table, but the difference is that it can be reused and not struck up to a single model. This can be regarded as master data tables. It can be linked to fact table in analytic views Analytic views If you see like BW, Analytic view is compared to InfoCube (or) Infoset in a ERP. It contain once central fact table with transaction to report on with number of tables or attribute views. 16

17 Analytic view does not store data, it is read from join of tables Joins and calculated measures are done in run time. Calculation view This can be referred as combination of tables, attribute views, analytical views to deliver complex business requirement. This is similar to MultiProvider There are 2 types of calculation view Graphical calculation view (No SQL) Script calculation view ( SQL, CE Functions). Procedures this is functions which are reusable witting script calculation views. Analytic privileges It determines who has access to which report including restriction on row level data. Engines in SAP HANA OLAP Engine > this called when any query is run on Analytic view Join Engine > Used when you execute any Attribute view Calculation engine > this is used to execute Calculation view in SAP HANA Row engine > Does operation on row based table, Window function SQL Engine > Native SQL BW on HANA Objects in detail Composite provider If we need to join during query execution, before BW 7.30, we have below options MultiProvider > Based on Union operation Infoset > Based on Join operation But from BW 7.30, HANA Composite provider was introduced. Composite provider in nutshell: It is an InfoProvider; you can join InfoObjects, DSO, SPO (Semantically partitioned objects), HANA Views like Analytic or calculation views using Join (or) Union to make data available for reporting. The editor for composite provider is purely based on Eclipse which is shipped as a part of HANA studio It is NOT possible to create composite provider in BW Administrative workbench. Open ODS Open ODS enables us to integrate external data in your DataWarehouse without need to stage data first. It also offers the flexibility to enrich external data with OLAP functionality even though data is not in data warehouse. 17

18 When to use Open ODS? It is used in case when we have multiple non SAP Disparate sources and do not want data to reside in my DataWarehouse but we need to leverage the BW core capabilities like master data and OLAP aggregation Open ODS view is useful when you want to bring a DB table or View into BW system We can create open ODS view in BW and HANA system. When to use composite provider and Open ODS view? Composite provider is well suited in case if the information is already in place Open ODS view is suited in case the DB tables are still in raw format. InfoSets and HANA InfoSets are NOT optimized to use in combination with HANA DB. The reason for above is once you define Infoset in HANA DB the join logic is same like the traditional RDBMS, So there will not be much benefit in using HANA. The efficient approach is to push down the join execution to HANA DB level by defining a composite provider. MultiProvider and HANA There is no run time difference between composite provider and MultiProvider as analytic manager in BW is well optimized for HANA. Hence there is no need to migrate existing MultiProvider into composite provider. Advanced DSO Advanced DSO Consist of maximum three tables Inbound table Change log Table of active data Note: We might not need all three tables; it depends on how we model the DSO. Data flow in Advanced DSO Data is initially loaded in Inbound table The data is either read from inbound table directly or it is activated first and then read from table of active data The change log contains the change history for the delta update from DSO to other target Important settings in Advanced DSO Write change log the delta is saved in change log, this is used to extract delta. Keep Inbound data and extract from Inbound table No data is saved in change log and the extraction is read from inbound for delta Unique data records you can choose this if you only load unique data records All characteristics as key, reporting on union of inbound and active table Here all characteristics are included in key, system across union of inbound and active tables in query. You should only load additive delta 18

19 Data is aggregated This is compared to cube Inbound as extended table if you use Sybase IQ as extended storage for BW this can be choose. It means data is stored only in persistency layer. Smart data access Smart data access in a virtualization technique. SDA enables SAP HANA to combine data from heterogeneous sources like Teradata, Sybase IQ, and Hadoop etc. Smart data access is a technology which enables remote data access as if they are local tables in SAP HANA without copying into HANA. Data required from other sources will remain in virtual tables Virtual tables will point to remote tables in different data sources. It will enable real time data access; it will not affect SAP DB. You can write SQL queries in SAP HANA which could operate on virtual table. HANA query processor optimizes the query then extract relevant part of query in the target DB, Return the result of query to HANA and complete operation. 19

20 New features available in SAP BW 7.4 BW Modeling tool in eclipse ( New) Open ODS View ( New) Composite provider ( New) Generation of SAP HANA Views ( New) Virtual master data ( Enhanced) Open hub destination ( Enhanced) Transformation ( Changed) Master data maintenance ( New) DataWarehouse workbench ( Enhanced) DB Connect ( Enhanced) Replication of DataSource ( Enhanced) Transfer using ODP (Enhanced) BW Provisioning from SAP System with ODP (New) BW data mart with ODP ( New) SAP HANA smart data access ( New ) Remodeling ( Enhanced) Consuming HANA models in BW Transient provider If you want to use SAP BW OLAP functions to report on SAP HANA Analytic or calculation view, you can publish these SAP HANA models to SAP BW system. Useful transaction: RSDD_HM_PUBLISH. Note: Transient provider cannot be transported; it has to be created in each system. Key features of transient provider Its meta data in BW is not persisted but always generated at run time BEx queries built on top can adapt to change automatically as far as possible Navigational attributes of assigned InfoObjects cannot be used Cannot be used in MultiProvider Can only be used in composite provider in order to merge with other InfoProvider It is exposed to BEx and BI tools Virtual provider It is a type of InfoProvider which reads data from BW InfoCube. Its characteristics and key figure are created based on data field in the HANA Model and InfoCube is constructed using the characteristics as dimensions and key figures duly filled in. 20

21 Advantages of Virtual provider: When compared to transient provider here InfoCube acts as data provider which helps in multi-level reporting We can create virtual provider based on SAP HANA model. This can be used in MultiProvider. Navigational attributes can be used BW Analysis authorization apply This can be transported Data read across at query runtime is not through SQL but by analysis APU that read InfoCube, DSO. So we can push down operation to HANA instead of doing in application server. If you see the above picture you can clearly understand when to use Transient provider, Virtual provider and how composite provider can be used in BW 7.4. You can also see that query can be built on top of composite provider, Transient provider and MultiProvider. Do see this picture many times to get more clarity of BW on HANA modeling scenarios; it will help to design effective HANA modeling in major projects. 21

22 Putting it all together, what will be the change in BW 7.4!! Let us see how SAP BW on RDBMS is going to be converted in SAP BW 7.4 on HANA. This diagram will help to choose the BW 7.4 Objects when modeling a HANA based BW system. These objects will be replaced SAP BW on RDBMS SAP BW 7.4 on HANA Composite provider Composite provider MultiProvider Infoset Virtual provider Open ODS View c InfoObject InfoObject Hybrid Provider InfoCube DSO PSA Advanced DSO Conclusion The objective of this article is to present all the essential features of BW on HANA in a nut shell to assist consultants and architects to implement BW powered by HANA more effectively. I hope all major areas have been covered in this article. 22

23 Related Content SAP BW 7.4 Help page NetWeaver overview SAP BI Architecture HANA.SAP.COM Analyzing Business as It Happens, SAP and Intel LSA++ SCN Copyright 2015 SAP SE SE or an SAP SE affiliate company. All rights reserved. No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of SAP SE. The information contained herein may be changed without prior notice. Some software products marketed by SAP SE and its distributors contain proprietary software components of other software vendors. National product specifications may vary. These materials are provided by SAP SE and its affiliated companies ( SAP SE Group ) for informational purposes only, without representation or warranty of any kind, and SAP SE Group shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP SE Group products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty. SAP SE and other SAP SE products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE in Germany and other countries. Please see for additional trademark information and notices. 23

SAP BW 7.4 Real-Time Replication using Operational Data Provisioning (ODP)

SAP BW 7.4 Real-Time Replication using Operational Data Provisioning (ODP) SAP BW 7.4 Real-Time Replication using Operational Data Provisioning (ODP) Dr. Astrid Tschense-Österle, AGS SLO Product Management Marc Hartz, Senior Specialist SCE Rainer Uhle, BW Product Management May

More information

A Few Cool Features in BW 7.4 on HANA that Make a Difference

A Few Cool Features in BW 7.4 on HANA that Make a Difference A Few Cool Features in BW 7.4 on HANA that Make a Difference Here is a short summary of new functionality in BW 7.4 on HANA for those familiar with traditional SAP BW. I have collected and highlighted

More information

SAP HANA Live & SAP BW Data Integration A Case Study

SAP HANA Live & SAP BW Data Integration A Case Study SAP HANA Live & SAP BW Data Integration A Case Study Matthias Kretschmer, Andreas Tenholte, Jürgen Butsmann, Thomas Fleckenstein July 2014 Disclaimer This presentation outlines our general product direction

More information

SAP Business Warehouse Powered by SAP HANA for the Utilities Industry

SAP Business Warehouse Powered by SAP HANA for the Utilities Industry SAP White Paper Utilities Industry SAP Business Warehouse powered by SAP HANA SAP S/4HANA SAP Business Warehouse Powered by SAP HANA for the Utilities Industry Architecture design for utility-specific

More information

RDP300 - Real-Time Data Warehousing with SAP NetWeaver Business Warehouse 7.40. October 2013

RDP300 - Real-Time Data Warehousing with SAP NetWeaver Business Warehouse 7.40. October 2013 RDP300 - Real-Time Data Warehousing with SAP NetWeaver Business Warehouse 7.40 October 2013 Disclaimer This presentation outlines our general product direction and should not be relied on in making a purchase

More information

An Overview of SAP BW Powered by HANA. Al Weedman

An Overview of SAP BW Powered by HANA. Al Weedman An Overview of SAP BW Powered by HANA Al Weedman About BICP SAP HANA, BOBJ, and BW Implementations The BICP is a focused SAP Business Intelligence consulting services organization focused specifically

More information

SAP BW 7.4 SP8 powered by SAP HANA and Roadmap. Product Management SAP Business Warehouse, SAP SE

SAP BW 7.4 SP8 powered by SAP HANA and Roadmap. Product Management SAP Business Warehouse, SAP SE SAP BW 7.4 SP8 powered by SAP HANA and Roadmap Product Management SAP Business Warehouse, SAP SE Disclaimer This presentation outlines our general product direction and should not be relied on in making

More information

Exploring the Synergistic Relationships Between BPC, BW and HANA

Exploring the Synergistic Relationships Between BPC, BW and HANA September 9 11, 2013 Anaheim, California Exploring the Synergistic Relationships Between, BW and HANA Sheldon Edelstein SAP Database and Solution Management Learning Points SAP Business Planning and Consolidation

More information

BW362 SAP NetWeaver BW, powered by SAP HANA

BW362 SAP NetWeaver BW, powered by SAP HANA SAP NetWeaver BW, powered by SAP HANA SAP NetWeaver - Business Intelligence Course Version: 07 Course Duration: 5 Day(s) Publication Date: 05-08-2014 Publication Time: 1210 Copyright Copyright SAP AG.

More information

SAP BW 7.4 SP8-SP9 powered by SAP HANA and Roadmap. Lothar Henkes, Product Management SAP EDW (BW/HANA), SAP SE

SAP BW 7.4 SP8-SP9 powered by SAP HANA and Roadmap. Lothar Henkes, Product Management SAP EDW (BW/HANA), SAP SE SAP BW 7.4 SP8-SP9 powered by SAP HANA and Roadmap Lothar Henkes, Product Management SAP EDW (BW/HANA), SAP SE Disclaimer This presentation outlines our general product direction and should not be relied

More information

SAP S/4HANA Analytics & SAP BW Data Integration Overview and How To Guide

SAP S/4HANA Analytics & SAP BW Data Integration Overview and How To Guide SAP S/4HANA Analytics & SAP BW Data Integration Overview and How To Guide Jürgen Butsmann, Thomas Fleckenstein, Matthias Kretschmer, Andreas Tenholte, Ulrich Christ October 2015 Customer Legal disclaimer

More information

SAP BusinessObjects Cloud

SAP BusinessObjects Cloud Frequently Asked Questions SAP BusinessObjects Cloud SAP BusinessObjects Cloud To help customers Run Simple, SAP is breaking the limitations of the past. On October 20, 2015, we unveiled a new generation

More information

BW362 SAP BW powered by SAP HANA

BW362 SAP BW powered by SAP HANA SAP BW powered by SAP HANA SAP NetWeaver - Business Intelligence Course Version: 08 Course Duration: 5 Day(s) Publication Date: 2014 Publication Time: Copyright Copyright SAP AG. All rights reserved. No

More information

BW362. SAP BW powered by SAP HANA COURSE OUTLINE. Course Version: 10 Course Duration: 5 Day(s)

BW362. SAP BW powered by SAP HANA COURSE OUTLINE. Course Version: 10 Course Duration: 5 Day(s) BW362 SAP BW powered by SAP HANA. COURSE OUTLINE Course Version: 10 Course Duration: 5 Day(s) SAP Copyrights and Trademarks 2015 SAP SE. All rights reserved. No part of this publication may be reproduced

More information

DMM301 Benefits and Patterns of a Logical Data Warehouse with SAP BW on SAP HANA

DMM301 Benefits and Patterns of a Logical Data Warehouse with SAP BW on SAP HANA DMM301 Benefits and Patterns of a Logical Data Warehouse with SAP BW on SAP HANA Ulrich Christ/Product Management SAP EDW (BW/HANA) Public Disclaimer This presentation outlines our general product direction

More information

SAP HANA SPS 09 - What s New? HANA IM Services: SDI and SDQ

SAP HANA SPS 09 - What s New? HANA IM Services: SDI and SDQ SAP HANA SPS 09 - What s New? HANA IM Services: SDI and SDQ (Delta from SPS 08 to SPS 09) SAP HANA Product Management November, 2014 2014 SAP SE or an SAP affiliate company. All rights reserved. 1 Agenda

More information

A Practical Guide to SAP" NetWeaver Business Warehouse (BW) 7.0

A Practical Guide to SAP NetWeaver Business Warehouse (BW) 7.0 Bharat Patel, Amol Palekar, Shreekant Shiralkar A Practical Guide to SAP" NetWeaver Business Warehouse (BW) 7.0 Galileo Press Bonn Boston Preface 17 An Introduction to Business Intelligence 21 1.1 ABCD

More information

SAP BW Columnstore Optimized Flat Cube on Microsoft SQL Server

SAP BW Columnstore Optimized Flat Cube on Microsoft SQL Server SAP BW Columnstore Optimized Flat Cube on Microsoft SQL Server Applies to: SAP Business Warehouse 7.4 and higher running on Microsoft SQL Server 2014 and higher Summary The Columnstore Optimized Flat Cube

More information

Real-Time Enterprise Management with SAP Business Suite on the SAP HANA Platform

Real-Time Enterprise Management with SAP Business Suite on the SAP HANA Platform Real-Time Enterprise Management with SAP Business Suite on the SAP HANA Platform Jürgen Butsmann, Solution Owner, Member of Global Business Development Suite on SAP HANA, SAP October 9th, 2014 Public Agenda

More information

The Arts & Science of Tuning HANA models for Performance. Abani Pattanayak, SAP HANA CoE Nov 12, 2015

The Arts & Science of Tuning HANA models for Performance. Abani Pattanayak, SAP HANA CoE Nov 12, 2015 The Arts & Science of Tuning HANA models for Performance Abani Pattanayak, SAP HANA CoE Nov 12, 2015 Disclaimer This presentation outlines our general product direction and should not be relied on in making

More information

Innovate and Grow: SAP and Teradata

Innovate and Grow: SAP and Teradata Partners Innovate and Grow: SAP and Teradata Lily Gulik, Teradata Director, SAP Center of Excellence Wayne Boyle, Chief Technology Officer Strategy, Teradata R&D Table of Contents Introduction: The Integrated

More information

SAP BW 7.40 Near-Line Storage for SAP IQ What's New?

SAP BW 7.40 Near-Line Storage for SAP IQ What's New? SAP BW 7.40 Near-Line Storage for SAP IQ What's New? Rainer Uhle Product Management SAP EDW (BW / HANA), SAP SE Public Disclaimer This presentation outlines our general product direction and should not

More information

Provisional Master Data in Integrated Business Planning for SAP Simple Finance An Example-Based How-To Guide

Provisional Master Data in Integrated Business Planning for SAP Simple Finance An Example-Based How-To Guide Provisional Master Data in Integrated Business Planning for SAP Simple Finance An Example-Based How-To Guide Applies to: Integrated Business Planning in SAP Simple Finance Summary SAP customers who use

More information

SAP Business Intelligence Adoption V7.41:Software and Delivery Requirements. SAP Business Intelligence Adoption August 2015 English

SAP Business Intelligence Adoption V7.41:Software and Delivery Requirements. SAP Business Intelligence Adoption August 2015 English Business Intelligence Adoption August 2015 English Business Intelligence Adoption V7.41:Software and Delivery Requirements SE Dietmar-Hopp-Allee 16 69190 Walldorf Germany Document Revisions Date 0 6/26/2015

More information

SAP BusinessObjects Business Intelligence 4.1 One Strategy for Enterprise BI. May 2013

SAP BusinessObjects Business Intelligence 4.1 One Strategy for Enterprise BI. May 2013 SAP BusinessObjects Business Intelligence 4.1 One Strategy for Enterprise BI May 2013 SAP s Strategic Focus on Business Intelligence Core Self-service Mobile Extreme Social Core for innovation Complete

More information

Using In-Memory Data Fabric Architecture from SAP to Create Your Data Advantage

Using In-Memory Data Fabric Architecture from SAP to Create Your Data Advantage SAP HANA Using In-Memory Data Fabric Architecture from SAP to Create Your Data Advantage Deep analysis of data is making businesses like yours more competitive every day. We ve all heard the reasons: the

More information

SAP BW: The Real-time Data Application Platform How SAP BW uses the SAP database options

SAP BW: The Real-time Data Application Platform How SAP BW uses the SAP database options SAP BW: The Real-time Data Application Platform How SAP BW uses the SAP database options Roland Kramer - Product and Strategy - PM EDW/In-Memory July 2014 Disclaimer This presentation outlines our general

More information

Finding the signals in the noise. Niklas Packendorff @packendorff Solution Expert Analytics & Data Platform

Finding the signals in the noise. Niklas Packendorff @packendorff Solution Expert Analytics & Data Platform Finding the signals in the noise Niklas Packendorff @packendorff Solution Expert Analytics & Data Platform Legal disclaimer The information in this presentation is confidential and proprietary to SAP and

More information

ITM204 Post-Copy Automation for SAP NetWeaver Business Warehouse System Landscapes. October 2013

ITM204 Post-Copy Automation for SAP NetWeaver Business Warehouse System Landscapes. October 2013 ITM204 Post-Copy Automation for SAP NetWeaver Business Warehouse System Landscapes October 2013 Disclaimer This presentation outlines our general product direction and should not be relied on in making

More information

SAP S/4HANA Embedded Analytics

SAP S/4HANA Embedded Analytics Frequently Asked Questions November 2015, Version 1 EXTERNAL SAP S/4HANA Embedded Analytics The purpose of this document is to provide an external audience with a selection of frequently asked questions

More information

IMPLEMENTATION OF DATA WAREHOUSE SAP BW IN THE PRODUCTION COMPANY. Maria Kowal, Galina Setlak

IMPLEMENTATION OF DATA WAREHOUSE SAP BW IN THE PRODUCTION COMPANY. Maria Kowal, Galina Setlak 174 No:13 Intelligent Information and Engineering Systems IMPLEMENTATION OF DATA WAREHOUSE SAP BW IN THE PRODUCTION COMPANY Maria Kowal, Galina Setlak Abstract: in this paper the implementation of Data

More information

Using SQL Server 2014 In-Memory Optimized Columnstore with SAP BW

Using SQL Server 2014 In-Memory Optimized Columnstore with SAP BW Using SQL Server 2014 In-Memory Optimized Columnstore with SAP BW Applies to: SAP Business Warehouse 7.0 and higher running on Microsoft SQL Server 2014 and higher Summary SQL Server 2014 In-Memory Optimized

More information

SAP BusinessObjects BI Clients

SAP BusinessObjects BI Clients SAP BusinessObjects BI Clients April 2015 Customer Use this title slide only with an image BI Use Cases High Level View Agility Data Discovery Analyze and visualize data from multiple sources Data analysis

More information

Reimagining Business with SAP HANA Cloud Platform for the Internet of Things

Reimagining Business with SAP HANA Cloud Platform for the Internet of Things SAP Brief SAP HANA SAP HANA Cloud Platform for the Internet of Things Objectives Reimagining Business with SAP HANA Cloud Platform for the Internet of Things Connect, transform, and reimagine Connect,

More information

Providing real-time, built-in analytics with S/4HANA. Jürgen Thielemans, SAP Enterprise Architect SAP Belgium&Luxembourg

Providing real-time, built-in analytics with S/4HANA. Jürgen Thielemans, SAP Enterprise Architect SAP Belgium&Luxembourg Providing real-time, built-in analytics with S/4HANA Jürgen Thielemans, SAP Enterprise Architect SAP Belgium&Luxembourg SAP HANA Analytics Vision Situation today: OLTP and OLAP separated, one-way streets

More information

SAP BusinessObjects (BI) 4.1 on SAP HANA Piepaolo Vezzosi, SAP Product Strategy. Orange County Convention Center Orlando, Florida June 3-5, 2014

SAP BusinessObjects (BI) 4.1 on SAP HANA Piepaolo Vezzosi, SAP Product Strategy. Orange County Convention Center Orlando, Florida June 3-5, 2014 SAP BusinessObjects (BI) 4.1 on SAP HANA Piepaolo Vezzosi, SAP Product Strategy Orange County Convention Center Orlando, Florida June 3-5, 2014 Learning points SAP HANA scenarios for business intelligence

More information

Drive Performance and Growth with Scalable Solutions for Midsize Companies

Drive Performance and Growth with Scalable Solutions for Midsize Companies SAP Brief SAP s for Small Businesses and Midsize Companies SAP Business All-in-One s Objectives Drive Performance and Growth with Scalable s for Midsize Companies Manage every aspect of your business in

More information

SAP Cloud for Sales Integration to SAP ERP 6.0 End-to-end master data synchronization and process integration

SAP Cloud for Sales Integration to SAP ERP 6.0 End-to-end master data synchronization and process integration SAP Cloud for Integration to SAP ERP 6.0 End-to-end master data synchronization and process integration SAP Cloud for Accounts & Prospects Products Quotation Recent Orders SAP ERP Customer Material Pricing

More information

SAP HANA SAP s In-Memory Database. Dr. Martin Kittel, SAP HANA Development January 16, 2013

SAP HANA SAP s In-Memory Database. Dr. Martin Kittel, SAP HANA Development January 16, 2013 SAP HANA SAP s In-Memory Database Dr. Martin Kittel, SAP HANA Development January 16, 2013 Disclaimer This presentation outlines our general product direction and should not be relied on in making a purchase

More information

CBW NLS High Speed Query Access to Database and Nearline Storage

CBW NLS High Speed Query Access to Database and Nearline Storage CBW NLS High Speed Query Access to Database and Nearline Storage Speed up Your SAP BW Queries with Column-based Technology Dr. Klaus Zimmer, PBS Software GmbH Agenda Motivation Nearline Storage in SAP

More information

SAP HANA SPS 09 - What s New? SAP HANA Scalability

SAP HANA SPS 09 - What s New? SAP HANA Scalability SAP HANA SPS 09 - What s New? SAP HANA Scalability (Delta from SPS08 to SPS09) SAP HANA Product Management November, 2014 2014 SAP AG or an SAP affiliate company. All rights reserved. 1 Disclaimer This

More information

SAP Database Strategy Overview. Uwe Grigoleit September 2013

SAP Database Strategy Overview. Uwe Grigoleit September 2013 SAP base Strategy Overview Uwe Grigoleit September 2013 SAP s In-Memory and management Strategy Big- in Business-Context: Are you harnessing the opportunity? Mobile Transactions Things Things Instant Messages

More information

CBW NLS IQ High Speed Query Access to Database and Nearline Storage

CBW NLS IQ High Speed Query Access to Database and Nearline Storage CBW NLS IQ High Speed Query Access to Database and Nearline Storage Speed up Your SAP BW Queries with Column-based Technology Dr. Klaus Zimmer, PBS Software GmbH, 2012 Agenda Motivation Nearline Storage

More information

Cut Costs and Improve Agility by Simplifying and Automating Common System Administration Tasks

Cut Costs and Improve Agility by Simplifying and Automating Common System Administration Tasks SAP Brief Objectives Cut Costs and Improve Agility by Simplifying and Automating Common System Administration Tasks Simplify management of SAP software landscapes Simplify management of SAP software landscapes

More information

Toronto 26 th SAP BI. Leap Forward with SAP

Toronto 26 th SAP BI. Leap Forward with SAP Toronto 26 th SAP BI Leap Forward with SAP Business Intelligence SAP BI 4.0 and SAP BW Operational BI with SAP ERP SAP HANA and BI Operational vs Decision making reporting Verify the evolution of the KPIs,

More information

Real-Time Reconciliation of Invoice and Goods Receipts powered by SAP HANA. Stefan Karl, Finance Solutions, SAP ASUG Presentation, May 2013

Real-Time Reconciliation of Invoice and Goods Receipts powered by SAP HANA. Stefan Karl, Finance Solutions, SAP ASUG Presentation, May 2013 Real-Time Reconciliation of Invoice and Goods Receipts powered by SAP HANA Stefan Karl, Finance Solutions, SAP ASUG Presentation, May 2013 Legal disclaimer The information in this presentation is confidential

More information

Integrated Finance, Risk, and Profitability Management for Insurance

Integrated Finance, Risk, and Profitability Management for Insurance SAP Brief SAP for Insurance SAP Cost and Revenue Allocation for Financial Products Objectives Integrated Finance, Risk, and Profitability Management for Insurance Gain deep business insights Gain deep

More information

Configuration and Utilization of the OLAP Cache to Improve the Query Response Time

Configuration and Utilization of the OLAP Cache to Improve the Query Response Time Configuration and Utilization of the OLAP Cache to Improve the Query Response Time Applies to: SAP NetWeaver BW 7.0 Summary This paper outlines the steps to improve the Query response time by using the

More information

SAP HANA An In-Memory Data Platform for Real-Time Business

SAP HANA An In-Memory Data Platform for Real-Time Business SAP Brief SAP Technology SAP HANA Objectives SAP HANA An In-Memory Data Platform for Real-Time Business Real-time business: a competitive advantage Real-time business: a competitive advantage Uncertainty

More information

SAP BusinessObjects Dashboarding Strategy and Statement of Direction

SAP BusinessObjects Dashboarding Strategy and Statement of Direction SAP BusinessObjects Dashboarding Strategy and Statement of Direction www.sap.com TABLE OF CONTENTS DISCLAIMER... 3 INTRODUCTION... 3 Engage with SAP... 3 Background... 3 CUSTOMER EXPECTATIONS AND BUSINESS

More information

ORACLE DATA INTEGRATOR ENTERPRISE EDITION

ORACLE DATA INTEGRATOR ENTERPRISE EDITION ORACLE DATA INTEGRATOR ENTERPRISE EDITION ORACLE DATA INTEGRATOR ENTERPRISE EDITION KEY FEATURES Out-of-box integration with databases, ERPs, CRMs, B2B systems, flat files, XML data, LDAP, JDBC, ODBC Knowledge

More information

Power Smart Business Operations with Real-Time Process Intelligence

Power Smart Business Operations with Real-Time Process Intelligence SAP Brief SAP Business Suite SAP Operational Process Intelligence Powered by SAP HANA Objectives Power Smart Business Operations with Real-Time Process Intelligence Gain visibility into processes and data

More information

Data Management for SAP Business Suite and SAP S/4HANA. Robert Wassermann, SAP SE

Data Management for SAP Business Suite and SAP S/4HANA. Robert Wassermann, SAP SE Data Management for SAP Business Suite and SAP S/4HANA Robert Wassermann, SAP SE Disclaimer This presentation outlines our general product direction and should not be relied on in making a purchase decision.

More information

Data Integration using Integration Gateway. SAP Mobile Platform 3.0 SP02

Data Integration using Integration Gateway. SAP Mobile Platform 3.0 SP02 Data Integration using Integration Gateway SAP Mobile Platform 3.0 SP02 DOCUMENT ID: DC02000-01-0302-01 LAST REVISED: February 2014 Copyright 2014 by SAP AG or an SAP affiliate company. All rights reserved.

More information

Data Aquisition Techniques in SAP Netweaver BW BI

Data Aquisition Techniques in SAP Netweaver BW BI Data Aquisition Techniques in SAP Netweaver BW BI Applies to: SAP BW 3.5, SAP BI 7.0 etc. For more information, visit the EDW homepage Summary This paper discusses the various sources available for the

More information

BW-EML SAP Standard Application Benchmark

BW-EML SAP Standard Application Benchmark BW-EML SAP Standard Application Benchmark Heiko Gerwens and Tobias Kutning (&) SAP SE, Walldorf, Germany tobas.kutning@sap.com Abstract. The focus of this presentation is on the latest addition to the

More information

R49 Using SAP Payment Engine for payment transactions. Process Diagram

R49 Using SAP Payment Engine for payment transactions. Process Diagram R49 Using SAP Payment Engine for payment transactions Process Diagram Purpose, Benefits, and Key Process Steps Purpose The purpose of this scenario is to show you how to check the result of payment orders

More information

Cost-Effective Data Management and a Simplified Data Warehouse

Cost-Effective Data Management and a Simplified Data Warehouse SAP Information Sheet SAP Technology SAP HANA Dynamic Tiering Quick Facts Cost-Effective Data Management and a Simplified Data Warehouse Quick Facts Summary The SAP HANA dynamic tiering option helps application

More information

BW370 BI Integrated Planning

BW370 BI Integrated Planning BI Integrated Planning SAP NetWeaver Course Version: 98 Course Duration: 5 Day(s) Publication Date: 2015 Publication Time: Copyright Copyright SAP SE. All rights reserved. No part of this publication may

More information

EMC: Managing Data Growth with SAP HANA and the Near-Line Storage Capabilities of SAP IQ

EMC: Managing Data Growth with SAP HANA and the Near-Line Storage Capabilities of SAP IQ 2015 SAP SE or an SAP affiliate company. All rights reserved. EMC: Managing Data Growth with SAP HANA and the Near-Line Storage Capabilities of SAP IQ Based on years of successfully helping businesses

More information

Transform HR into a Best-Run Business Best People and Talent: Gain a Trusted Partner in the Business Transformation Services Group

Transform HR into a Best-Run Business Best People and Talent: Gain a Trusted Partner in the Business Transformation Services Group SAP Services Transform HR into a Best-Run Business Best People and Talent: Gain a Trusted Partner in the Business Transformation Services Group A Journey Toward Optimum Results The Three Layers of HR Transformation

More information

ORACLE DATA INTEGRATOR ENTERPRISE EDITION

ORACLE DATA INTEGRATOR ENTERPRISE EDITION ORACLE DATA INTEGRATOR ENTERPRISE EDITION Oracle Data Integrator Enterprise Edition 12c delivers high-performance data movement and transformation among enterprise platforms with its open and integrated

More information

SAP BW powered by SAP HANA: Understanding the Impact of HANA Optimized InfoCubes Josh Djupstrom SAP Labs

SAP BW powered by SAP HANA: Understanding the Impact of HANA Optimized InfoCubes Josh Djupstrom SAP Labs [ SAP BW powered by SAP HANA: Understanding the Impact of HANA Optimized InfoCubes Josh Djupstrom SAP Labs [ Objectives At the end of this session, you will be able to: Understand the motivation for HANA

More information

2015-09-24. SAP Operational Process Intelligence Security Guide

2015-09-24. SAP Operational Process Intelligence Security Guide 2015-09-24 SAP Operational Process Intelligence Security Guide Content 1 Introduction.... 3 2 Before You Start....5 3 Architectural Overview.... 7 4 Authorizations and Roles.... 8 4.1 Assigning Roles to

More information

Leverage the Internet of Things to Transform Maintenance and Service Operations

Leverage the Internet of Things to Transform Maintenance and Service Operations SAP Brief SAP s for the Internet of Things SAP Predictive Maintenance and Service SAP Enterprise Asset Management Objectives Leverage the Internet of Things to Transform Maintenance and Service Operations

More information

The Edge Editions of SAP InfiniteInsight Overview

The Edge Editions of SAP InfiniteInsight Overview Analytics Solutions from SAP The Edge Editions of SAP InfiniteInsight Overview Enabling Predictive Insights with Mouse Clicks, Not Computer Code Table of Contents 3 The Case for Predictive Analysis 5 Fast

More information

TE's Analytics on Hadoop and SAP HANA Using SAP Vora

TE's Analytics on Hadoop and SAP HANA Using SAP Vora TE's Analytics on Hadoop and SAP HANA Using SAP Vora Naveen Narra Senior Manager TE Connectivity Santha Kumar Rajendran Enterprise Data Architect TE Balaji Krishna - Director, SAP HANA Product Mgmt. -

More information

Xcelsius Dashboards on SAP NetWaver BW Implementation Best Practices

Xcelsius Dashboards on SAP NetWaver BW Implementation Best Practices Xcelsius Dashboards on SAP NetWaver BW Implementation Best Practices Patrice Le Bihan, SAP Intelligence Platform & NetWeaver RIG, Americas Dr. Gerd Schöffl, SAP Intelligence Platform & NetWeaver RIG, EMEA

More information

Data Warehouses and Business Intelligence ITP 487 (3 Units) Fall 2013. Objective

Data Warehouses and Business Intelligence ITP 487 (3 Units) Fall 2013. Objective Data Warehouses and Business Intelligence ITP 487 (3 Units) Objective Fall 2013 While the increased capacity and availability of data gathering and storage systems have allowed enterprises to store more

More information

ENTERPRISE EDITION ORACLE DATA SHEET KEY FEATURES AND BENEFITS ORACLE DATA INTEGRATOR

ENTERPRISE EDITION ORACLE DATA SHEET KEY FEATURES AND BENEFITS ORACLE DATA INTEGRATOR ORACLE DATA INTEGRATOR ENTERPRISE EDITION KEY FEATURES AND BENEFITS ORACLE DATA INTEGRATOR ENTERPRISE EDITION OFFERS LEADING PERFORMANCE, IMPROVED PRODUCTIVITY, FLEXIBILITY AND LOWEST TOTAL COST OF OWNERSHIP

More information

IBM DB2 specific SAP NetWeaver Business Warehouse Near-Line Storage Solution

IBM DB2 specific SAP NetWeaver Business Warehouse Near-Line Storage Solution IBM DB2 specific SAP NetWeaver Business Warehouse Near-Line Storage Solution Karl Fleckenstein (karl.fleckenstein@de.ibm.com) IBM Deutschland Research & Development GmbH June 22, 2011 Important Disclaimer

More information

Asian Paints: Enabling Real-Time Analytics Across Growing Data Volumes

Asian Paints: Enabling Real-Time Analytics Across Growing Data Volumes 2015 SAP AG or an SAP affiliate company. All rights reserved. Asian Paints: Enabling Real-Time Analytics Across Growing Data Volumes Asian Paints Limited Industry Chemicals Products and Services Paints

More information

Mastering the SAP Business Information Warehouse. Leveraging the Business Intelligence Capabilities of SAP NetWeaver. 2nd Edition

Mastering the SAP Business Information Warehouse. Leveraging the Business Intelligence Capabilities of SAP NetWeaver. 2nd Edition Brochure More information from http://www.researchandmarkets.com/reports/2246934/ Mastering the SAP Business Information Warehouse. Leveraging the Business Intelligence Capabilities of SAP NetWeaver. 2nd

More information

Business Intelligence In SAP Environments

Business Intelligence In SAP Environments Business Intelligence In SAP Environments BARC Business Application Research Center 1 OUTLINE 1 Executive Summary... 3 2 Current developments with SAP customers... 3 2.1 SAP BI program evolution... 3 2.2

More information

Near-line Storage with CBW NLS

Near-line Storage with CBW NLS Near-line Storage with CBW NLS High Speed Query Access for Nearline Data Ideal Enhancement Supporting SAP BW on HANA Dr. Klaus Zimmer, PBS Software GmbH Agenda Motivation Why would you need Nearline Storage

More information

Enterprise Information Management Services Managing Your Company Data Along Its Lifecycle

Enterprise Information Management Services Managing Your Company Data Along Its Lifecycle SAP Solution in Detail SAP Services Enterprise Information Management Enterprise Information Management Services Managing Your Company Data Along Its Lifecycle Table of Contents 3 Quick Facts 4 Key Services

More information

Greater Continuity, Consistency, and Timeliness with Business Process Automation

Greater Continuity, Consistency, and Timeliness with Business Process Automation SAP Brief Extensions SAP Business Process Automation by Redwood Objectives Greater Continuity, Consistency, and Timeliness with Business Process Automation Streamline critical enterprise processes Streamline

More information

Enhance your Analytics using Logical Data Warehouse and Data Virtualization thru SAP HANA smart data access SESSION CODE: 0210

Enhance your Analytics using Logical Data Warehouse and Data Virtualization thru SAP HANA smart data access SESSION CODE: 0210 Enhance your Analytics using Logical Data Warehouse and Data Virtualization thru SAP HANA smart data access Balaji Krishna, Product Management SAP HANA Platform. SAP Labs @balajivkrishna SESSION CODE:

More information

Create Mobile, Compelling Dashboards with Trusted Business Warehouse Data

Create Mobile, Compelling Dashboards with Trusted Business Warehouse Data SAP Brief SAP BusinessObjects Business Intelligence s SAP BusinessObjects Design Studio Objectives Create Mobile, Compelling Dashboards with Trusted Business Warehouse Data Increase the value of data with

More information

Analyze, Validate, and Optimize Business Application Performance

Analyze, Validate, and Optimize Business Application Performance SAP Brief SAP Extensions SAP LoadRunner by HPE Objectives Analyze, Validate, and Optimize Business Application Performance Test performance throughout the application lifecycle Test performance throughout

More information

Enabling Better Business Intelligence and Information Architecture With SAP Sybase PowerDesigner Software

Enabling Better Business Intelligence and Information Architecture With SAP Sybase PowerDesigner Software SAP Technology Enabling Better Business Intelligence and Information Architecture With SAP Sybase PowerDesigner Software Table of Contents 4 Seeing the Big Picture with a 360-Degree View Gaining Efficiencies

More information

Integrating SAP and non-sap data for comprehensive Business Intelligence

Integrating SAP and non-sap data for comprehensive Business Intelligence WHITE PAPER Integrating SAP and non-sap data for comprehensive Business Intelligence www.barc.de/en Business Application Research Center 2 Integrating SAP and non-sap data Authors Timm Grosser Senior Analyst

More information

Real People, Real Insights SAP runs analytics solutions from SAP

Real People, Real Insights SAP runs analytics solutions from SAP Real People, Real Insights SAP runs analytics solutions from SAP Michael Golz CIO Americas, SAP Responsible for both IT service delivery and innovative solutions, Michael discusses the changing role of

More information

Formulate Winning Sales and Operations Strategies Through Integrated Planning

Formulate Winning Sales and Operations Strategies Through Integrated Planning SAP Brief SAP Supply Chain Management SAP Sales and Operations Planning Objectives Formulate Winning Sales and Operations Strategies Through Integrated Planning Keep pace with rapidly changing market conditions

More information

Gain Contextual Awareness for a Smarter Digital Enterprise with SAP HANA Vora

Gain Contextual Awareness for a Smarter Digital Enterprise with SAP HANA Vora SAP Brief SAP Technology SAP HANA Vora Objectives Gain Contextual Awareness for a Smarter Digital Enterprise with SAP HANA Vora Bridge the divide between enterprise data and Big Data Bridge the divide

More information

Run Better in Weeks to Address Current and Future Business Needs

Run Better in Weeks to Address Current and Future Business Needs SAP Brief SAP Rapid Deployment s Objectives Run Better in Weeks to Address Current and Future Business Needs Accelerate your time to value Accelerate your time to value Meeting core business objectives

More information

BW Source System: Troubleshooting Guide

BW Source System: Troubleshooting Guide P. Mani Vannan SAP Labs India TABLE OF CONTENTS TROUBLESHOOTING:... 3 CHECK WHETHER SOURCE SYSTEM CONNECTION IS OK... 3 RELEVANT AUTHORIZATIONS FOR BACKGROUND USER... 8 ERROR RELATED TO IDOC MISMATCH BETWEEN

More information

CBW NLS ADK-based Nearline Storage Solution

CBW NLS ADK-based Nearline Storage Solution CBW NLS ADK-based Nearline Storage Solution Keep Seamless BW Query Access to Database and Archived Data Dr. Klaus Zimmer, PBS Software GmbH Agenda Motivation Nearline Storage in SAP BW Architecture ADK-based

More information

Qlik connector for SAP NetWeaver

Qlik connector for SAP NetWeaver Qlik connector for SAP NetWeaver Increasing the value of SAP with quick and flexible data discovery Organizations spend millions of dollars automating their business processes. But unfortunately, many

More information

Protect Your Connected Business Systems by Identifying and Analyzing Threats

Protect Your Connected Business Systems by Identifying and Analyzing Threats SAP Brief SAP Technology SAP Enterprise Threat Detection Objectives Protect Your Connected Business Systems by Identifying and Analyzing Threats Prevent security breaches Prevent security breaches Are

More information

SAP HANA Vora : Gain Contextual Awareness for a Smarter Digital Enterprise

SAP HANA Vora : Gain Contextual Awareness for a Smarter Digital Enterprise Frequently Asked Questions SAP HANA Vora SAP HANA Vora : Gain Contextual Awareness for a Smarter Digital Enterprise SAP HANA Vora software enables digital businesses to innovate and compete through in-the-moment

More information

The New Face of Business Intelligence for SAP Customers

The New Face of Business Intelligence for SAP Customers Business Objects, an SAP company The New Face of Business Intelligence for SAP Customers Place holder Dan Kearnan, SAP BI Marketing, Business Objects Ken Hartman, Hughes Network Systems Agenda Why SAP

More information

Business Warehouse BEX Query Guidelines

Business Warehouse BEX Query Guidelines Business Warehouse BEX Query Guidelines Table of contents Specific Query Design Guidelines... 2 Variables/Parameters/Prompts... 2 Key Figures... 2 Characteristics... 3 General Query Design Considerations

More information

Welcome to an introduction to SAP Business One.

Welcome to an introduction to SAP Business One. Welcome to an introduction to SAP Business One. In this topic, we will answer the question: What is Business One? We define SAP Business One and discuss the options and available platforms for running

More information

SAP Business Intelligence Adoption V6.41: Software and Delivery Requirements. SAP Business Intelligence Adoption February 2015 English

SAP Business Intelligence Adoption V6.41: Software and Delivery Requirements. SAP Business Intelligence Adoption February 2015 English Business Intelligence Adoption February 2015 English Business Intelligence Adoption V6.41: Software and Delivery Requirements AG Dietmar-Hopp-Allee 16 69190 Walldorf Germany Document Revisions Date 0 11/11/14

More information

This presentation provides a SECOND LEVEL of information about the topic of Central Finance.

This presentation provides a SECOND LEVEL of information about the topic of Central Finance. This presentation provides a SECOND LEVEL of information about the topic of Central Finance. Central Finance is not a product rather it is a non-disruptive approach for SAP s customers to get the benefits

More information

LHI Leasing Simplifying and Automating the IT Landscape with SAP Software. SAP Customer Success Story Financial Services Provider LHI Leasing

LHI Leasing Simplifying and Automating the IT Landscape with SAP Software. SAP Customer Success Story Financial Services Provider LHI Leasing LHI Leasing Simplifying and Automating the IT Landscape with SAP Software SAP Customer Success Story Financial Services Provider LHI Leasing Company LHI Leasing GmbH Headquarters Pullach, Germany Industry,

More information

SAP HANA. SAP HANA Performance Efficient Speed and Scale-Out for Real-Time Business Intelligence

SAP HANA. SAP HANA Performance Efficient Speed and Scale-Out for Real-Time Business Intelligence SAP HANA SAP HANA Performance Efficient Speed and Scale-Out for Real-Time Business Intelligence SAP HANA Performance Table of Contents 3 Introduction 4 The Test Environment Database Schema Test Data System

More information

SAP HANA From Relational OLAP Database to Big Data Infrastructure

SAP HANA From Relational OLAP Database to Big Data Infrastructure SAP HANA From Relational OLAP Database to Big Data Infrastructure Anil K Goel VP & Chief Architect, SAP HANA Data Platform WBDB 2015, June 16, 2015 Toronto SAP Big Data Story Data Lifecycle Management

More information