Public Public
Harjeet Judge,Debraj Roy/Customer Experience Group
EA208 - SAP BusinessObjects BI4 Tips and
Tricks for Optimized SAP HANA Reporting
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Agenda
What is SAP HANA
SAP HANA Access Methods
Semantic Layer on HANA
SAP BI Clients
Demo
Wrap-up
What Is SAP HANA?
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Today's World
Data
Warehouse /
Marts
OLAP
Transactional
System
OLTP
Real-time
posting
into Transactional
System
Aggregation
Batch transfer to
Data Warehouse
Limited flexibility due to
pre-defined data structures
Long query run-times
Loss of detail
Long Wait times for reports Reporting
Challenges
Large Volumes
High Impact
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What if this would all happen real-time?
No Aggregation / No Data Staging / No Data Marts
Real-time
Loading into
SAP HANA
High Performance
Large Volume
Data Processing
Fast, flexible and detail
analytics over large
volumes
SAP HANA
IN-MEMORY
'Real Life'
Business
Transaction
Analysis and Insight
Action
SAP HANA Access Methods
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SAP BusinessObjects BI access to HANA Direct access
Explorer
Analysis Office,
Analysis OLAP
Lumira,
Predictive Analysis
Design Studio
Note: Direct access background technologies might
vary (SQL via JDBC, via ODBC, BICS, MDX, etc.) the
common criteria is that the access methodology is
transparent to the final user of the tool
Direct access
Crystal Reports
Enterprise Tables
Information
Models
SAP HANA
Database
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SQL
SAP BusinessObjects BI access to HANA Free-hand SQL
Tables
Information
Models
SAP HANA
Database
Extended SQL
Crystal Reports
Enterprise
Crystal Reports
2011/2013
Note: Free-hand SQL access is available via ODBC and JDBC
middlewares
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SQL
SAP BusinessObjects BI access to HANA Universe based
Tables
Information
Models
SAP HANA
Database
Extended SQL
Univ
ers
e
Web Intelligence
Crystal Reports
Enterprise
Dashboards
Note: Universe access is available via ODBC and JDBC
middlewares
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Semantic Layer on HANA Access to SAP HANA – BI 4.1
BI 4.1 DSL clients can access SAP HANA through relational universes and
multidimensional direct access
• Single source and multisource
• Full support of HANA information models (analytic views and calculation views)
Explorer *
Dashboard Design
SQL
SQL
MDX
SE
MA
NT
IC L
AY
ER
U
NIV
ER
SE
D
IRE
CT
AC
CE
ES
S
Tables
Information Models
SAP HANA
HANA STUDIO
SQL Visual Intelligence *
Web Intelligence Predictive Analysis *
CR for Enterprise
CR for Enterprise * Can also access universes
Semantic Layer on HANA
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Semantic Layer on HANA Two questions
• Should I build my universe on information models
or on tables?
• How to make sure my universe on HANA has a
good performance?
13
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Semantic Layer on HANA HANA Engines
• For best performance, SAP recommends
leveraging the OLAP engine for
aggregating large volumes of data.
• Depending on which database object you
query against, the engine that runs at
query execution time varies
• The engine selection does not depend on
which query language you use
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Semantic Layer on HANA Building a universe on Information Models
• The work done in HANA studio is reused
• The same models can be used in Analysis or Explorer
• The appropriate HANA engines optimize the query execution
• Programmatic calculation views allow more complex levels of data manipulation than universes (e.g. L or R language)
Pros
• Some SQL constraints apply to information models which impact the ad-hoc query experience
• Programmatic calculation views are fully executed even if not all metadata is requested
Cons
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Semantic Layer on HANA Benefits
Relational universes
Automatic business layer generation: limited administration, no need to modify the business layer
Universe customizations: reorganization, renaming, calculations, metadata security, etc.
Multiple views in a single universe: one single access point
Multidimensional access
No need to create a universe, no added administration
Full support of SAP HANA multidimensional capabilities
Generate merged multi-views universe
Use a universe wizard to generate a data foundation and business layer on top of multiple SAP HANA views
Any dimensions and attributes that are common to different views are created as a single business layer object,
and special aggregate-aware objects are generated to make queries on multiple views possible
Powerful query generation while preserving SAP HANA performance
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Semantic Layer on HANA Universe Performance Tuning
17
• “Array fetch size” value:
o Default is 10 but it can be raised
higher (max 1000) for better
performance
o Higher values run faster queries but
need more memory
• Ensure query synchronization is
performed in HANA and not in the client
tool
o Set Join_by_SQL = Yes in Data
Foundation.
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Semantic Layer on HANA Universe Performance Tuning
• Enable Query Stripping in Universe
o Performance improvement for
WebI reports on relational
universes
o Optimally reduced queries on
HANA views and agnostic RDBMS
o New setting in relational universe
introduced in BI 4.1 been
introduced
SAP BI Clients
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SAP Web Intelligence
Web Intelligence is an interactive reporting tool that can access relational as well as
multidimensional data sources via the concept of Universes. The reports can be viewed online
or offline thanks to the microcube, an embedded local in-memory cache engine (microcube). In
case of Hana, WebI will access it through relational access using SQL
Enables off-line (microcube) as well as interactive analysis (e.g,HANA)
Access to heterogeneous data sources
Basic dashboarding capabilities (Drill, CVOM charts, dynamic filters)
Advanced Reporting capabilities (Desktop Rich Client, DHTML, Mobile)
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SAP Web Intelligence with SAP HANA
Benefits
With traditional databases, when huge volume of data needs to be queried, aggregate tables might need to be
created to overcome performance degradations, not with SAP HANA
Another inconvenience is that you might wait for the next ETL load to have up-to-date data
Thanks to SAP HANA in-memory engine and replication capabilities, the data is aggregated on-the-fly in real-
time and the user gets “live” data every time he/she accesses or drills into the report
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SAP Crystal Reports Enterprise
SAP HANA access and benefits
Direct access to SAP HANA using a
multidimensional access.
Hierarchies support
Member selector
Full support of SAP HANA in SQL mode using
relational universes
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SAP Lumira
SAP HANA access and benefits
Online access using relational connection
Time and geography hierarchies
Offline access using relational connection:
data cached in SAP Sybase IQ
Semantic enrichment, calculations, time and
geography hierarchies
Data manipulation
Datasets merge
Demos
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Demo Content
Demo 1: Universe HANA Multiview
Access multiple HANA views and synchronize the datasets locally
Demo 2: Web Intelligence optimization for HANA: Query Stripping
Make sure your report is SAP HANA optimized by “stripping” your query. Push calculations down to SAP HANA and retrieve only the results.
Demo 3: Web Intelligence optimization for HANA: Query Drill
Enable drill workflows to make the most of SAP HANA performance
Demo 4: Crystal Enterprise on HANA
Create an OLAP connection on SAP HANA
Create a multidimensional document with Crystal Reports for Enterprise
Demo 5: SAP Lumira on HANA
Perform data discovery directly on HANA and implement different visualizations
Wrap-Up
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Further Information
SAP Education and Certification Opportunities
www.sap.com/education
Watch SAP TechEd Online
www.sapteched.com/online
SAP Public Web
scn.sap.com
www.sap.com
Frequently Asked Question: WebIntelligence on HANA
Best Practices: WebIntelligence on HANA
Creating Relational Universes: Best Practices
Best Practices: Creating a universe on SAP HANA
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Thank you
Contact information:
Debraj Roy
mail to: [email protected]
Harjeet Judge
CEG – Customer Experience Group
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In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or
release any functionality mentioned therein. This document, or any related presentation, and SAP SE’s or its affiliated companies’ strategy and possible future
developments, products, and/or platform directions and functionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for
any reason without notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. All forward-
looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place
undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions.
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