The document describes DataVard's BW Fitness Test and HeatMap products which provide analysis and recommendations to optimize SAP BW systems. The BW Fitness Test analyzes key performance indicators, system usage, and data distribution. It benchmarks the system against others. The HeatMap visualizes query usage and runtimes to identify performance optimization opportunities. Both tools help with data management, testing, compliance, and preparing for upgrades like SAP HANA.

1. # 1
DataVard BW Fitness TestTM and
HeatMap

2. # 2
How DataVard Approachs Operation
Goal
EINZELKÄSTEN
Develop a solid understanding of realistic
improvement potential. Understand what
really moves the needle.
Analysis
Identify potential for central rules and
policies.
Governance
Implement improvement in the identified
areas for improvement based on the
central set of rules.
Automation
Shrink your PROD and non-
PROD database
Automate (regression)
testing to the max
Be ahead of your auditor
and secure your landscape
Reflect business changes in
your landscape
Match the value of data to its cost. Deploy future ready storage
infrastructure (HANA & X).
Automate testing based on system usage (operational intelligence)
System security, Password security, User and authorization
management, ABAP code vulnerability
M&A, consolidation, harmonization, standardization, mass data
changes, unbundling
Data
Management
Security &
Compliance
Testing
Managing Business
Change

3. # 3
Identifying value and real usage of the data, potential for performance and size improvement, security & compliance check
to safeguard security, availability & performance, improvement of SAP performance, user management
SAP System-Monitoring with Canary Code
How DataVard Approachs Operation
OutBoard™
ERNA™KATE
Lean Data Management Testing
Analysis with ERP/BW Fitness Test
Automated housekeeping ERNA
Centralises, automates and manages the housekeeping functions across
the SAP Landscape.
95% compression into recycle bin
Nearline Storage and Archiving OutBoard
Automates and manages data offloading from online database to any storage (RDBMS, Cloud,
Hadoop etc.), data remain accessible and writable
Automated Testing KATE
Test Case Management, Usage Stats and Heat Maps to check scenarios
Script lessTest Automation and AutomaticTest Data Selection
Selective System Copy
Toolsets to manage test environments in SAP ERP/BW aiming at making test systems smaller
based on characteristics (eg. time slice)
Automated, scramble and authorisation available for compliance

4. # 4
How fit is my SAP System?
q Analysis of System Usage,
Data Volume and
Performance
q Benchmarking
q Trending
q Preparation for Data
Management, Upgrade,
HANA, Big Data
q Available for ERP and BW
D a t a V a r d B W F i t n e s s T e s t T M

5. # 5
BW Fitness Test
n Identifies data growth and distribution
n System performance analysis
n System robustness analysis
n Comparison of all KPIs against 200+ BW systems in the world
RISK AND BENEFITS ASSESMENT
LEVERAGE INVESTMENTS
INCREASE PERFORMANCE
OPTIMIZE HANA SIZE AND COSTS
DATA CLASSIFICATION
Power of BW Fitness Test

6. # 6
5%
15%
15%
9%
11%
32%
5%
5% 3%
Master data
Temporary data
Other data
PSA data
Changelog data
ODS data
Cube E data
Cube F data
Cube D data
Data distribution in SAP BW*
Comments:
§ 13-17% of system size is
reporting data
§ Quick check on
housekeeping potential
(size of BALDAT,
RS*DONE, ...)
§ HANA sizing report gives
a 1st indication (OSS
note 1736976)
“Only 12% of all data in BW is actually used.”
Forrester research* Source: DataVard BW Fitness Test™

7. # 7
BW Fitness Test™ - Project Phases
SAP BW
HTML Output
incl. Recommendations by DataVard Consultant

8. # 8
BW Fitness Test™ - Installation
The BW Fitness Test software is shipped and installed to the BW
production system as a standard ABAP transport request containing
the programs which extract the necessary KPI information.

9. # 9
BW Fitness Test™ - Prerequisites
Supported BW versions: 7.0+
Supported database systems:
• MaxDB
• MSSQL
• DB2
• DB4
• DB6
• HANA
• Oracle
• Sybase ASE
• Informix
Other Prerequisites:
• DB statistics should be up to date (for ORACLE)
• Query statistics must be turned ON with the setting - OLAP
Statistics Detail Level = 2 - All (Statistics should be turned on
prio to the BW Fitness Test execution, so that data are
collected at least 6 to 1 month before the execution)
• Please provide us with the OSS user and the logon data for
the BW system which is to be analyzed with at least the
following authorizations: SE11, SE16, SE38, SM37, SM50,
RSA1, DB02, DB20, /DVD/BWFT, ST22.

10. # 10
BW Fitness Test™ - Execution
The analysis runs in max 3 background processes no longer
than 6 days.
There is no impact on the performance of the involved BW systems.

11. # 11
BW Fitness Test™ – Sample http://
bwftsample.datavard.com/
Check
Here
The BW Fitness Test™ prepared us excellently to make our SAP BW
fit for the future. We now manage our aged data with Nearline
Storage and improved our Load Performance.
Steffen Muesel, Randstad

12. # 12
Project Phase – BWFT
§ Customizable
parallelization
§ Collection of BWFT
KPIs
§ Download and
shipment of XML
results
§ Collection of results
§ Comparison to best practices / benchmark
§ Manual analysis and verifications
§ Customer requirement
§ Building recommendation
§ Presentation or
results and
recommendations
§ HTML, PPT or PDF
Output
§ SAP transport
§ ABAP based
§ Authorization
Technical
Functional
Technical ExecutionInstallation of BWFT Analysis of Results Delivery and Presentation
1st Week 2nd Week 3rd Week 4th Week

13. # 13
A Co-Innovation with Randstad
When running a SAP system many
“architect” questions remain open:
- Which data / time slice is being actively used
- Are applications being used as designed and
planned (# users & data volume)
- Date volume vs. data usage in an application
- Where does data growth come from
- How can I predict data growth
- Are the most important reports/queries running at
good performance
HeatMap – Innovation

14. # 14
DataVard HeatMap for SAP BW – Features
Query
runtime
ETL UsageQuery usage
Analyzer
Data visualization in a HeatMap
Analysis of data in list view
Custom aggregation of statistics
Collectors
Statistics
Condense
Is your HOT data fast enough?
Is your data in active use? Is data loaded in the right frequency?
1
2
3

15. # 15
DataVard HeatMap - USE CASES
Leading chemical
company: 8,1 TB of data
which was queried less
than 5 times over a 6
months period.
DATA
MANAGEMENT
Major german bank: 142
Queries that have been
executed more than 500
times (during one day)
with an avg. runtime of
more then 1 minute.
142 * 500 * 1 min =
71.000 mins = 1184
Hours of people waiting.
One of our biggest
customers: identify the
500 most frequently used
queries with the top 5
selections based on the
query statistics gathered
by HeatMap.
The result was a
reduction in test efforts
by 320 hours per SAP
Support Package.
With the help of
HeatMap a major Oil &
Gas producer has
identified and
subsequently stopped
4,5 hours of nightly loads
into unused Objects.
PERFORMANCE
TUNING
REGRESSION TEST
ETL OPTIMIZATION
8,1 TB non-active
data moved to NLS
Save 948 hours of
waiting per DAY
Reduce test efforts by
320 hours per SP
Stopped 4,5 hours
of nightly loads

16. # 16
Query usage collector - EXAMPLE
Size KPI (size of box) = Size of
InfoProvider in GB
Color KPI: Access in given time
frame via queries (green = HI, red =
LOW/No)
A
B
Full system InfoCube analysis
§ Analyzed time frame 11.6. – 21.11.
§ 22.130 GB of data in 1.113 InfoCubes
analyzed
§ Analysis runtime of 54 hours
§ 8.138 GB of data with less then 5 queries
accessed, o/w 3.154 GB not at all

17. # 17
Objective: Ensure important queries perform at top speed
Size KPI: Usage of queries in given period
Color KPI: Average query runtime
Use case:
- Support for performance optimization of queries
- See which queries are important and have bad performance
- Validate performance optimization – before and after
Query runtime collector

18. # 18
Full system analysis
- Analyzed time frame of one day
21.11.2014
- Analysis runtime of 10 minutes
- 142 Queries with avg. runtime more
then 1 minute
- The queries have been executed 551
times (during one day)
- 142 * 500 * 1 min = 71.000 mins = 1184
Hours of people waiting
Query runtime collector - EXAMPLE
Usage of queries in given period
Color KPI: Average query runtime
A
B

19. # 19
DataVard‘s HeatMap build Operational
Intelligence from user behavior above and
beyond the BI statistics (! time slice).
Best use cases are:
- Reviewing the architecture (data still in use,
granularity / aggregation, data distribution etc.)
- Data Management (esp. in preparation for SAP
HANA) like NLS, Housekeeping or avoiding data
- Performance Optimization (reporting and ETL)
- Test Management
Key take aways

20. # 20
Project Phase – BWFT incl. HeatMap
§ Customizable parallelization
§ Collection of BWFT KPIs
§ Collection of Extended Query Statistics
(recommended 6 weeks, but can differ)
§ Download and shipment of XML results
§ Collection of
results
§ Comparison to
best practices /
benchmark
§ Manual analysis
and verifications
§ Customer
requirement
§ Building
recommendation
§ Presentation or
results and
recommendations
§ HTML, PPT or PDF
Output
§ SAP transport with
BWFT and
HeatMap
§ ABAP based
§ Authorization
Technical
Functional
Technical ExecutionInstallation of Software Analysis of Results Delivery and Presentation
Duration - 1 week Duration - 6 weeks (recommended) Duration - 1 week Workshop - 1 day

21. # 21
Jan Meszaros
Solution Center Lead (ILM
Consulting)
jan.meszaros@datavard.com
Your contact at DataVard

22. # 22
No part of this publication may be reproduced or
transmitted in any form or for any purpose without the
express permission of DataVard GmbH. The
information contained herein may be changed without
prior notice.
DataVard, OutBoard, ERNA, CanaryCode, BW
Fitness Test and ERP Fitness Test are trademarks or
registered trademarks of DataVard GmbH and its
affiliated companies.
SAP, R/3, SAP NetWeaver, SAP BusinessObjects,
SAP MaxDB, SAP HANA and other SAP products and
services mentioned herein as well as their respective
logos are trademarks or registered trademarks of SAP
AG in Germany and other countries.
All other product and service names mentioned are
the trademarks of their respective companies. Data
contained in this document serves informational
purposes only. National product specifications may
vary.
These materials are provided by DataVard GmbH and
its affiliated companies (“DataVard") for informational
purposes only, without representation or warranty of
any kind, and DataVard shall not be liable for errors or
omissions with respect to the materials. The only
warranties for DataVard 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.
CR
Copyright DataVard GmbH.
All rights reserved.CR
Copyright DataVard GmbH.
All rights reserved.