Our experience shows that temporary and system data contributes towards more than 30% of the size of their SAP databases. This was one of the driving forces behind the development of our housekeeping solution ERNA, which helps in a smart way to keep temporary and system data growth under control. This webinar presents the most typical problems with SAP housekeeping and the solution towards its optimisation.

1. © 2014 DataVard # 1
Joseph W. O‘Leary
DataVard, Inc.
Shrink your database
with automated
housekeeping

2. © 2014 DataVard # 2
§ Reduce system size in regards to
Logs and Temporary Data
substantially
§ Improve loading performance
§ Be better prepared for future
challenges like migration to SAP
HANA® platform
§ Transparency
§ Reduce data cleansing effort
§ Minimum effort, maximum benefit
§ ERNA functionalities (i.e. cockpit
for more transparency)
§ Experience of DataVard
consultants
§ Price
§ Result of Analysis (DataVard BW
Fitness Test): 1.308 GB temporary
data and logs blocked nearly half
of the system size 25 % database
size reduction
§ Deletion of 750 GB unnecessary
data (PSA, ChangeLog, Cube
compression, RFC Logs)
§ Reduction of workload: only
§ 1 workday per month for
housekeeping
Customer Example
Customer Profile
An international leader in specialist publishing in the area Science, Technology, Medicine.
“With the help of ERNA we were able to substantially reduce the effort for data
cleansing, with minimum effort and realizing savings of 25 % of the system’s size.
We are now well prepared for future challenges like SAP HANA®.”
Key figuresObjectives Highlights
Database Size Reduction: 25% through Housekeeping

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Clean up your system
Size reduction example (Housekeeping and NLS)
183 183
998 321
918
780.3
650
325
312
156
0
48.1
0
500
1000
1500
2000
2500
3000
3500
Heute mit OutBoard und ERNA
OutBoard
Cube data
ODS data
Other data
Temporary data
Master data
Before After
-68%
-15%
-50%
-50%
Total DB space saved of 43%!

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User
happiness
TCO&data
access
TCO
Smart Data Management
§ Performance
optimization, Tuning
§ In-memory
§ Ensure SLAs are met
GOALS TACTICS
§ Use appropriate
storage: Archiving,
NLS, Smart data
access
§ Set up central policies
§ Define policies
§ Set up housekeeping
§ Automation
Information “at your
fingertips”
speed and high
availability is key.
Keep & store, but
reduce costs.
Purge, delete,
housekeeping
Hot Data
Business critical data
Data required for
reporting and planning
Cold Data / Old Data
Aged data, history
Infrequent, rare use
Need to keep (legal,
internal, industry
requirements)
Dead Data
Technical data (e.g.
logs, protocols, PSA)
Redundant data

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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
Step 1: Fitness Test
Typical distribution of data in a BW system
Comments:
§ Data you report on is
only 13-17% of the
system size
§ Temporary data is
subject to housekeeping
(BALDAT, RS*DONE, ...)
§ Use the HANA sizing
report as a 1st indication
(OSS note 1736976).
§ Create a plan for the
data lifecycle
(data load to data exit)
“Only 12% of all data in BW is actually used”
Source: Forrester research

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Housekeeping activities
n Application log
n Batch log
n IDoc tables (EDI40, EDIDS)
n qRFC, tRFC
n Job-Tables (TBTCO, TBTCP etc.)
n Change & Transportsystem
n Spool data (TST03)
n Table Change Protocols
n Batch Input Folders
n Alert Management Data (SALRT*)
n Old short dumps
n Batch input data
Netweaver
Scope of Housekeeping
n Unused customers
n Unused vendors
n Phantom change documents
n Phantom texts
ERP
n PSAs & Change Logs
n Request logs & tables (RSMON*
and RS*DONE)
n Unused dimension entries
n Unused master data
n Cube & Aggregate compression
n Temporary database objects
n NRIV buffering
n Table buffering
n BI-Statistics
n Process Chain Log
n Errorlogs
n Unused Queries
n Empty partitions
n BI Background processes
n Bookmarks
n Web templates
Business Warehouse

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7 reasons housekeeping is not done
Organizational Functional
n Unclear responsibilities
Basis or Application-Team?
n Low visibility
What happens when its not done is
not transparent
n No dedicated resources
Will management pay for cleanup?
n Tools spread out in the
system
Many small programs that can be
found in many SAP notes
n Not enough functionality
If there is a program it often only
allows keep or delete, no archiving
n Too high risk
Deleting permanently is risky
n No transparency
no tool that says if cleanup is
running correct and in full

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Central cockpit for all activities

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Recycle Bin makes more aggressive deletion possible
Ease discussions about retention times.
Instead of deleting data, you can temporarily store it in a compressed recycle bin, from which it
can be deleted at a later date.

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Recycle Bin compression (example PSA)
Same retention time
using less space
Today
6monthsPSA
14days
PSA
15 days- 6months compressed in
recycle bin (Quick Restore possible)
Benefit:
ERNA Recycle Bin
Automated deletion

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Less work through one central access
Keep your whole SAP Landscape in good condition
ERNA runs either stand-alone in a single
SAP System or is installed on a central
instance to automatically housekeep the full
system landscape

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Mass processing leads to lower implementation effort
By grouping objects, that are to be house kept, the implementation effort is kept low.
New objects can be automatically included to existing groups, by using wildcards and
dynamic patterns.

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Calendar & Scheduler
Ensure, that the planned housekeeping activities are really being implemented.
There are multiple monitoring tools: the calendar view shows all planned tasks within the full
SAP Landscape, where ERNA is running.

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Clean up your system in 3 steps
Start Run Deploy1 32
§ Prepare Project
§ Kick off workshop
§ Analyze potential
§ Scope definition based
on BW Fitness Test and
archiving roadmap
§ Target storage definition
§ OutBoard™ (NLS /
ERNA) installation
§ Initial customizing
§ Housekeeping setup
§ Object adjustments
§ Deletion and retrieval
tests
§ Performance tests
§ Setup of ongoing
archiving / deletion
§ Knowledge Transfer
§ Initial Housekeeping
§ Result validation
§ Optional: Tablespace
reorganization
§ Project Sign-off
& Support
§ Ongoing Housekeeping
done by customer

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Your presenter:
Joseph W. O‘Leary
Product Manager ILM
DataVard, Inc.
joseph.o.leary@datavard.com
Request a demo here:
www.erna.datavard.com

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Who is DataVard
§ Specialized in Data Management
for SAP
§ Customers range from SMEs (60 users)
to Fortune 500 (e.g. Allianz, BASF,
KPMG, Roche, Nestle)
§ Focus on Data Management and ABAP
development
§ SAP and ABAP only
§ SAP certified solutions for BW Nearline storage
and housekeeping
§ Partnership with SAP in consulting (e.g. SLO)
§ Partnership with SAP in development (e.g. ILM)
Success
Experience
Focus

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Copyright DataVard Inc. 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 DataVard GmbH. The information contained herein may be changed without prior
notice.
DataVard and OutBoard 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
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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
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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.
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