- SAP Managed Tags:
Source: SAP
Figure 1
So much data, and so little time available.
Do you have a large system that you want to convert to SAP S/4HANA? Do you have too much data and too little downtime available to move?
In addition to being vital in the battle to maintain a manageable system size during business operations, SAP Data Volume Management is an integral part of your SAP S/4HANA conversion project to help you reduce the existing volume of data in your system as well as growth rates, both of which are crucial to ensuring a manageable downtime during the actual migration.
Source: <https://www.asug.com/events/manage-time-and-data-volume-during-sap-s-4hana-conversion>
Source: SAP
Figure 2
Agenda is shown above
Source: SAP
Figure 3
Purpose of data volume management is to control your growth rates in your SAP system
How to reduce volume
Data avoidance - do not write data unnecessary data to database
Turn on summarization in FICO
Housekeeping - deletion reports available
Archiving will have a positive impact if you have an old system
Can use DVM in Solution Manager
If using SAP HANA, option to use DVM dashboard in one support launchpad
Why?
Source: SAP
Figure 4
Only bring over the data you require to S/4HANA
Benefits include less hardware, cost is smaller with less data, shorter conversion times
Source: SAP
Figure 5
Scenarios to move to S/4HANA
What to highlight when run conversion
Source: SAP
Figure 6
Early watch services
Statistics on the age footprint of data
After 2 years, value of data is less; not accessed frequently, think of data archiving
Source: SAP
Figure 7
What are the challenges?
Why do we do this?
Old data to migrate to S/4HANA and where the data structures are checked, old data may fail checks, and you may see data quality issues
Archive vs. delete; decision to make with the users
Future reporting requirements; S/4HANA has some built-in analytics
Data tiering concepts - what data to focus on
Custom code adjustments for archiving or data aging
New models and applications
After migration, adjust technology
- Clustered tables before S/4HANA, declustered after
How to prioritize?
Source: SAP
Figure 8
Data quality - run a test conversion
You can run a financial data quality service via SAP Support
Do as early as you can
Archive as much as possible
Conversion run times - reduce size of clustered tables will help reduce run times
Check the sizing report
DVM is in readiness check
Source: SAP
Figure 9
Sizing report will tell you what to expect and what to pay for
DVM is not a must if you are OK with sizing report results
Source: SAP
Figure 10
Clean up results, some calculations based on data aging
Obsolete data can be deleted
Source: SAP
Figure 11
Largest tables
Look at deletion or archiving before S/4HANA conversion
Source: SAP
Figure 12
Readiness check sizing has a DVM area
Reduction based on 24 or 12 months
Source: SAP
Figure 13
Sizing and archiving potential
Source: SAP
Figure 14
SolMan Launchpad
Reorg and compression can be simulated
Forecasting and simulation - how big system will be
Archive or delete data
If not migrate for some time - stop data going into the system
Source: SAP
Figure 15
Guided self service, one of the HANA quick wins
Source: SAP
Figure 16
Analyze data from ECC system
Might see data outside of your retention policy, which could be a "quick win"
Source: SAP
Figure 17
DVM available on launchpad, must be on HANA
See tiles - top left, memory statistic - used and free
2 upper right- disk stats - used and free
3 (middle) memory optimization statistics
4 - click into it to see archiving/deletion object
5 - additional scripts that can be run on data collected
6 - age of data in system (bottom middle)
How access archived data in S/4HANA?
Source: SAP
Figure 18
See changes in data for accounting
Archived data stays in old data structure
Source: SAP
Figure 19
Example archive access
Can't access classic FI archived files
Source: SAP
Figure 20
Source: SAP
Figure 21
Define info structure on your own; see SAP note to see fields necessary
Source: SAP
Figure 22
More examples
CO_ITEM is replaced by CO_TRANS
Source: SAP
Figure 23
Changes as a result of S/4HANA
Source: SAP
Figure 24
Best practice guide
https://wiki.scn.sap.com/wiki/display/TechOps/Data+Volume+Management
Have you started archiving as part of your journey to S/4HANA?
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