This blog has been some time in the making.It had been a new year resolution that I should put pen to paper or rather ‘keystrokes to blog’ about experiences in migrating data in the Utilities industry.
The business scenario behind one of the solutions was also interesting in the sense that the system was built keeping in mind that we were building it for multiple business units within a single client in the system.The business units each corresponded to the gas industry in 4 different markets in Europe as well as the United Kingdom.
My blog(s) is specifically about the processes used from start to end of the data migration and how we went about it. They will be explained in more detail in follow up blogs to this one.
The processes below are in the order in which they take place in the data migration life cycle.
1. Profiling the data.
Understanding the data model to be followed and hence mapping of business logic from legacy to SAP. Once we know the business process is mapped in SAP we can figure out the migration object.
2. Mapping the Attributes
Once we have the migration object identified we need to map the attributes to be brought over from Legacy to SAP. This is accomplised by the use of a mapping sheet.The sheet can also be used to specify the file structure.
3. Data Upload
One of the biggest pluses of the SAP IS-Utlities solution and IS solutions in general is the Data Migration Workbench (transaction EMIGALL).This is the upload tool used for most IS-U processes and is very easy to configure to meet our requirements. The statistics for our upload is also easily readable. More in a later blog.
4. Data Cleansing
As in all software development life cycles the data has to be cleansed. This phase also helps us to iron out any file structure issues at the time of extraction as well the data quality . This is an iterative process and happens more than once .
The final process and business critical is the reconciliation of the data.This can be done through various reports.The technical reconciliation can be at the count level to understand that all of the data extracted is uploaded into SAP. The more important reconciliation is the functional side of it where we check that all the data required combined together to proceed in the new system has been migrated or not.
Well that is a start. Check this space for more updates 🙂