Data Migration and Conversion Strategies in Oracle E-business Suite

Data Migration and Conversion Strategies in Oracle E-business Suite:

Data Migration and Conversion Strategies in Oracle E-business Suite

Businesses spend billions of dollars migrating data between information-intensive applications. Yet up to 75 percent of new systems fail to meet expectations, often because flaws in the migration process result in data that is not adequately validated for the intended task.

Data migrations generally result from the introduction of a new system. This may involve an application migration or consolidation in which one or more legacy systems are replaced or the deployment of an additional system that will sit alongside the existing applications.

Whatever the specific nature of any data migration, the ultimate aim is to improve corporate performance and deliver competitive advantage.

Especially while implementation of Oracle e-business Suite and migration of the data from other legacy system to Oracle 

Steps To Design an Effective Data Conversion Process:

Below are the steps for effective data migration and conversion process for any implementations in Oracle ERP.

1-              Data Need for Conversion.

2-            Data Mapping / Conversion Design

3-            Finalization of Data for Migration

4-            Loading of data for QA (Validation)

5-             Data Migration /Data loading to Production.

6-            Data Validations - Production

Data Need for Conversion:

The first point is to decide which data is required for conversion and requirement. It is normally depend on your implementations domain and modules. Which modules are implementing during the imp mentation and that basis it is decided what is the requirement of the data.

For example it is Oracle Financials and SCM implementation and for that you need to load the data from Financials modules let say for Oracle Fixed Asset data and from Supply chain you need to load data for Oracle Inventory.

Data Mapping / Conversion Design

After identifying the data for migration the next stage is to make the conversion design and data mapping.  Few are the important points for data conversion design.

• ·       Extraction of data from Legacy System
• ·       Templates for data loading
• ·       Preparation of mapping sheet to map the legacy data to Oracle required data.
• ·       Field to Field mapping of data legacy to required data.
• ·       Legacy system data validation for mapping sheets.
• ·       Data conversion if required during mapping and validation

Finalization of Data for Migration:

Once the Mapping is complete, the next step is to preparing and finalization of data for migration. This step is very crucial, because whatever data is finalized and migrated will be affected the performance of the ERP and it is saying garbage in and garbage out.

Each and every aspect of the data should be reviewed and analyzed that every piece of information that is required from the legacy data is available and converted into Oracle required form.

Like for Assets data for migration to oracle from legacy system, should be checked that each and every information is included in the data sheets like Assets number, tag number, Asset Category, Manufacturer, Invoice number, serial number etc...

Loading of data for QA:

It increases the effectiveness of the data migration process. Data is loaded into Test Instance (Sometimes called-QA Instance) for detail quality assurance. Mostly QA teams are deployed on QA for data loading. But many cases the imp mentation team validates the data when it loaded to Test Instance.

After QA it identifies all the issues/ deficiencies of data uploaded then the same issues to be resolved from the actual data before final upload.

Data Migration / Data loading to Production:

After data validation the next step is data migration to Production. This step is relatively straightforward. However, it would likely be quite time-consuming due to the size of the legacy database.

Data Validations:

Once the data is migrated to prod, the last step is to validation of prod data. Mostly this validation is high level and summary level data is validated because detail validation is done on QA (Quality Assurance) level.