Common Data Migration Pitfalls and How can we avoid them
Historically, many data migration projects have been plagued by risks and delayed go lives, resulting in costly budget overruns. The usual culprit is the data !!A frequently overlooked aspect of ERP deployments is the integrity of the data that the system delivers. Traditionally, many systems integrators implementing a new system prioritize the project
Common Data Migration Pitfalls and how can we avoid them
Historically, many data migration projects have been plagued by risks and delayed go lives, resulting in costly budget overruns. The usual culprit is the data !!A frequently overlooked aspect of ERP deployments is the integrity of the data that the system delivers. Traditionally, many systems integrators implementing a new system prioritize the project in this order:
Even though data is one of the most important factors for business success, it gets the least attention. Often, system integrators will defer the data loads to the client's staff, and some may incorrectly assume the data migration is a simple file transfer between systems. Suffice to say, the effort associated with data migration is often grossly underestimated.
Common Pitfalls and mistakes in Data Migration and Tips to Avoid them :
a. Poor data quality: Sometimes data defects are known, but new deficiencies are often uncovered after extraction. This is where SAP BI/BO data services can helps us, delivering profiling reports that can be used before, during, and after migration. These reports also provide crucial inputs to continuous monitoring programs implemented as a part of larger information governance initiatives- which are part of larger information governance initiatives- which are an important part of any data migration project .
b. Missing Data : You will be surprised to discover just how many "mandatory" fields in source systems are blank or nulls? The SAP solutions we mentioned to help to measure poor data quality which can be used to quantify the scope of missing data .
c. Mismatched data: Field overuse is a classic problem of incorrect data sometimes two or more different domains of data can be found in one field that was repurposed after its original use became obsolete. The cure for this issue is to define the domain rules and have the SAP BO/ BI services report the errors so that corresponding data conversion rules can be created and executed.
d. Data is not available in the time for Go Live: Operational commitments are sometimes misaligned with system implementation, delaying the entire deployment. Accessing, extracting and transforming the source data is often the issue here . A key part of the solution is to use an extract, transform, and load ETL tools and prove that works for the environment, it accelerates extract coding and validation rules development.
e. Data requirements are not captured properly: Business and data transformation rules are not sufficiently researched or documented to the breadth or depth necessary for consolidating multiple systems into one target. This is always the hardest part of a migration project. Ensure that you have both the commitment from the business users and time in their schedules to help us formulate the rules.
Summary : Always think of Data first before you get started with a new system migration and implementation . Raise the priority for data migration in the task list and ask your system integrators how they plan to get the migration done with a thorough planned strategy. Use the standard industry standards and methodology for Enterprise Data lifecycle management method, to help guide through the process steps .Choose the right tools and budget them with thorough planning to ensure the smooth technical data conversion of data between systems followed with sufficient and stringent data validations and testing.