Data migration has always been a high risk challenge. Every project has it’s own complexities that makes the data migration a unique experience for respective projects.
As you push your organization to achieve new heights, your IT infrastructure has to be changed to technologies that can handle your future needs. This makes Data Migration an inevitable challenge.
Data warehouse is a back bone of any data driven organization hence migrating very core part of IT infrastructure is a high risk job. So when you decide to migrate Data warehouse, it is not just an IT project. Every stake holder(project managers, business owners, SMEs, front end application users) within an organization is accountable for successful migration.
There are common reasons for organizations to migrate their existing Data warehouse solutions :
- No more scalable solution
Business is expanding but Data infrastructure is failing to scale linearly.
- Licensing and maintenance cost
Commercial RDBMS licensing cost is increasing but return on investment is staggered.
- Consolidation of scattered data marts
Need a single version of truth across business.
- Degraded performance
Not able to handle mixed workloads
- Inability to support complex applications
Newer applications such as Pattern Analysis, Correlation analysis not supported or difficult to develop.
Factors to be considered for successful migration :
- Understanding of source data
It is crucial that source data is properly understood. Involve subject matter experts and business owners to understand sources before planning any further activities.
- Data Quality
An advance data quality tools will help you understand the source data along with Data statistics and data segmentation.
- Data Pruning
Identify data sources for first phase of migration and migrate data that is essential to your business. Discontinue ETL processes which are no longer of any use. Involve downstream application users to justify importance of data. Discard processes which load duplicate data.
- Source to Target Mapping
Map every field from source to target and make sure significance of data remains intact.
- Resource Planning
Data migration is a high risk job and relying of inexperience resources can prove costly. Hire resources with experience in data migration, technology and domain.
- Data Reconciliation
Data reconciliation between legacy to target is a continuous process throughout Data Migration development. Use advance tools to validate transformations.
- Legacy Data
Define an automated process to migrate legacy data to newer system because many times data gets corrupted during development and testing phase.
We, at Agile Soft Systems, provide end to end solution for data migration projects. Our data migration experts can help you to fast track migration process.
For more information, contact us.