1. Data Architecture Management
Includes developing a data model, planning databases and table structures, and figuring out the key data flows and integrations that will need to happen between systems.
Data development is about producing a technology-driven solution to move data from place to place. It may be moving things from a data generation system to a data reporting system, or writing queries for reports, or a variety of systems development tasks that enable migration correctly.
2. Data Development
There won’t be a manual data manipulation in any stage. All data conversions will be done only using the agreed tools.
3. Data Operations Management
Data operations must be limited to according to migration specification. Only approved tools/functions/reports can be used to execute any operations over SAPA/Hydro data.
Data back-up is recommended to be done in every stage of migration.
4. Data Security Management
No direct DB access is allowed and authorization concept must allow the authorized users to “see only what they should see”.
Important is that at the same time data security management is not only to keep people from accessing information they shouldn’t, but it is also about efficiently providing access to the data people need (e.g. “display” authority can be granted only to authorized operation user to view migration result for validation and reconciliation purpose).
5. Data Quality Management
One of the key migration area is the data quality management.
To have a successful migration the high quality of data source must be ensured.
Therefore, it is recommended to perform data cleansing and data enrichment before it can be stated the data are ready for migration.