Suva
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Suva
"For more than ten years, synvert (previously saracus) consulting has been a competent partner supporting us in all areas of BI development. From business analysis to the development of complex ETL routes to reporting, the consultants of synvert consulting take care of all the work. Thanks to the good know-how and the good social competence, the project goals can be achieved at any time. The cooperation is so easy and good that we can concentrate on the work at any time. The collaboration is a real success!"
Suva - DWH Pharos: Source data migration due to the introduction of a new operational system.
Suva is the most important provider of compulsory accident insurance in Switzerland, insuring around 2 million employees against occupational accidents, occupational diseases, and non-work-related accidents. For over 10 years now, Suva has been maintaining a steadily growing data warehouse that serves as a data hub for internal and external information needs.
Recently, Suva had to introduce a new claims and premium system after having used the same developed, COBOL-based insurance system for more than 20 years. This change to an industry solution (Adcubum Syrius), expanded for Suva, fundamentally altered the data foundation for the DWH. The objective of the project was to adapt the DWH to the new requirements with the following objectives:
- Migration of all data due to the old system’s replacement with a new operational system.
- Transfer of the entire database.
- Automation of the source data connection.
- Maximum possible reuse of the existing core DWH layer.
- Consistent data quality.
- Transfer of the entire database.
- Automation of the source data connection.
- Maximum possible reuse of the existing core DWH layer.
- Consistent data quality.
To manage the increasing number of source objects, a distinct approach was implemented to handle mutations from the source system. Metadata tables were used to register new tables, while a PLC/SQL framework (GenDel) provides data deltas via database views for processing. ETL processes continue to be performed using Informatica PowerCenter. The existing anchor modelling of the core DWH by synvert (formerly saracus) enabled the reuse of structures and ensured flexibility for expandability. In addition, the Oracle Business Intelligence Enterprise Edition (OBIEE) was added to the SAS infrastructure as a new BI tool. Oracle's strengths in online analytical processing (OLAP) are being leveraged, while OBIEE serves as the frontend for operational reporting.
- By using GenDel, the process of connecting to the source data can be automated up to the layer closest to the data warehouse; this automation can be maximised to the fullest extent possible.
- By converting to a daily loading cycle, data can be made available more quickly.
- In addition to analytical evaluations, the data warehouse can now also generate operational evaluations and data interfaces with a high frequency of updates.
- Strengthening of the data warehouse as the central data hub for Suva.
- The implementation of GenDel has automated the source connection, enabling the efficient and easy addition of new source tables without the need for individual ETL processes.
- Analysis and detailed design of entire data areas in the DWH (costs, premiums, payroll, etc.).
- Execution of the entire project cycle for operational reporting: from requirements analysis and design to the implementation and testing of the system and reports.
- Since not all legacy data was transferred to the new source system, the DWH had to perform its own data archiving, which now serves as an additional data source to further enable a comprehensive view of Suva’s complete data history (since 1918).
- Use of new BI technology (OBIEE).
- Optimisation of load times and increased automation by shifting from a monthly load cycle to a daily one, guaranteeing a daily supply of new data for operational reports, keeping them up to date.
- The implementation of the operational system required adapting the DWH to new source data structures, putting pressure on a prompt completion.
The conversion of the DWH was implemented on schedule. The core DWH modelling, which had been designed with specialist logic in earlier project phases, allowed for the continued use of a significant portion of the existing data model, despite the complete conversion to a new source system; this not only strengthened the significance of the DWH in Suva, but also made the conversion process more efficient. The use of GenDel enabled Suva to meet the growing demand for automation of ETL processes, as well as offering a flexible and easily configurable interface that allows for the straightforward connection of additional source data.
