83% improvement in enabling SAP data loads.
Tailored workflows meeting unique needs with ease.
Real-time insights enabling data-driven operations.
Challenge
Sharaf DG needed a cloud-native ELT platform tightly integrated with Snowflake. Possessing efficient data extraction from various sources and improving data refresh cycles without overloading source systems was top of the list of requirements.
Sharaf DG needed a cloud-native ELT platform tightly integrated with Snowflake. Possessing efficient data extraction from various sources and improving data refresh cycles without overloading source systems was top of the list of requirements.
Solution
Over 3 months, Sharaf DG successfully migrated all data sources to Matillion + Snowflake, streamlining extraction processes.
Using the ‘push-down SQL’ strategy and Matillion’s ‘API Query Profile’ component has allowed Sharaf DG to simplify the extraction of data from previously challenging third party’s, which have unlocked inaccessible data sources.
Over 3 months, Sharaf DG successfully migrated all data sources to Matillion + Snowflake, streamlining extraction processes.
Using the ‘push-down SQL’ strategy and Matillion’s ‘API Query Profile’ component has allowed Sharaf DG to simplify the extraction of data from previously challenging third party’s, which have unlocked inaccessible data sources.
Results
- Creation of ELT pipelines has reduced from days to hours, enabling rapid synchronization between operational databases and the cloud data warehouse.
- From the incremental and "push-down SQL" techniques key SAP data loads are completed in just 30 minutes, instead of 3 hours, from incremental and "push-down SQL" techniques.
- Substantial reduction in resource consumption and boost in overall performance
- Creation of ELT pipelines has reduced from days to hours, enabling rapid synchronization between operational databases and the cloud data warehouse.
- From the incremental and "push-down SQL" techniques key SAP data loads are completed in just 30 minutes, instead of 3 hours, from incremental and "push-down SQL" techniques.
- Substantial reduction in resource consumption and boost in overall performance
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