Without a doubt, SAP database management is an optimized repository for data storage. Then, why do businesses increasingly look to migrate databases to Snowflake, a data warehouse system that is based in the cloud, from SAP?
This post will take you through the many benefits of SAP to Snowflake database migration and the steps to ensure that the process of doing so is successful and passes off without any issues.
The reason why SAP users prefer to move data to the cloud environment through Snowflake is that the transactional nature of SAP often leads to delays in execution. This has further increased after the high growth in data-driven applications. Moreover, access permissions to SAP data often lack clarity and there is confusion about who is permitted to use the data and who is not.
One way to mitigate this problem is to move databases from SAP to platforms like Google BigQuery, Azure Synapse, Amazon Redshift, and Snowflake, all of which operate in the cloud. The SAP to Snowflake migration makes sure that the database is replicated to various locations so that stringent data security can be maintained. This is very critical in the current data-driven business environment.
Benefits of Moving Data from SAP to Snowflake
These are some of the important benefits of moving data from SAP to Snowflake that help in increasing operating efficiencies.
- A critical benefit of data migration is that the data warehousing solution Snowflake is cloud-based. Hence, it provides fully-managed automated services such as data storage, compression, and high performance and businesses do not have to build indexes or carry out any internal changes.
- Data from SAP or other third-party applications can be processed by Snowflake in their native format – unstructured, semi-structured, or structured. This is also relevant when changes occur in the architecture of the data files.
- SAP data can be easily and seamlessly processed by Snowflake as this cloud-based platform has a very simple structure. Further SAP users get single-window access to actionable data. This enables them to follow FAIR (findable, accessible, interoperable, reusable) principles.
- After migrating data from SAP to Snowflake, users get access to reliable business content that helps them to carry out multiple intricate queries, report generation, and data loading.
- Another benefit of the migration from SAP is that Snowflake provides flexible and scalable data storage capabilities. This allows users to quickly scale up during a sudden surge in storage demand and later come back to previous levels and pay only for the quantum of resources used. This results in considerable savings as compared to traditional databases where flat fees are charged irrespective of the storage capacities utilized.
During SAP to Snowflake, both the source and the target databases have to be kept in sync if incremental data has to be continuously loaded.
Moving Data from SAP to Snowflake
Several steps need to be taken for this form of data migration.
#Determining what is to be moved to Snowflake
These typically include –
- The tables and databases
- Finalizing the users who will be allowed to have access to the tables and the databases
- Finalizing the applications and scripts to be used for loading data to tables
- Finalizing the time cycle for updating the data to the tables
- Fixing the patterns for using data
Once these aspects are determined, strategies can be made to fix the inputs and the level of support needed for moving data from SAP to Snowflake.
#Planning the data movement execution
After the parameters are decided in the previous step, a plan for moving the data from SAP has to be worked out. A phased approach beginning with low-impact databases, applications, and tables and then moving to other complex tasks should be adopted. However, regardless of the approach, focus on syncing the data before completing this stage.
The process will be as follows –
- Based on historical analysis, categorize the tables and databases into specific steps starting with tables that typically need minimum changes and have a low impact on organizational operations. Carry out simultaneous data movement, consumption, and end-to-end data ingestion. This will help to identify any issues in the early stages to be rectified immediately.
- Use automated tools instead of manual coding to speed up data movement from SAP to Snowflake. Choose tools that reduce time to market as they automate a large portion of the re-tooling and syncing activity, especially during executing repeatable steps in the phased approach.
#Generating accounts in SAP HANA and Snowflake
The migration process can be initiated only after accounts are generated in SAP HANA and Snowflake. These include generating users and accounts as well as databases and warehouses on Snowflake.
#Building the SAP Extractor
By writing your preferred code, data can be extracted from SAP as it supports connections through ODBC/JDBC drivers and APIs. However, first ensure that all custom fields are extracted and type information preserved during data extraction as it will help to create tables in Snowflake later. Do not use a JSON/AVRO format but prefer a typed format as it helps to store the data and evade CSVs.
#Creating tables in Snowflake
The extracted data is to be now used for creating tables in Snowflake whose field types have to be synced and mapped to the SAP field types. For typed format as detailed in the previous step, the process becomes still easier even though there might be a need to rename columns that do not match the Snowflake column naming guidelines.
#Moving data from SAP to Snowflake
Finally, the COPY INTO command is used for loading bulk databases into Snowflake. A scheduler may be integrated into the process to make it run seamlessly on the desired frequency. This completes the SAP to Snowflake data movement process.