One of the most optimized database management platforms and data storage repositories that are preferred by most data-driven organizations today is SAP. However, many of them are now looking for alternate resources because of a drawback inherent in SAP and that is its transactional nature which leads to execution delays, especially after the recent exponential growth in data-driven applications. The main hurdles are a lack of clarity as to who gets access to data stored in SAP, and for whom it is blocked. 

There is a way, though, to get around this issue and that is to migrate data from SAP to cloud-based platforms and data warehouses such as Google BigQuery, Azure Synapse, Amazon Redshift, and Snowflake. This ensures that the same databases are replicated and stored in multiple locations. The most effective solution in this regard, it has been seen, is to move databases from SAP to Snowflake primarily because all the benefits of the cloud like data security are available to users.  

The process of moving databases from SAP to Snowflake takes place over several stages. Here is a point-by-point explanation and comprehensive review of each of them. 

  • Decide the Parameters for SAP to Snowflake Data Transfer

A critical step before initiating the SAP to Snowflake data transfer process is to decide the parameters that have to be taken into account. These are as follows:

  • The databases and the tables
  • The users and applications that will have access to the selected databases and tables
  • The periodicity of data updating to the tables
  • The projected form of usage of the data that is migrated from SAP to Snowflake.

Once all these parameters are decided upon and finalized, the actual migration process can be started.  

  • Prepare a Migration Workflow

A workflow for the migration has to be prepared now with all the parameters detailed above incorporated into it. Phase out the steps, starting with completing first the low-impact databases, applications, and tables before taking up more complex tasks. Take special care to make sure that whatever may be the migration method adopted, the SAP database is in sync with Snowflake when the process is completed. 

Go by these steps:

  • First, go through the results of the previous step and break down the tables and the databases into manageable sections. Start with the tables that require minimum changes and will not affect business operations.
  • To identify any problems quickly at every step, data movement, consumption, and end-to-end data ingestion should be concurrent.
  • For data movement from SAP to Snowflake, always use automated and the most optimized tools available. This will help complete most of the complex re-tooling and syncing activity without human intervention at any stage. 
  • Create Accounts in SAP HANA and Snowflake

After preparing the workflow for the migration, accounts in SAP HANA and Snowflake have to be created and Snowflake has to be configured with the appropriate UI/CLI that includes the required warehouses, databases, users, and accounts on the cloud-based platform. 

  • Design the SAP Data Extractor and Tables in Snowflake

To extract SAP data, users can write their preferred code as SAP supports connections through ODBC/JDBC drivers and APIs. For easily creating tables in Snowflake later, make sure that all custom fields are extracted and type information preserved while extracting SAP data. Prefer CSVs by using a typed format instead of JSON/AVRO formats to store data. 

The extracted data from SAP has to be now used to create Snowflake tables. Map SAP and Snowflake by syncing Snowflake field types with the SAP field types. The columns with names that do not match the guidelines of Snowflake have to be renamed. 

  • Move SAP Data to Snowflake 

After following the steps, the final task is to load the files and data extracted into Snowflake. An integrator may be used to seamlessly go through the process. The COPY command loads bulk files. There are two ways to do so. The first is automating the process to incorporate all changed data periodically and the second, using deltas to load the data by taking a snapshot of the data once from SAP and moving it to Snowflake. Following the second process ensures that subsequently, only the deltas have to be loaded into Snowflake. 

Benefits of Moving Data from SAP to Snowflake

There are several benefits of moving data from SAP to Snowflake. Here are a few of the more critical ones. 

  • By moving data from Snowflake, a cloud-based data warehousing solution, users can avail of fully-managed automated services such as data storage, compression, and high performance. Hence, there is no need for organizations to build indexes or carry out any internal changes. 
  • Snowflake can process data from SAP or other third-party applications, regardless of whether it is in an unstructured, semi-structured, or structured form. This is relevant even when changes are made in the structure of the data files.
  • Because of the simple structure of Snowflake which is based in the cloud, it is possible to easily and seamlessly process SAP data with users being provided single-window access to actionable data. This helps businesses to follow FAIR (findable, accessible, interoperable, reusable) principles.  
  • SAP to Snowflake database migration enables users to get authentic and credible business content, helping them to take up multiple intricate queries, report generation, and data loading.  
  • Being based in the cloud, Snowflake provides scalable data storage capabilities with users having the option, for example, to scale up if required from 10GB to 30PB and then down to 10GB again when the peak demand is over. Payment too is as per the resources consumed. 

Always keep both SAP and Snowflake in sync to get the continuous movement of data. 


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