In this post, you will know about the many aspects of replicating SAP applications to BigQuery by taking the help of SAP Data Services.
Currently, you can integrate data like Google BigQuery with the business data present in the SAP Data Warehouse Cloud of the SAP Business Technology Platform using hyper-scaler storage. What is critical is that data can be queried through virtual tables directly with specific tools for this activity. The main advantage here is that users, through live connectivity, can query Google BigQuery data from the SAP Data Warehouse Cloud, enabling businesses to carry out maximized business analytics and report generation.
You can also replicate data from SAP to BigQuery and evaluate all third-party and SAP data in one place. You also get real-time analytics without replicating data through live connectivity and use virtual tables to query BigQuery, thereby optimizing the Rate of Return on current SAP and Google services.
To start SAP to BigQuery replication, the database must be on SAP HANA or on any other platform that has the support of SAP. The SAP to BigQuery process of database replication is used to combine data in SAP systems with that of BigQuery.
After replication, the data can be used for obtaining vital business insights from Machine Learning (ML) for analysis even on petabyte scales. The SAP to BigQuery replication process is simple and SAP system administrators with the required expertise and skillsets in the configuration of SAP Basis, SAP DS, and the Google Cloud can easily do it.
Preliminary activities for SAP to BigQuery
Before going through data replication, carry out a few preliminary activities to make the SAP to BigQuery process a seamless affair.
- Install, configure, and make ready for operations the database server, SAP Data Services, and the SAP application system.
- Check whether the configuration is as per the licensing requirements of SAP.
However, the groundwork for SAP to BigQuery replication might vary depending on whether data is being exported from an SAP application system or an ancillary database.
The SAP to BigQuery replication workflow
The SAP to BigQuery data replication is a smooth and seamless operation and hence preferred by most businesses. The first step is extracting data through the SAP Data Services or any other SAP-supported database. This data is then formatted and processed so that it matches the architecture of BigQuery. Finally, the processed data is loaded into BigQuery for cutting-edge analytics.
It is possible to decide in advance the time when SAP Data Service would begin the data replication. Once the operation is set in motion all existing data in the BigQuery table is overwritten by the data that is newly imported. After the replication is completed, BigQuery is delinked from the source database and is no longer kept synchronized.
However, the only exception to this is when the Change Data Capture (CDC) feature of the SAP Data Service is leveraged by the SAP Replication Server for real-time data provisioning and ensuring data capabilities for all the source tables.
This is how the SAP to BigQuery data movement works.
- SAP applications update all data in the source system
- The SAP LT Replication Server replicates all changes made to the data that are then stored in the Operational Data Queue.
- A subscriber of the Operational Delta Queue, SAP DS, continually tracks changes to the data at pre-determined intervals.
- The data from the delta queue is extracted by SAP DS and then processed and formatted to match the structure that is supported by BigQuery. Once this step is completed, data is loaded from SAP to BigQuery and can now be used by businesses for analytics.
This is the workflow of data replication from SAP to BigQuery.
Hurdles faced during SAP to BigQuery data replication
While SAP to BigQuery data replication is a seamless and uncomplicated process when the right automated tools are used, DBAs often have to overcome certain hurdles.
The main problem is that during data replication, critical data from several points have to be merged to derive value while creating analytical dashboards. Businesses have to combine data existing in hyper-scaler storage like Google BigQuery with the data that exists in the SAP Data Warehouse Cloud. The optimized solution for organizations to this challenge is to link SAP to BigQuery in which case the data that is queried from BigQuery is available in the SAP Data Warehouse Cloud without replication.
Once this link is established, it is possible to use various dashboards for checking data integrated into a single source with the SAP Analytics Cloud. The benefit here is that queries are amalgamated through virtual tables with current and specific data that is not cached or replicated from its source.
Features of the best tools for SAP to BigQuery data replication
While several tools can be used for data replication from SAP to BigQuery, only the best and the most optimized ones will ensure that no challenges are faced during the process. The most critical factor here is whether the selected tool requires access to a database or it supports replication directly from the SAP runtime versions. Regardless of whether replication is from the application layer or the database layer, the best tools provide support to both methods.
Select a tool that is fully automated and can replicate huge volumes of SAP data to the BigQuery database without any drop or lag in speeds and performance. Further, the tool should be able to maintain the referential integrity of data and ensure that the precise time, date, and values changing at the columnar level are on record.
Use such SAP to BigQuery tools for optimally replicating data for better reporting and analytics.
