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SAP to BigQuery Data Replication – Workflow, Tools, Challenges

Are you looking to query data directly through virtual tables? It can now be done seamlessly by using hyper-scale storage to integrate business data in SAP Warehouse Cloud (based on SAP Business Technology Platform) with Google Big Query. The benefit here is that live connectivity can be provided along with the capability to query Google Big Query data from the SAP Data Warehouse Cloud, leading to analytics of critical business data.

There are multiple benefits of replicating data from SAP to BigQuery. One is analyzing SAP and third-party data in one place thereby optimizing ROI in SAP and Google services. Another is availing live analytics without replicating data, thereby ensuring real-time connectivity to query Big Query by virtual tables.

For SAP to BigQuery, the database can either be running on SAP HANA or any other platform. The only precondition is that it has to be supported by SAP. In this case, replicating data can be used to create a backup in SAP so that it can be used with data from multiple SAP systems to Big Query. The data provides insights from Machine Learning (ML) for data analytics in even petabyte-scale systems. Thus, replication from SAP to BigQuery can easily be undertaken by SAP system administrators who have the required expertise in SAP DS, SAP Basis, and Google Cloud.

Starting with data replication from SAP to BigQuery

Before initiating SAP to BigQuery data replication activities a few preliminary steps have to be carried out. The most critical is pre installing, configuring, and readying the database server, SAP Data Services, and the SAP application system. It is also necessary to check whether the configuration meets all licensing requirements. However, the preconditions for starting data replication from SAP to BigQuery may differ depending on whether data is being exported directly from an SAP application or an ancillary database.

Workflow of SAP to BigQuery data replication

The workflow of SAP to BigQuery data replication is as follows.

  • SAP applications first update data in the source systems.
  • SAP LT Replication Server replicates all changes to the data and this is stored in the Operational Delta Queue.
  • SAP DS which is a subscriber of the Operational Delta Queue monitors the queue for any changes to the data at pre-defined intervals.
  • SAP DS extracts the data from the delta queue, formats it to match the structure supported by Big Query, and begins loading the processed data from SAP to BigQuery.
  • SAP to BigQuery data replication is now complete and is available in Big Query for analysis.

The workflow of data replication from SAP to BigQuery is seamless and users can preset when SAP Data Servicers should start to export the data. This exported data overwrites all data that exists in the target Big Query. Once the replication is completed, it is not necessary to keep the data in the target system (Big Query) in sync with the source systems. For changes that occur after the data replication activity, there is a provision in the SAP Replication Server to leverage the existing Change Data Capture (CDC) feature of the SAP Data Services. It carries out data provisioning and delta capabilities in real-time for all source tables.

Optimized tools for SAP to BigQuery data replication

Several tools are capable of SAP to BigQuery data replication. Knowing about the best and using them will make the process easy and without any hitches or complexities. The most important point to consider is whether the selected tool supports replication directly from the SAP runtime versions or whether access to a database is necessary. Both methods are supported by the best tools regardless of whether replication is from the application layer or the database layer.

Some of the attributes of the tools that should be insisted upon for SAP to BigQuery data replication are as follows.

  • Fully automated with the ability to perform independently without human intervention of the DBAs. Since coding is not required, the TCO will be quite low. A point-and-click interface should suffice for SAP data replication, SCD type history, data transformation, and data reconciliation.
  • The best tools can replicate huge volumes of SAP data to the Big Query database without any drop or lag in speeds and performance.
  • Choose tools for data replication from SAP to BigQuery that maintain the referential integrity of data and ensure that the precise time, date, and values changing at the columnar level are on record.

Using the SAP to BigQuery tools with these capabilities transforms data optimally for better reporting and analytics.

Some challenges faced for SAP to BigQuery data replication

While the tools for SAP to BigQuery replication make sure that the process is free from complexities and fully automated, there are certain challenges to be faced.

The primary challenge is that in data replication from SAP to BigQuery, critical business data from multiple points have to be federated so that value can be derived while creating analytical dashboards. It helps organizations to integrate data located in the hyper-scaler storage like Google Big Query with the data that is existing in the SAP Data Warehouse Cloud. The solution for businesses to get around this issue is to link SAP to BigQuery. In such instances data that is queried from Big Query is available in the SAP Data Warehouse Cloud without replication.

After this live connectivity is implemented, businesses can check data integrated into a single source with the SAP Analytics Cloud using various dashboards. The result is that queries are federated through virtual tables with current and specific data that is not cached or replicated from its source.

 

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