Today, companies are becoming more and more drawn to the benefits of using Google BigQuery for S4/HANA. The main question we’d like to answer is: why is this  serverless data warehouse so attractive  to so many SAP customers? Let’s take a look at our Automotive Customer case study to explain why…  

Our Automotive Customer approached us because they needed a straightforward way of integrating SAP data with non-SAP systems while staying within their current budget. At the time, they were evaluating SAP BW and SAP Analytics Cloud to combine their data but decided to look elsewhere due to high costs and long implementation timeAlso, to note, their in-house team was recently trained on how to use the Cloud for analyzing data. 

 The solution was obvious to us: implement Google BigQuery.  

 But why? 

Google BigQuery forms the data warehousing backbone for modern BI solutions and enables seamless data integration, transformation, analysis, visualization, and reporting. With serverless data warehousing, Google does all the required resource provisioning, so businesses can focus solely on their data analysis rather than worrying about upgrading, securing, or managing the infrastructure. 

 While using Google BigQuery, users can analyze data at scale with 26% – 34% lower three-year TCO versus other cloud data warehouse alternatives. 

 Coupled with Google BigQuery, BigQuery BI Engine is a trailblazer in terms of its memory analysis service. This tool allows users to interactively analyze large and complex datasets with sub-second query response time and high concurrency.  

 Let’s take a look at how we were able to implement Google BigQuery. 

 Our GCP Integration Tool enabled us to source our Automotive Customer’s data pretty quickly. This tool helps extract data from SAP table extractors, CDS views, info sets, and BW cubes/ADSO’s.  

 It has robust support for delta management, including initializing without data transfer, full load, repetition of failed delta, and pseudo delta. It also supports live streaming of data and Change Data Capture (CDC) for SAP tables. 

 We make use of SAP standard extractors to extract SAP data with delta capability. Data obtained by this tool can be staged into GCP Cloud storage (optional). From this point, it is transferred to the BigQuery staging tables.  

 From BigQuery staging, data is flattened/demoralized and merged with final reporting tables. At this point, the integration of SAP data with non-SAP data is possible. 

 Finally, to make sure that our Automotive Customer was set up to create reports, we activated Google Data Studio and Tableau. Other tools, such a PowerBI, QlikView, and Looker, are great options; however, in this scenario, Google DataStudio and Tableau made the most sense for our Automotive Customer. 

 Here is sample profitability dashboard for our customer in DataStudio: 


Our GCP integration tool and our strategic migration approach were able to transition our Automotive Customer to the Cloud seamlessly with no downtime or extra costs. To this day, our customer is thrilled with BigQuery, and they are also pleased on how quickly we were able to transition their data to the Cloud.  

We did everything we could to show our Automotive Customer the benefits they would reap from moving their data into BigQuery by creating a roadmap on how we were going to extract and move their data, which made them more comfortable with the process. Also, considering their in-house team was trained on how to use the Cloud for data analytics, our solution made the most sense. 

If you’re interested in learning more about the benefits of using Google BigQuery Data warehouse for your SAP systems, we invite you to watch our on demand webinar. Click here to access the Integrating SAP Analytics on BigQuery on demand webinar!