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I have performed two POCs over SAP Business Data Cloud. My core expertise is in DataSphere and it was a core part of this initiative. We integrated data from S/4, ECC, and Alteryx. We transformed the data models into a traditional analytical model and created Insight apps for reporting.
The best features I appreciate in SAP Business Data Cloud are that SAP is now offering a single platform subscription. Previously, if you wanted data engineering, you had to pursue DataSphere or BW, or if you wanted to extend for reporting, you had to buy another subscription for SAC. Instead, you can take a single subscription of SAP Business Data Cloud and implement whatever you need.
Another advantage is the subscription-based model with pay-as-you-go pricing. This is beneficial instead of having to buy a fixed amount of memory that you have to pay for even if you are not using it. The flexibility is quite good.
The large scale of integration is significant. Through the open cloud connector, we can integrate many systems. Previously, it was a closed SAP environment. Now we can integrate with different platforms across the board and transform data across the platforms, with SAP Business Data Cloud at the center. This makes it easy to convince clients and business stakeholders that they should purchase the subscription.
SAP Business Data Cloud ensures that data keeps the same meaning and relationship when moving between systems in quite insightful ways. Because we are integrating with cross-platforms, many clients now want to move from their on-premise systems to the cloud and gain some footing in AI. When considering the size of data for big companies or organizations in the energy sector or manufacturing sector, which have multiple landscapes across their business, everyone wants to integrate everything. In that scenario, SAP Business Data Cloud is quite helpful for live data reporting, replication, and data transformation.
From my POC experience, I can say we can assume definitely around 30 to 40 percent time saving.
With SAP's AI capabilities in SAP Business Data Cloud, there are some parts integrated, but I am not convinced or impressed as much as I am with traditional data warehousing. For example, there was one component called data generator available in SAP Business Data Cloud. It was transforming a previously built data model in BW to the DataSphere model. However, we have seen some disturbances where the data model built on custom functional modules needs human dependency. It was not transforming exactly as much as our requirement. That is one point.
The second point is about the Insight app; I am not that happy about this. It can be improved. For the Insight apps, they need to be shared through other reporting platforms because of client requirements. One of my clients was from the manufacturing sector and wanted to try the Insight app. They wanted some reports in SAC and some reports in Power BI. However, the Insight app is not available; we cannot share this Insight app to Power BI. That was the issue we faced. This is a limitation.
In SAP Business Data Cloud, to help different AI assistants stay in sync and share the same business rules so they do not give conflicting information, I feel SAP still builds all these AI capabilities into a closed system. If you compare other data engineering stacks, they are openly integrating and partnering with other platforms. They are much more advanced and much more ahead of their time in comparison to SAP Business Data Cloud.
SAP Business Data Cloud does support AI or ML enabled with new use cases in our organization. There are some apps we want to develop, and it is not only limited to SAP Business Data Cloud. We are trying to integrate Joule capabilities into SAP Business Data Cloud. For example, if we are doing a greenfield implementation, on top of these tables, we have to create the CDS view for optimized extraction. In that case, we are trying to do this CDS extraction and CDS code writing using Joule AI automation. That is something SAP could directly integrate into SAP Business Data Cloud. It will save us time.
Second, they have given the product generator, so remodeling is a bit easy. The third point is about reporting. The Insight app is not something I am happy with overall. The Insight app concept was not giving end-to-end functionality, and there is a limited scope of customization into that pre-built Insight app. SAP can work on improving this.
I have been using SAP Business Data Cloud for almost one year. Since it was launched, I started reviewing and exploring the possibilities of what we can implement over it.
I would rate the stability at seven out of ten, with ten being the best.
You can take scalability as a nine, definitely nine.
I rate the technical support at eight point five out of ten, with ten being the best.
On the pricing point, I would say it is quite high compared to other solutions that are available in the market. Unless the client's priority is performance and costing is the secondary priority for them, the client is not willing to buy SAP subscriptions.
Comparing SAP Business Data Cloud with other solutions or other vendors, with the open connectors and cloud connector, it is quite easy. There are also OData services and JDBC drivers. There are many ways to integrate, but we mainly use the standard approach. If it is an SAP-based system, then we use a cloud connector. If it is non-SAP systems, like Azure, then we use the open connectors. For example, Qlik Sense or Alteryx.
I have used the self-service analytics in SAP Business Data Cloud, and they help change our data models quickly. It is quite good. They still need some human intervention while we are doing this, but the capability is present. Essentially, we can shorten the development team in this process, definitely. It also reduces our development time. We did not need to develop a requirement again and again. We can reuse those models or Insight apps.
Moving our old data to SAP Business Data Cloud has made our daily operations faster or easier. I have mentioned that many clients have old on-premise systems. Some of them still have 7.5, some moved to BW for HANA. They can now take the private cloud edition. If they move to the private cloud edition, it is very easy. We did not need to do a greenfield implementation. Instead, we can do the brownfield approach. Over there, as I mentioned earlier, there are some disturbances we have seen for custom function modules, but that is quite manageable. Instead of getting a big team of developers, with the help of experts on a particular platform, we can shorten this duration.
Connecting SAP with platforms like Snowflake, Google, or Microsoft has changed the way my team manages and moves data. Many customers are using different landscapes like Databricks, and Databricks is kind of leading organizational data into their AI capabilities. We can now directly work on something, develop some AI capability, or work on AI capabilities or some AI solution that the client requires. With zero delta sharing, it is a bit easy. Instead of storing the data in the traditional way where we used to push the data into another system, we can directly share and do this on our AI agents or generative AI components for direct development in Databricks. That is quite helpful. The zero delta share copy is quite helpful and is also saving a lot of money and is cost-effective.
I am using the integration for SAP HANA Cloud and SAP Business Data Cloud.
This integration affects my management processes as I am working with one manufacturing client who wants a single platform where they want to decommission all their previous different landscapes over the region and want a single global region landscape. In that case, we proposed SAP Business Data Cloud because whatever data we are getting across the platform, we store in a single landscape. We can consolidate and transform into a single landscape. Furthermore, this live replication gives us an edge over traditional data warehousing solutions like BW. This affects things such as time-divided regional divisions due to time zone constraints. Previously, traditional on-premise systems were hosted on on-premise servers. Now, SAP is hosting in the cloud, so it was quite easy to integrate all landscapes into a single platform. This reduces the complexity of the organization.
With SAP, I am using Data Product Studio with SAP Business Data Cloud.
The benefits I have seen in using these two products together are that it is saving time of rebuilding. Suppose someone had already built something according to my requirement. Then, going through the data marketplace, instead of developing everything, I can directly get that data product from the data marketplace. It was saving my implementation and development cost for the project and also time. It is quite helpful.
SAP Business Data Cloud is mostly deployed in the cloud. Now clients want to move to the cloud itself. Most of them want to upgrade to a cloud solution itself. I did not work on a hybrid model solution, but I have heard from my excellence team that they are also trying to implement the hybrid solution as well.
I have worked on the integration with the S3 bucket and Alteryx system. Apart from that, I did not work on other integrations. Most of the clients want to buy the S3 bucket itself because its costing is comparatively very low in the market. Most clients want to store their historical data into the S3 bucket itself.
Most of my clients are from either the energy sector or the manufacturing sector. They are huge clients. I have told you, unless they do not have the priority of performance, then most clients, for the ERP system, are buying an S4 system, but for the integration and for the data engineering, they used to buy or choose other platforms. For this, one section over SAP can work on pricing for the smaller scalar organization.
SAP Business Data Cloud does require some maintenance in that the admin team or Basis team used to take care of these things. Mostly now it is moved to a cloud solution, so it is easy. Prior to the on-premise system, it is quite a bit easier to install the updates right now. The main point is that SAP has really worked on reducing the complexity of installing the updates and on these things, so that was the great part.
I would rate the overall solution as an eight because there are some platform limitations that need to be worked on. Sometimes, the SAP support team itself will give a direct statement that it is standard functionality. That is why I have cut two points. Otherwise, it is quite good.
If the data volume is huge and the priority is performance, then I would recommend SAP Business Data Cloud. I am in consulting myself. I used to recommend to clients that if they want to take performance as their number one priority and they want to get into new technology like AI as well as they want to get into the cloud, then I assure them that they should get into SAP Business Data Cloud. But if cost is their first priority, then they can still take the private cloud edition and transform their old legacy systems in a phase-wise manner over time. However, costing is something that is impacting. From my overall experience, costing is something where other platforms get an edge over SAP.
I would rate this review as an eight out of ten overall.
I have been using SAP Business Data Cloud solution, and typically this involved Data Sphere and SAC. Earlier, when SAP announced SAP Business Data Cloud, it brought Data Sphere, SAC, and Databricks to a single platform. We had already started implementing SAP Business Data Cloud as part of our move from BW 7.5. Then we decided to move out from BW and go to SAP Data Sphere, and that migration was more of a greenfield implementation. We are almost done with the implementation and are almost live all queries on SAC, with the back-end modeling and the entire architecture setup on SAP Data Sphere. SAP Data Sphere and SAC will be moving into SAP Business Data Cloud formation going forward, with Databricks being external, so we are not going in for SAP Databricks, but for an external Databricks.
The integration aspects between SAP and SAP Business Data Cloud are pretty good and seamless. SAP has done a lot of hard work in setting up the right integration and orchestration framework. There are multiple ways to take the data, whether it is remote tables or SLT or database triggers or ABAP connections. All of them work seamlessly, and if I want to take the data out of SAP Business Data Cloud, there are multiple options where we have taken data out to Azure Data Lake using premium outbound as a service and replication flows in Data Sphere. These orchestration aspects are really seamless.
The integration and orchestration have been so good that I do not see any performance degradation or challenges in taking data out from SAP. It has worked well for us, with only a couple of challenges that we have figured out.
SAP Business Data Cloud offers new ways of working compared to the on-premise SAP BW platform. It's a complete shift for both developers and end users, which I feel is a significant improvement.
I see a positive effect from SAP Business Data Cloud on our organization as we consolidate our entire analytics offering, whether it is through traditional reports and dashboards or building a complete data foundation with a single version of truth on SAP Business Data Cloud.
Self-service from an end-user perspective has not been utilized right now. We are in the migration phase, and there is a lot of change management because the business users have to move from BW to SAC. It's a platform change, and currently, we have not enabled the self-service mode for the users; we are allowing them to adjust first. Going forward, the plan is to create models across different business verticals.
There is a long way to go with SAP Business Data Cloud. There are areas where more insight applications could be developed beyond what's currently available for people intelligence. We would like to see applications around supply chain, manufacturing, and maintenance that could provide automated insights directly from the system.
In my current role, I have been in the data and analytics field for almost 16 - 17 years.
Stability and uptime are not problems at all, with proactive notifications for planned downtimes and performance degradations.
The scalability of the platform is good as it is cloud native; I do not see any problems in scaling.
We regularly work with SAP support for any issues and interact with many SAP architects and product management team members regarding new features. The interaction has been good, and the support has been adequate without any challenges. I would rate SAP support an eight because the support is proactive, with timely updates and good resolution to problems.
Moving from SAP BW, the earlier analytics and data warehousing platform. We switched because SAP moved to the cloud with SAP Business Data Cloud, aligning with our goal to adopt a cloud-native strategy for analytics and ERP.
BW has a lot of objects, including cubes, DSOs, ADSOs, composite providers, and multi-providers, and there is a lot of flexibility in the system. One needs to really think through what logic gets incorporated at what piece in Data Sphere, and you need to plan well in terms of translating a particular flow from BW to Data Sphere. It also involves limited access to CDS views that were not supported while we moved from ECC to S/4HANA. The entire logic was rewritten or re-implemented with SAP tables, and we needed to see what stage we were in when it comes to SAP as an ERP core versus what my strategy is to avoid any future rework.
I am proceeding with my implementation team.
We did not want to move out of the SAP platform, especially as most of our data resides in SAP BW.
What is coming out in SAP Business Data Cloud is that it is a completely managed platform. There is a lot of standard content available, such as People Intelligence based on SuccessFactors data. Our HR team will want insights from all the data available in SuccessFactors. Pre-built content in the People Intelligent Insight application allows us to install the data products and the application, making it easier to obtain insights from the data flowing from SuccessFactors.
My current plan involves using SAP Joule for some AI use cases, but on SAP Business Data Cloud, AI-related use cases have not been implemented yet since we are in the migration journey. The data foundation layer is being made to support all AI use cases going forward.
The purpose of using SAP Business Data Cloud is to maintain a single version of truth. If we take any SAP data into external platforms for AI or ML use cases, we expose the data out from SAP Business Data Cloud to ensure that the same data is delivered, avoiding scenarios of picking data from SAP into Azure directly.
We have not yet used Data Product Studio. We have started installing some insight applications and data products related to SuccessFactors but have yet to fully explore Data Product Studio.
There is a long way to go with SAP Business Data Cloud. There are areas where more insight applications could be developed beyond what's currently available for people intelligence. We would like to see applications around supply chain, manufacturing, and maintenance that could provide automated insights directly from the system. Overall, I would rate this solution a 7-8 out of ten.
