SAP Business Data Cloud Reviews

The usual use cases for SAP Analytics Cloud that I work with are to make it simple, either reporting, or planning, or predictive scenarios.

The capabilities of SAP Analytics Cloud that I consider the most valuable are that all three functionalities are in one tool, and because they are, you don't have to buy another tool to make planning, you don't have to buy another tool to implement prediction. To get some predictive scenarios for your business plan is possible without additional purchases.

I think the areas of SAP Analytics Cloud that could be improved or enhanced are mentioned by users or companies, and they would definitely mention the price in terms of planning licensing. From a consulting point of view, I don't see any major weaknesses. It is reasonably well-developed, and the perfect strength is that innovations are coming on a quarterly basis. It is slightly behind other tools in terms of the number of graphical outputs. Some tools have it faster, but every increment of innovations contains new features. On the other hand, it is perfectly fitting to the SAP environment, with seamless integration to all SAP modules, not only ERP but also SuccessFactors and other tools from the SAP family, for example, integrated business planning for the production planning. This is really a highlight compared to other tools.

I have been working with SAP Analytics Cloud for eight years.

The stability and reliability of this solution are based on the contract with SAP, the cloud tenant contract. The productive environment is stable, with four times a year, there is an upload of the quarterly upgrades, and it is always announced in advance. You have a chance to test it on your test tenant in small increments, so it should not break your productive reports and productive environment.

In terms of the scalability of SAP Analytics Cloud regarding the number of users, you buy the licenses or subscriptions based on some packages, which is differentiated based on the type of license, whether it is just reporting or whether it should cover also planning. A minimum number of planning users is ten, while a minimum number of reporting users is twenty-five, and in some special cases, it can be also only five for demo systems. This varies and needs to be revised with the official SAP pages. Since it is a public cloud service, the consumption of capacity unit goes per the tenant. SAP Analytics Cloud can be used by a small company, and it can be used by a large corporate.

The technical support is a very well-organized service, with a lot of tools for me as a consultant and for the end user on how to contact SAP support and get issues solved. I don't have any concerns about that.

Positive

I do not have experience with Cognos, which is why I was interested in the review, but I am a consultant and I'm implementing SAP Analytics Cloud.

I work for an SAP partner and I am a consultant.

The predictive analytics features of SAP Analytics Cloud include four different tools: regression, time series, and I don't remember the third one now, and the latest edition is Monte Carlo simulation, which works with uncertainties very well. This is also an advantage, and you can implement the result of the prediction to your reporting or to your planning scenarios, doing what-if scenarios.

The interactive data visualization is rather intuitive, and it can work for end users who just run the report and maybe click one filter. You can also create very sophisticated and highly developed dashboards with a lot of scripting and logic behind the screen. It has the tools for every type of user for the analysis.

The process is usually straightforward for me, but the biggest challenge always with the reporting tools is to fit it in the customer's environment. This is always the case with all tools because you need to fit it in their infrastructure and ensure connectivity. All types of connectivity are well described in the connectivity guide of SAP Analytics Cloud. If we struggle with something, it is always on the customer side with their environment, not with the tool itself.

SAP provides enough documentation and enough material for me to find a workaround.

I am not a BI consultant at SAP CZ anymore; I am a consultant in NTT DATA Business Solutions.

I have been working in my current field overall for the past twenty years.

I rate SAP Analytics Cloud as nine and a half on a scale from one to ten, with ten being the best solution and one being the worst.

As an SAP consultant, my use case typically depends on what the client is asking for. We're seeing more and more with SAP Business Data Cloud that it is used in conjunction with S/4 upgrades where companies are moving from ECC to S/4, and at the same time, they're modernizing their BI stack. They have BW in the past, and instead of keeping that and connecting that to S/4, they know they need to modernize anyway, so they modernize this with SAP Business Data Cloud at the same time. I've seen that with three different clients over the past year.

It combines traditional data warehouse features with Data Lake formations, positioning BDC as a true central analytics hub to enable one-version-of-the-truth.

The most valuable feature of SAP Business Data Cloud is not really limited to BDC itself. It's the two core applications, which are SAC and Data Sphere. I think seamless planning is the number one feature that is really advantageous to users and really something that stands out for SAP versus everybody else because no other tool has that feature.

In ensuring that data keeps the same meaning and relationships when it moves between different systems in SAP Business Data Cloud, we're using the catalog function with all new implementations. And we're assigning meta tags and additional information, KPI definitions. The catalog feature in SAP Business Data Cloud is what we're ensuring. When you're creating new models, you rely on the lineage and standard features built into SAP Business Data Cloud or Data Sphere specifically.

What I dislike about SAP Business Data Cloud is that the way they position the data products is a little confusing for users because it is fundamentally different whether you're using data products that SAP delivers or customer built data products. SAP built data products are really valuable content to speed up the implementation cycle. Also, one needs to create custom data products to be able to share data from Data Sphere to Databricks or Snowflake. But that is really not the full-fledged data product feature set that SAP has when they offer their own. So the data you're sharing with the other systems is just a table. That is confusing for users or potential customers because they think they can share the same objects you're using for reporting with Databricks, and you cannot. You can only share tables. If SAP was a little more open and transparent about those differences, I think that would be better.

For everything related to SAP Business Data Cloud, there are still a few things that are a little quirky. I would give the entire solution an eight out of ten.

I have been using SAP Business Data Cloud since its system was released around May last year, coinciding with Sapphire. I started using it immediately in a demo and test environment. The first productive use with a client was about nine months ago.

In terms of stability, I have never seen or heard about any lagging, crashing, or downtime related to SAP Business Data Cloud. That is really the number one advantage. I've been working with SAC as one of the primary components of this tool since 2018, and it's the single most stable tool in the analytics space that I've seen from SAP in my 25 years.

SAP Business Data Cloud is very scalable. There's no issue. You can ramp up and down CPU power and availability as needed on the fly. It scales very well.

Regarding the speed and the quality of the technical support for SAP Business Data Cloud, from that being a new tool and being pushed and promoted by SAP, it is very quick. They're very quick to reply. Even with medium-priority tickets, you get a reply usually in one or two days.

If I were to put SAP's support on a scale from one to ten, I always prefer to find my own solutions, so the search is not very intuitive and the organization of the notes is not very intuitive, but once you raise the message and you get a reply, it's usually useful. I would give it an eight out of ten.

I have worked with various  alternatives to SAP Business Data Cloud.

The initial deployment for a new client using SAP Business Data Cloud, I would honestly say is fairly difficult, but SAP is supporting that. For the initial deployment, you need to rely on SAP's assistance. You need to configure SAP for me, you need to have the proper contractual prerequisites in place. You have to integrate to your existing systems. It is a lot of work and there are a lot of steps that need to happen. I would say it's rather difficult.

From what I think about the pricing of SAP Business Data Cloud, this would have to be specific. From an analytics pricing point of view, it's very good and very competitive. From a planning license perspective, SAC on that side is very expensive if you need developer features. That piece is very expensive. From the BDC formation overall, I would say it is priced right, but it is very difficult to estimate the actual cost. SAP uses the consumption unit concept and it has an estimator and a calculator, but with all the features that you may want to use, it's not very transparent and it is very difficult to determine your cost upfront. That is another aspect that I keep hearing from customers where SAP could really improve if they would be more straightforward with what you really need to have to use certain features and what at the end you will pay for it. The pricing transparency is not very good.

I can name a few alternatives I have encountered, including Power BI, Tableau, and Business Objects.

If I were to compare them, it really depends on the feature we're talking about and what the actual requirement is. If you do a direct comparison of what most companies are doing, which is Power BI to SAC, I think SAC is the better solution in the context of SAP data. What it allows you to do is access the data live, and you don't have to load and replicate and duplicate the data, whereas in Power BI, when you use SAP as the backend, you have to load data to Power BI. This results in data duplication, additional cost, additional time, and it's not real-time. A fundamental difference between the two is SAC allows planning and Power BI does not. It's a completely different tool with many more features.

In terms of user-friendliness, every tool has a learning curve. You have to learn it. In terms of stability, I think SAC is more stable. I've used this at a couple of clients with self-refreshing dashboards that you display on a big screen in a warehouse and you just start it up and it runs. It never crashes, never fails, and shows you data in real time, 24/7. It is a very reliable and stable and mature tool.

When it comes to the actual formatting of things and data blending, there's still a place for Business Objects. No other tool allows a user to pixel-perfect format static reports and the ability to create custom formulas and joins, as Business Objects does. It really depends on what feature people are requiring to be able to say which tool is better. But for what most people do, Power BI versus SAC, I would say SAC is much better, if your backend data is SAP.

In SAP Business Data Cloud, we're using Joule and Just Ask on the SAC side, but we haven't used any other AI features yet.

As I'm a consultant and we're not using this on our own, what I see is that when you train the model in SAC, the answers are fairly accurate. It used to be a gimmick, where you have text-to-SQL basically, where the system translates this. This has improved significantly over the past year. It's actually a feature that you're not only showing to your clients that this is possible, but it's actually usable for them. That has improved significantly.

I have not seen users change data models. When I talk to customers about self-service BI, it's always limited to the front end, such as SAC stories. We have not come across customers who really establish this data steward and data space concept where you have an owner within the business for HR, finance, or sales, which SAP is promoting. We have not come across clients that actually use this. Any self-service is limited to the front-end SAC piece.

Whether SAP Business Data Cloud requires any maintenance on my end depends on how you define maintenance. As with every tool, it's more housekeeping where you keep the system clean and don't clutter it with a lot of test or development objects. Beyond that, no. SAP takes care of that.

We have not used SAP Connect to integrate data with external parties or third-party platforms. All the implementations that we have done are SAP data only. The only external data we've connected was from SQL, using an ODBC connection and the SAP tool DP Agent, but not SAP Connect. We have used BDC Connect, which is that component that you need in SAP Business Data Cloud to be able to share data with an existing Databricks environment.

Overall, I would rate this product an eight out of ten.

There are so many use cases, but in my current project landscape, the main important thing that SAP Business Data Cloud is doing is replacing the current ETL flow from Ehana to BODS, from Ehana to IVP we are sharing by CDS, or from any other sources to Ehana we are bringing by BODS. Those ETL flows are the main use case we are replacing with SAP Business Data Cloud using the data flow.

I can give you a quick specific example. In my current project landscape, we have multiple flows where we are sending the data from S/4 to Azure Data Lake using Ehana as a transformation layer. So from S/4 to Ehana and then again Ehana to the Azure Data Lake. But using SAP Business Data Cloud or Data Sphere, what we created, we replaced these pipelines directly with the data flow where in the SAP Business Data Cloud framework, in the Data Sphere framework, we have the source as the S/4 and the target, we directly selected as the Azure Data Lake. There is no need for the BODS tool for creating the pipeline or the Enterprise Hana as a middle layer to send and process the data. We can just directly send data one to one from S/4 to ADLS using the Data Sphere as a framework or SAP Business Data Cloud.

There are a lot of other use cases also where we are planning to expand our SAP Business Data Cloud. For example, we have a lot of historical data coming from EDW or Teradata systems where those data are not required to keep directly in the HANA modeling space. We have a lot of memory issues happening in our enterprise HANA framework, the XSA framework. What we are planning is, if we move to SAP Business Data Cloud, we can keep those historical data in the HANA Data Lake storage file as a parquet file, and whenever required for any modeling purpose or data load purpose, we can bring them from the data lake storage to our HANA modeling space. Also, we are planning to move our entire architecture. We have already started with BW for the different sectors where BW is approaching sunset time; we plan to move those directly to the SAP Data Sphere. For any new implementation, we will definitely do it on SAP Business Data Cloud or Data Sphere only.

The best feature of SAP Business Data Cloud is that it's a cloud-based solution, making it software as a service. It's no longer confined to only the database, allowing flexibility to work with your application layer. This advantage that BW used to give isn't available in SAP enterprise modeling. The most interesting thing I've faced is the data lake storage; it has enormous data lake storage capability and is already optimized for use. Any data source can just be dumped here, and when required, you can query the necessary part of the data lake for your modeling purpose. You don't need to store everything in HANA disk as we used to do in SAP Enterprise HANA modeling; that was a waste of HANA disk memory. You can use the data lake feature, and the data flow feature also gives flexibility to move data around from any source to any destination without needing any ETL tool. From a flow perspective, this is a very good tool.

In my current landscape, I mentioned that we had to send files from S/4 tables to Azure Data Lake; it used to require considerable effort with BODS, which also involves a licensing cost. Now, with SAP Business Data Cloud, we save on the BODS license and avoid the costs associated with the Enterprise HANA 48 terabyte box. We have saved costs due to the data lake framework. Moreover, with SAP Business Data Cloud, we can easily store petabytes of data, which will help save on costs going forward. We have minimized our BODS reliance and the need for traditional ETL tools. Further integration of tools like SAP IBP within the Data Sphere will enable further removal of existing ETL pipelines, translating to more significant cost savings.

The integration options are quite good, but the interface can be tricky. For example, you have two storage spaces: the data lake file space and the HANA modeling space. In connection settings when creating the HANA cloud connection, you must mention the association with the HANA data lake space. This interface might seem hazy to newcomers. As for performance, I haven't worked with huge data handling in the manner we did in Enterprise HANA. That's a new learning area for me since I haven't explored performance aspects deeply. Integration options are good; I worked on transformation flows, data flows, and replication flows. The replication flow is particularly effective for sending SLT-enabled data using SAP landscape transformation, allowing flexibility with your ABAP CDS or S/4 tables. The data flow is good for sending data from one system to another without needing any ETL feature, enabling the use of Data Sphere directly, while transformation flow is crucial for transferring large datasets within SAP Business Data Cloud or the Data Sphere framework.

I have used SAP Business Data Cloud for the last one year.

In my experience, I rate SAP Business Data Cloud a 7 out of 10. It sometimes behaves unpredictably, but overall it is good and stable.

We are still relatively new to SAP Business Data Cloud in our organization. Our Enterprise HANA box is 48 terabytes, associated with high server costs, and we have NSEs as well. We are planning to fully implement SAP Business Data Cloud in our enterprise landscape, utilizing the substantial storage area of the data lake. Not all data needs to be stored directly in HANA disk, so we plan to separate the data into cold, warm, and hot storage types. Warm data will reside in our regular HANA modeling space while cold data can be efficiently stored in the file. For warm data, we aim to leverage SQL on file or Dremio for HANA Delta Lake capabilities to retrieve data rapidly. This segregation of cold, warm, and hot data using SAP Business Data Cloud will improve how we currently manage all data in HANA disk or memory.

Customer support is good. I have had positive experiences with customer support.

Previously, we used Enterprise HANA and BW as our old solutions before switching to leverage the cloud capabilities and new features aligned with SAP's roadmap.

There were no other options available for consideration.

From a learning perspective, there needs to be better support from SAP. The primary drawback is that while SAP provides access to the Data Sphere as basic learning, it only grants access to the HANA Cloud space, not the HANA Data Lake space. Furthermore, access to custom data product creation or installation is limited. Improving access for learners and customers wishing to understand the tools is essential. The learning documentation and software are not as robust as I would hope from SAP's side.

My advice for those considering SAP Business Data Cloud is to fully leverage its capabilities. Do not focus solely on the Data Sphere; explore SAC, utilize Data Bricks, and employ the HANA Data Lake capabilities for enhanced data models. Engage with innovations including data mesh for unstructured or streaming data.

Regarding SAP Business Data Cloud's AI capabilities, I do not have much idea, but from what I have learned, its AI capabilities mainly reside within the S/4 side, specifically Joule, and also in SAC with natural language processing features. However, I haven't explored much; they target user perspectives by allowing users to create their reports without requiring predefined reports. Users can easily build data models and generate reports through simple queries.

I have worked on some NLP features; the outputs focus on creating basic dashboards along with Joule for S/4. From my experience, they are fairly basic, and I would rate the AI capabilities about 5 out of 10.

In maintaining that data keeps the same meaning and relationships while moving between systems, we ensure that if we create data for sharing to DataBricks or other applications within the SAP Business Data Cloud framework, the data includes proper metadata and semantic information. For instance, we always assign a unit to revenue quantities or currency data to maintain meaning. When sharing data products between systems including DataBricks for machine learning, we ensure all dimensions and measures maintain proper semantic associations.

We haven't fully moved the old BW data to SAP Business Data Cloud yet. We have utilized the data product generator for brownfield implementation when moving traditional BW objects to SAP Business Data Cloud. For new sectors, we are forgoing BW in favor of greenfield implementations.

I have observed challenges with SAP Business Data Cloud, mainly in terms of database direct access. You have to navigate through the administration cockpit for database queries. In SAP BW, we lacked direct database access, which I feel should change in SAP Business Data Cloud going forward. Users should have proper access to HANA cloud, allowing easy usage of the graphical view and checking performance or functioning of calculation views or table functions. The performance-checking aspect lacks a bit due to the need to filter or assess at a node level. There is a tricky interface challenge in working with the HANA cloud and HANA data lake. The custom data product creation feature also seems complex, requiring a data sharing cockpit profile and more.

I rate SAP Business Data Cloud an overall 7.5 out of 10.

I have worked with SAP Data Sphere, and Business Data Cloud is a recent introduction because I am currently working on a critical S/4 transformation. Currently, the analytics landscape is on B4, and they are moving to Business Data Cloud, so that is where I am working with SAP Business Data Cloud. Although I have worked on different parts of it like SAP Data Sphere previously, it has been more than two years since I have worked on it.

When I talk about Business Data Cloud, I have been an out-and-out SAP analytics person, and I have worked on almost all of the versions of BW that were available, seeing both the good and the bad sides of it. A lot of it is basically expectation management. Earlier, when SAP introduced improvements, it primarily focused on its process orientation and how this process orientation can be put into data used for analytics to provide a cross-functional and in-depth view of business functions. However, many big enterprises do not realize that when this product is sold to them, they might be promised certain features, but technology has its own limitations. For example, when I was working with something called TREX, which was BW Accelerator, people put in huge amounts of data into just processing that. When the transition to HANA happened, there were many gaps regarding how you can have a powerful engine in a Ferrari, but you cannot use a Ferrari to tow a truck. My point is that if your data model is poorly designed, no matter how good the processing is, it will not support it, and that is supposed to fail. You cannot expect HANA to run five years of data at once and process everything; that is not possible. So it is important to understand that at the end of the day, while it does have a lot of processing power, it is just a technology system.

You should focus a lot on the design aspects before you embark on a journey to implement any newly designed product or newly introduced product in the market for your reporting or analytics requirements. You need to understand what to do and what not to do with that product. For example, when HANA came into the picture, one report designed for financial leadership faced issues because they executed many different variants at the same time using a single query from an existing workbook. That is expected to fail no matter how good the product is. Your data and your best practices are non-negotiable when you are designing or implementing; having qualified people on-ground with thorough design evaluation is essential while embarking on that journey.

So if I look at SAP Business Data Cloud compared to the traditional data warehouse, you can have a data lake or a data warehouse, whatever the case may be. SAP Business Data Cloud sort of eliminates the need for extensive technology integration; you do not have to build ETL pipelines. It is sitting on one single cloud, essentially a product as a service, and it integrates directly with HANA in native tables, handling all data replication and availability for you. Compared to BW, you can trust the data products from Business Data Cloud because the data comes directly from your book of records, such as S/4HANA or any functional system you are referring to. So it represents a paradigm shift from how BW or traditional warehouses worked with SAP.

Business Data Cloud provides added functionality where you do not need reconciliation; you just need to ensure that your KPI definitions are on point and broadly aligned with your various analytics requirements, so you can trust your numbers. Within SAP, there is a lot of focus on trusting your numbers, as sometimes downstream errors can skew the overall reporting. For example, I worked with a client where a copy-paste error inflated their overall inventory drastically. Here, you can trust your numbers more effectively; you can set different priorities and identify outliers, which simplifies analytics. You need to have a deeper understanding of your processes, so the time to value increases.

Time to value has significantly increased because there is a lot less dependency on your traditional IT organization. If I am working with finance leadership, I can have my own person managing a universe on top of finance data, define the requirements for them, and they can generate reports. The integration with AI and ML makes my life much easier, and while I have not explored Databricks in depth yet, whatever I have heard about it providing add-on capabilities is a game changer.

For now, we are still in the evaluation and setup process of Business Data Cloud. Those evaluations continue, but definitely, the integration with AI and ML capabilities would provide more flexibility in adding business value. For example, you can schedule predictive maintenance based on your existing data and define heuristics for automating order fulfillment, managing order cost dynamics and inventory according to the requirements. This gives a much better flexibility and predictability to proceed.

The best feature of SAP Business Data Cloud, in my opinion, is the flexibility it gives me to have business content identified and installed. The good thing is that any customizations can be outsourced to BTP, making any necessary changes or migrations much easier. Since the data and everything is hosted by SAP, it reduces my dependency on allied teams regarding business dependency. For authorizations, I have more control; I can manage my own space and access. Additionally, the part of Business Data Cloud that includes Data Sphere comes with SAC as a bolt-on, making my base reporting much more accessible, even though I might need additional licenses for planning, but that is acceptable.

SAP Business Data Cloud provides added functionality where you do not need reconciliation; you just need to ensure that your KPI definitions are on point and broadly aligned with your various analytics requirements, so you can trust your numbers. Within SAP, there is a lot of focus on trusting your numbers, as sometimes downstream errors can skew the overall reporting. For example, I worked with a client where a copy-paste error inflated their overall inventory drastically. Here, you can trust your numbers more effectively; you can set different priorities and identify outliers, which simplifies analytics. You need to have a deeper understanding of your processes, so the time to value increases.

SAP Business Data Cloud could be improved by publishing broad guidelines on how to handle it correctly, perhaps specifying certain things not to do. For instance, my current structure requires extracting, transforming, and loading data, but Business Data Cloud operates more in BW modeling in HANA mode. You still need your SQL joins, but you only need to persist data when necessary. If it can introduce agents to accelerate data modeling or aid development, that would provide extra flexibility. For example, if I need to make customizations, I could define specifications, and an agent could develop that on BTP and integrate it with my BDC, giving me additional flexibility and a better time to value from the development cycle while adhering to SAP's recommended coding standards.

I would not honestly give any product a perfect rating. However, one area where Snowflake has gained traction is dynamic workload management. I am uncertain if SAP Business Data Cloud provides that feature, but if I have certain reporting demands and the system is at its limit, jobs can fail. It should offer automated workload management, and while SAP can charge for it, such a feature would prevent higher workloads from causing system failures and disruptions.

I have been in this field for almost 18 to 19 years.

As far as stability and availability go, the current landscape hosted in AWS has generally met expectations. Barring a few human errors, we have not seen significant availability issues. In a typical quarter, the availability has been over 99%; in a few cases, it dropped to around 98.5%, but overall, I do not anticipate availability being an issue.

Since SAP Business Data Cloud is completely hosted, I believe scalability should not be a problem. Based on the need, additional licenses or resources can be procured, so I do not see scalability as an issue.

In my experience, I would rate SAP support as two to three out of five.

To get accurate help, I have noticed that the first-level support staff usually do not devote much attention to the case. For example, when I provide a set of instructions, they often simply ask me to implement those steps without checking whether they are applicable. If I need a response on the same day, I am 99% sure that it will not be resolved within that timeframe.

I have not used the self-service analytics features extensively. I am more focused on the data modeling side. However, I have seen that the self-service analytics or the ad-hoc analytics available for B4HANA has not been leveraged much. I have noticed people moving to Snowflake or Power BI for self-service analytics. From what I have read about SAP BDC, I think that it could be very helpful and could help keep businesses on board with the SAP ecosystem rather than moving away to other analytics systems.

The integration with AI and ML makes my life much easier, and while I have not explored Databricks in depth yet, whatever I have heard about it providing add-on capabilities is a game changer.

SAP provides an excellent framework for business reporting and regulatory requirements, considering those factors in their solutions. You can comply with regulatory frameworks much better because SAP imposes strict controls, where every change is audited. You can audit and keep track of everything going on. When discussing regulatory frameworks, SAP BW typically forms part of SOX audits, meaning it is a regulated system with proper processes in place. However, if you take data out of SAP, while it offers more flexibility for analytics, it also creates risks—particularly concerning data integrity, such as HR or core finance related data, which could lead to information leaks.

I rate this product an 8.5 out of 10 overall.

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.

SAP Business Data Cloud serves multiple solutions. The primary use case is dashboarding and analytics. Second, customers can use it to create an enterprise lake or lakehouse solution on SAP. Additionally, there is an agentic AI solution, which means on top of the dashboarding or enterprise warehouse, I can run machine learning and AI, generative AI directly on those analytics as well. These are the use cases for which a customer would choose SAP Business Data Cloud.

As a partner, I believe the biggest advantage in the product is that SAP context is maintained. If I don't use SAP Business Data Cloud and I bring SAP data outside to a hyperscaler data lake, I lose the SAP context. Here, SAP context is maintained, and that is the biggest advantage. Additionally, SAP has standard APIs for integrating SAP Business Data Cloud with all SAP products, so I get out-of-the-box dashboards, which means out-of-the-box content, and the APIs are pre-delivered by SAP.

The product helps to eliminate silos between agents with a shared understanding of the business. SAP Business Data Cloud has a unique feature called Delta Share. For customers who have partial data inside SAP and some data outside SAP, they don't need to replicate the same data twice. I can share whatever is already there in SAP Business Data Cloud with hyperscalers and vice versa. If I have some data in Amazon and some data in SAP Business Data Cloud, I can share both of the data with each other bi-directionally, which prevents silos.

The concept of Universal Business Context capability in the product helps to maintain data meaning and relationships across systems. Context is maintained through Data Sphere, which is part of SAP Business Data Cloud, where I can maintain new entity relationships. There is also a feature called knowledge graph, where I can add my own semantics on top of it.

SAP Business Data Cloud has SAP BDC Connect for data integration, which enables the sharing and Delta Sharing of data that I mentioned. The product has support for AI and ML, which helps with integrations to Snowflake or Databricks. Inside SAP Business Data Cloud, I don't have the AI or the machine learning part, but it uses that as a joint offering via Snowflake's machine learning capabilities or Databricks capabilities, or I can reuse hyperscaler capabilities like Amazon, Azure, and Google. I share the data using Connect, and then I run machine learning and pass back the results.

SAP Business Data Cloud includes SAP Analytics Cloud, which is very similar to Tableau and Power BI. The analytical agility feature in the product does impact my ability to work efficiently. Data Product Studio helps to build and manage data products. SAP has been releasing data products from their side, and I can install and activate these data products using the studio. It is created as a plug and play. I can go and select the data product and activate it, which activates end-to-end the entire pipeline, making it fast.

I use SAP BDC Connect with all new partners like Snowflake, Google, and Microsoft. Every version comes out, and today, it is only available for Databricks. By June, I will get Azure and Snowflake, and by October, I will get Google, with every quarter a new partnership being announced.

I use integration between SAP HANA Cloud and SAP Business Data Cloud, but that is the standard integration available between all SAP products, not just HANA Cloud. I can get integration with even the LOB solutions of SAP like Ariba.

If we speak about potential improvements or areas for improvement, the primary concern is cost. The main missing element right now is content in all areas. The content is highly limited right now for most of the data products, with only three or four available at this point. Data products are not available for everything, and all are being developed. If I start a project, I have to create it myself or wait for SAP to release it sometime in the future. The most important missing feature is that not all the data products are ready as of today. If the cost could be slightly reduced to make it much more competitive compared to what is available, it would also help.

Cost is quite high when I look at the market and competitors. If I compare the cost with SAP competitors, I find that when creating an enterprise data lake, if I don't use SAP Business Data Cloud and make it directly in the hyperscalers, it is pretty much cheaper than doing the same in SAP Business Data Cloud.

I have been working with SAP Business Data Cloud for approximately one and a half years as a partner with the vendor.

In terms of stability and reliability, there is some downtime, but I find it pretty reliable. The downtime I have experienced occurred only once, and it was down for maybe a few minutes. SAP Business Data Cloud is pretty reliable, and I don't see a major issue there.

SAP Business Data Cloud is scalable. There are no limitations in terms of scale, so it fits both SMB customers and enterprise customers.

Regarding customer support and the technical team, that is a broader topic that doesn't only apply to SAP Business Data Cloud. Since it is fairly new, there is a good amount of support available right now. In SAP's policy, for the first couple of years, the product team is also part of the support team. Currently, I have decent support and no complaints regarding poor service. Judging on my experience, I would rate support from zero to ten points as about eight.

Regarding installation, I would say it is quite straightforward as compared to the competitors. From a complexity point of view, I don't think it is too complex; it is good.

I have observed some ROI with SAP Business Data Cloud. There are advantages, but it is early days because it is just one year out in the market. Once the entire solution is ready, meaning by the end of this year, I will start seeing ROI. While the product is ready and good, I still have to develop all the content. Once the content is available, then it is a faster go-live with lesser cost in implementation, and that would give an ROI.

Setup cost doesn't affect much because I still have to manage the pipelines, but that is about it. Cost is quite high when I look at the market and competitors. If I compare the cost with SAP competitors, I find that when creating an enterprise data lake, if I don't use SAP Business Data Cloud and make it directly in the hyperscalers, it is pretty much cheaper than doing the same in SAP Business Data Cloud.

I am building my own solution similar to SAP Business Data Cloud, so I use both, depending on the customer choice. If customers want to use SAP Business Data Cloud, I sell that. If they don't want to go for it, then I use my own solution on Amazon Data.

A solid rating for SAP Business Data Cloud would be eight points, which reflects my overall assessment of the product.

My main use case for SAP Business Data Cloud involves developing solutions on the cloud by taking data from our in-house BW system, bringing it to the Data Sphere, and planning to conduct reporting on SAP Analytics Cloud. SAP Business Data Cloud is a consolidated solution that combines Data Sphere, SAP Analytics Cloud, and is managed by SAP BTP, which provides AI and machine learning features.

A specific example of how I am using it in a real project involves our SAC standalone system, which has the limitation that we cannot consume a very high volume of data. To address this issue, we are conducting a POC on SAP BW. In SAP Business Data Cloud, we are bringing data from our SAP BW system into SAP Data Sphere, wrangling this data, and planning to create a dashboard in SAP Analytics Cloud while incorporating AI features supported by SAP Business Data Cloud platform.

Regarding my main use case, one challenge we faced was the high volume of data, which led to poor performance in standalone mode, and data loading took considerable time. We have a requirement to consume a high volume of data, meaning billions of data points, not just millions. This capability allows us to provide the business with reports and dashboards that can start at a very high-level company code and drill down to the specific document level.

SAP Business Data Cloud offers a Data Sphere platform for data orchestration and storage, providing excellent features while being connected with BTP and integrating SAP AI, machine learning, and general integration.

The platform's data orchestration and AI integration make a significant difference for my team by featuring native connectivity with Databricks. We can store data in our Data Sphere, utilizing the zero-copy approach to use Databricks machine learning features and bring back data for reporting in SAC platform. We are currently working on a POC for this scenario, where we will consume data in Databricks without making copies and will use it for our dashboarding and reporting.

SAP Business Data Cloud has positively impacted my organization, although it is not fully implemented yet as we are currently conducting the POC. Our business requires using AI and machine learning features, and this tool has advanced capabilities which we want to leverage to provide value and fulfill current and future requirements for the business.

Improvements for SAP Business Data Cloud are needed, especially regarding connectivity, as loading the hierarchy is somewhat complex. A smooth transition is something we want, where we can easily use what we have developed in our SAP BW within SAP Data Sphere or SAP Business Data Cloud platform, as data is an integral part of SAP Business Data Cloud.

Regarding improvements, we need native integration with our existing SAP BW system, which is quite old and has seen investment over the last ten years. There is not an easy way to migrate from our current BW reporting to SAP Business Data Cloud solution, so maintaining both solutions in parallel is necessary. In the future, we hope to find a path to easily migrate from SAP BW to SAP Business Data Cloud, which will be quite helpful. Currently, we are utilizing this solution for new business requirements and not planning to migrate our existing BW to SAP Business Data Cloud yet.

In terms of features, the commenting feature when having a live connection with the Data Sphere is not exceptional. In standalone SAC, when you store data, the commenting feature is excellent, allowing comments at data point layers or multiple layers. I wish they would include commenting with the live connection to the Data Sphere with SAC stories and dashboards in the future.

I have been working in my current field for the last fifteen years.

SAP Business Data Cloud is quite stable.

SAP Business Data Cloud's scalability is good because it is a cloud solution, allowing for scaling based on requirements, which is a beneficial attribute of the software-as-a-service model.

Customer support from SAP is very good; they are assisting us with the POC to ensure successful implementation in the future, providing excellent support.

Previously, I used standalone SAC. Now that it has been repackaged with Data Sphere and BTP, I am moving to a more integrated SAP Business Data Cloud platform.

I have used self-service analytics features in SAP Business Data Cloud to quickly change our data models, which has significantly improved our team's speed, as it is a very good feature—part of SAC and also part of SAP Business Data Cloud—allowing even business users to utilize this functionality effectively.

I have not seen a return on investment yet, but I believe it will provide more features for the business, particularly in AI and machine learning, helping to optimize workloads. While we cannot measure benefits currently, I am optimistic that it will be beneficial in the future, potentially reducing the need for resources.

My experience with pricing, setup costs, and licensing indicates that it is slightly on the higher side, but we are still in the assessment phase and are finding value for the money. If we do not, we may request SAP to provide a discount or reduce the price.

Before choosing SAP Business Data Cloud, we evaluated other options such as Google, but since our data resides in SAP systems, we thought the integration would be much better with SAP, which understands our data's meaning. This allows us to utilize our previous investments by using SAP Business Data Cloud platform.

I believe SAP Business Data Cloud could positively impact my team once fully implemented by providing faster insights and better scalability, as it is a fully cloud solution managed by SAP. Scaling can happen at any time, requiring just a change in some settings and an increase in payment. We currently have licenses for a limited number of users, but in the future, more users will be required. Since this is a software-as-a-service solution, these aspects are crucial.

Regarding SAP Business Data Cloud's AI capabilities, I feel that its governance and security are well-maintained since we have our authorization control via the company code. This ensures that the business cannot access any data outside their permissions, as AI cannot query data outside user access, making it quite well-controlled.

The accuracy and reliability of SAP Business Data Cloud's AI output can depend on the context. Sometimes, when I ask a question, the system interprets it differently and provides an unexpected answer. It can be challenging for the system to understand what I am saying clearly. Our business has high expectations and often compares our features to ChatGPT or Copilot, and while SAP Business Data Cloud is good, it does not quite match those GenAI tools.

SAP's AI uses my company's real official data to provide correct answers. This is the first product where we are utilizing AI and machine learning. Previously, our use of SAC AI within BTP was not effective. With the new SAP Business Data Cloud platform, we are optimistic about achieving more accurate and business-friendly AI and machine learning capabilities.

I have not connected SAP Business Data Cloud to any other AI agents, and I do not believe it is possible for other AI to integrate easily due to security concerns. We have not included any AI agents in our SAP landscape.

We use SAP Business Data Cloud for reporting and dashboarding, ensuring we provide the right context of the data when moving it from our SAP BW system because that data is highly contextualized and not raw. This allows the business to understand the data for their self-service reporting.

Currently, we are not using SAP Business Data Cloud Connect for data sharing as the platform is new, and we do not have that much data to share.

We have not connected SAP Business Data Cloud to external platforms such as Snowflake, Google, or Microsoft, so our data management and movement remain unchanged.

SAP Business Data Cloud is quite stable.

My advice for others considering SAP Business Data Cloud is to start with smaller solutions if you plan to move from SAP BW and see how it fits into your current landscape. It is not a big bang transition. Starting with smaller projects allows for a smoother integration, with the prospect of more capabilities from SAP in the future for migrating fully from SAP BW to SAP Business Data Cloud.

My additional thoughts about SAP Business Data Cloud are that it is a promising, future-oriented product with substantial AI and machine learning features, and I believe that the product is still evolving, so more improvements will come for its components such as SAC, Data Sphere, and BTP. I would rate this product a seven out of ten.

My primary use case for SAP Business Data Cloud is understanding and analyzing business data from multiple sources to generate insight for decision-making. As a part of my certification learning, I focused on how SAP Business Data Cloud integrates data, maintains business context, and supports analytics through data spheres and SAP Analytics Cloud.

For example, in one scenario, I explored how sales, customer, and operational data from different systems can be unified into a trusted data layer, which can be used to create multiple dashboards and business reports. This helped me understand how organizations can improve reporting accuracy and make faster data-driven decisions.

What stood out to me most was the capability to work with a unified business data cloud while maintaining business context. Instead of looking at isolated data sets, the platform helps connect information from different sources, which makes reporting more meaningful and easier to understand.

I also appreciated how dashboards can provide a single view of key business metrics, making it easier to identify trends and support decision-making. From a learning perspective, the integration between data management and analytics was particularly impressive. One challenge I faced initially was understanding the overall architecture and how components such as SAP Data Sphere, data models, and analytics fit together.

Since I am relatively new to this platform, there was a learning curve, but once I understood the data flow, it became easier for me to work with it.

To some extent, my experiences are mainly through training and learning scenarios, but SAP Business Data Cloud helped me understand AI and machine learning that can be applied to trusted business data rather than isolated data sets. Given my background in AI, NLP, and data analytics, one of the use cases that stood out to me is combining business data with predictive analytics to support forecasting and trend analysis.

For example, in my sentiment analysis and market forecasting project, I could see how a platform such as SAP Business Data Cloud could provide governed, high-quality data to improve reliability on AI models and business insights. Another use case was executing reporting and decision support where AI-driven insights can help identify patterns, anomalies, and opportunities more quickly than traditional reporting methods.

What I found most valuable was the connection between AI capabilities and trusted enterprise data. It reinforces the idea that successful AI projects depend not only on the model itself but also on the quality, governance, and business context of the underlying data.

Overall my experience has been positive, but I think SAP Business Data Cloud could be further improved on onboarding experience for new users, because the platform brings together multiple concepts such as data integration, governance, modeling, and analytics. There can be a learning curve for people who are new to the SAP ecosystem.

I would also appreciate more guided tutorials and examples and learning resources focused on real-world business scenarios. That would help new users become productive more quickly. Another area of improvement could be simplifying the configuration and modeling processes, especially for users coming from a non-SAP background. Making these workflows more interactive would improve adoption and reduce the time required to get started.

One area that could continue to evolve is AI experience. SAP Business Data Cloud already provides a strong foundation with trusted business data, but additional AI-driven recommendations, automated insights, and natural language analytics could make it even easier for business users to extract value from the data.

I also think expanding and simplifying integration with a wider range of third-party platforms and data sources would be beneficial, especially for organizations operating in a hybrid environment with both SAP and non-SAP systems. Overall, the platform is very strong in data management and analytics. The improvements I would appreciate are mainly around making advanced capabilities more accessible and reducing complexity for new users.

I have been working in the current field for twelve months. I have been building experience in analytics, AI, and cloud technologies for approximately a year through internships, projects, and certification, including SAP Business Data Cloud.

SAP Business Data Cloud was stable in my experience. During my training and hands-on exercises, I did not experience any significant downtime or reliability issues. Most challenges were related to learning the platform rather than platform performance.

Based on my training and understanding of the platform, SAP Business Data Cloud appears highly scalable. Its cloud-native architecture allows organizations to grow their business and analytics capabilities while maintaining governance, performance, and business context.

I did not directly interact with SAP Business support because my experience was all through certification training. However, I found documentation and learning resources helpful and comprehensive. More beginner-focused examples and real-world scenarios would make the learning experience even better.

Before learning SAP Business Data Cloud, I primarily worked with SQL, Python, Tableau, Excel, Google Cloud, and AWS-based solutions for analytics projects. I was not migrating from another enterprise data platform. SAP Business Data Cloud was my first-hand experience and exposure to a comprehensive enterprise data management and analytics platform.

I do not have production ROI metrics because my experience was in a training environment. However, it improved my efficiency in understanding data integration and analytics workflow, reduced the time needed to understand complex data architecture, and strengthened my abilities to work with data-driven projects.

I do not have direct experience with pricing or licensing because I have used SAP Business Data Cloud in a training environment. From my understanding, it is an enterprise-focused solution where costs can depend on usage, scale, and required capabilities. I was not involved in evaluating and negotiating licenses.

I was not involved in the formal evaluation process. I was familiar with solutions such as Snowflake, Google BigQuery, and Azure Data Services, but I chose to learn SAP Business Data Cloud because of its strong focus on enterprise data integration, governance, and analytics within the SAP ecosystem.

Since my experience with SAP Business Data Cloud has primarily been through certification training and learning projects, the biggest impact has been made on my understanding of enterprise data management and analytics.

One specific benefit was gaining a clear understanding of how organizations can integrate data from multiple sources into a single trusted environment for reporting and decision-making. It also improved my knowledge of data governance and data modeling and analytics workflow. From my project perspective, my background in data analytics and AI has become easier to connect with real data use cases. For example, I was able to better understand how business data could be structured and analyzed to support forecasting, trend analysis, and executive reporting.

While I do not have production metrics to share, it has significantly improved my ability to work with data-driven solutions and enterprise analytics concepts.

It definitely increased my confidence in handling enterprise analytics concepts. Before learning SAP Business Data Cloud, I mainly focused on the technical side of data analytics, such as data processing, machine learning, and visualization. Through SAP Business Data Cloud, I gained a better understanding of how data is managed and governed at the enterprise scale. As a result, I now approach projects with a stronger focus on data quality, integration, and business context, rather than just analytics itself. This helped me think more strategically about how data supports business decisions.

In terms of efficiency, having a structured framework for understanding data flow and data analytics processes reduced the time I spend on trying to connect different pieces of information. It also improved the quality of my work because I became more aware of the importance of trusted and well-governed data when generating insights.

The features that stand out the most to me are the ability to unify SAP and non-SAP data while preserving business context. This helps me create a trusted data foundation for analytics and reporting. Another feature I found valuable is the integration with SAP Data Sphere, which makes data modeling, governance, and access management more streamlined.

I also appreciate the data analytics capabilities through SAP Data Cloud and SAP Analytics Cloud, where users can create dashboards and gain business insights from a single platform. Finally, the platform's support for AI and advanced analytics is very promising because organizations can use high-quality, governed data for forecasting, planning, and intelligent decision-making.

From my experience, the overall process was fairly straightforward. Once I understood the platform architecture and the relationship between SAP Data Sphere and the analytic layer, the interface is designed to help users organize and model data in a structured way. The main challenge for me was the initial learning curve. Since SAP Business Data Cloud includes concepts such as data modeling, governance, semantic layer, and data integration, it took some time to understand how everything connects. However, after working through training exercises and other use cases for creating data models and building dashboards, it became much easier.

One additional feature I would highlight is the governance aspect. Having trusted, well-managed data is extremely important for analytics and AI use cases. SAP Business Data Cloud does a good job of maintaining data quality and business context across different sources.

One concept I found most valuable during my SAP Business Data Cloud training was its focus on preserving business data context and data segments. Rather than simply moving data from one system to another, the platform helps maintain meaningful relationships and business definitions associated with that data. In my training scenario, I learned how SAP Data Spheres and the business data fabric approach ensure that the data remains consistent when it is integrated from different sources.

It reduces the risk of different teams interpreting the same data in different ways. What I found particularly helpful was the emphasis on data modeling, governance, and semantic layers. These capabilities help me maintain consistent business definitions and relations across systems, which is important for accurate reporting, analytics, and AI-driven insights.

Although my experience was in a training environment, I saw the value of connecting SAP Business Data Cloud with external platforms because it helped me reduce data silos and create a more unified view of business information. The biggest benefit is the improvement in data sharing, integration, and access to analytics across different systems.

On a scale of one to ten, I would rate SAP Business Data Cloud an eight out of ten. The platform provides strong capabilities for data integration, governance, analytics, and maintaining business context. I particularly appreciate its unified approach to enterprise data and its potential for AI-driven insights. The reason I would not give it a higher score is the learning curve for new users and some complexity around the set modeling. Overall, it is a very capable platform with a lot of value for organizations managing large-scale business data.

My advice is to start with a clear business objective and invest time in learning the platform architecture and data governance concepts. The learning curve is manageable with training, and the platform offers strong capabilities for data integration, analytics, and AI when used efficiently. I rate SAP Business Data Cloud an eight out of ten overall.

My main use case for SAP Business Data Cloud is to unify and manage enterprise data from SAP and non-SAP sources primarily for reporting, BI, and data integration.

A specific example of how I use SAP Business Data Cloud is for the consolidation of our SAP ERP system with business applications into SAP.

The best features SAP Business Data Cloud offers are unified data access, data governance, and data integration.

I find the unified data access feature most valuable day-to-day due to its strong governance and seamless integration with SAP, which helps support reporting and AI from a trusted data foundation. These features help reduce data errors and improve speed, accuracy, and business insights.

SAP Business Data Cloud has positively impacted my organization by improving data access and reporting through a centralized and governed data platform. Previously, teams spent significant time collecting and reconciling data from multiple systems, but now reporting becomes faster and more consistent, enabling better collaboration between finance and sales.

Since implementing SAP Business Data Cloud, reporting has become 30 to 50 percent faster as business data no longer needs to be manually consolidated from multiple systems. Additionally, we see fewer data inconsistencies due to standardized data storage, improving collaboration among finance, sales, and operations teams working from the same trusted data source. This helps management make faster and more accurate decisions.

I would like to see simpler deployment and out-of-the-box integration with non-SAP systems, as well as enhancements to the self-service analytic features in SAP Business Data Cloud. These improvements would reduce implementation effort and make the platform more accessible for business users.

I have been using SAP Business Data Cloud for the last two to three years.

SAP Business Data Cloud is stable and has been reliable for us, showcasing stable performance, good availability, and consistent results for our reporting and analytics needs.

The scalability of SAP Business Data Cloud has been strong, as it has handled growth in data volume, user demand, and reporting requirements without significant performance issues, making it adaptable to changing business needs.

Customer support for SAP Business Data Cloud has generally been positive, as we have received timely assistance with most issues, and complex cases have been handled effectively through SAP's escalation process.

I would rate customer support for SAP Business Data Cloud an 8 out of 10.

We did not use any other solution prior to this; from day one, we have been using SAP Business Data Cloud.

The setup cost for SAP Business Data Cloud was moderate to high, as expected for an enterprise platform. The licensing process was straightforward once our requirements were defined, and the operational benefits helped justify the investment.

We have seen a return on investment through time savings and efficiency rather than fewer employees; reporting has become 30 to 50 percent faster, and manual efforts have decreased, allowing teams to spend more time on analytics instead of data collection and reconciliation.

The setup cost for SAP Business Data Cloud was moderate to high, as expected for an enterprise platform. The licensing process was straightforward once our requirements were defined, and the operational benefits helped justify the investment.

Before choosing SAP Business Data Cloud, we evaluated options like Snowflake, Data Battery, and Microsoft Azure data services. We chose SAP Business Data Cloud because it integrates with our SAP landscape and provides stronger governance from the data.

My advice for others looking into using SAP Business Data Cloud is to focus first on business goals, prioritize data quality and governance, and start with a few high-value use cases. This approach helps demonstrate value quickly and makes implementation smoother. I would rate SAP Business Data Cloud an 8 out of 10 overall.

SAP Business Data Cloud solution's main use cases center on AI-infused analytics. Previously, SAP Data Sphere and SAP Analytics Cloud provided data analytics based on available data. However, when we want to incorporate non-SAP related data such as inflation prices, shipment delays, or currency exchange rates, we can now infuse these data points with our SAP data to identify lead times, shipment delays, vendor performance, or actual revenue based on currency conversion. These challenges are being resolved because we brought external, real-world data into our Databricks environment, processed it with algorithms, and then displayed the results on the SAP Analytics Cloud dashboard.

The improvements to our organization are significant. We can now integrate external data sources with our internal SAP systems to gain deeper insights into vendor performance, supply chain delays, and financial metrics affected by currency fluctuations. This capability enables us to make more informed business decisions based on comprehensive data analysis.

SAP Business Data Cloud has two most valuable features. First, the platform now includes a designed workflow that enables data to move from one place to another in a more manageable way, whereas previously the environment lacked this flow. Second, the data products represent a significant advancement. Previously, SAP provided business content that required installation and manual data pulling, though it came pre-configured. Now, the data products offer more manageable, refined, and usable work. This approach encourages adopting the standard version rather than pursuing customization, as SAP provides support for standard versions.

Third, the increased customization capabilities allow us to implement algorithms and develop solutions with greater freedom. We have the flexibility to program anything, bring in any data, or conduct analysis with more autonomy than ever before.

We have only scratched the surface of benefits from using SAP Business Data Cloud because it is new for us as well. SAP Business Data Cloud market does not have many available resources, so we brought in resources to train our team. For training purposes, we brought in international currency exchange data and shipment delays data related to ongoing geopolitical situations. We are currently processing this data with our open purchase orders and shipment information to identify what analyses we can perform. Although we have these capabilities available, we have not yet enthusiastically begun using them, but this will be included in our next quarter plan.

In my opinion, SAP Business Data Cloud could be improved in the availability of Joule, which is more focused towards data products. However, if Joule becomes more feasible with custom products, I believe that would significantly improve SAP Business Data Cloud and the AI roadmap that SAP is planning.

I have been working in the SAP analytics field for around seven years.

Regarding stability and availability of SAP Business Data Cloud, the system tenant availability is very good. We do face issues during quarterly releases when systems occasionally go down, but this occurs very rarely. Other than during these quarterly release periods, the availability is excellent.

The scalability of SAP Business Data Cloud solution is excellent because I have reviewed the roadmap extending to 2040 that SAP announced. Since SAP has consolidated everything on one platform, there is ample room to expand as much as needed. Previously, the components were scattered around, but now there is a comprehensive roadmap available.

On a scale of one to ten, I would rate SAP's customer service and support as six.

My experience with deployment of SAP Business Data Cloud is that there were not many requirements. It is essentially a tenant setup requiring licensing only. We already had licensing for SAP Data Sphere and SAP Analytics Cloud, so we simply switched off from one side and switched on to the other side, and then SAP Business Data Cloud became available. There were not many requirements for the deployment itself. However, I must note that the process is quite lengthy. When it comes to purchasing or licensing, the account manager available in Saudi Arabia takes much longer to process. When we have requirements, we want to close them as soon as possible, but the process took a few weeks or even months. This represents a drawback.

I started utilizing SAP Business Data Cloud this year because we changed our licensing category from an individual category to SAP Business Data Cloud. The name itself was announced this year. Previously, it was not a complete package; it operated as silos with SAP Data Sphere as one component, SAP Analytics Cloud as a separate component, and SAP Joule as another separate component. From 2026, and in late 2025, SAP announced the launch of SAP Business Data Cloud as a complete package. The installation approach is different now. Previously, we purchased licenses through SAP BTP, but now there is another platform where we can buy licenses. SAP now provides a complete package as SAP Business Data Cloud.

I would assess the AI features of SAP Business Data Cloud as follows: previously, there were already two or three AI features available. We are currently using Joule as an SAP AI feature, which has natural language processing capability. Joule processes data based on the NLP model and provides analysis based on our requirements and scripts.

Regarding SAP Business Data Cloud's ability to eliminate silos between agents, the answer depends on who we call agents. Agents could be people from outside the organization or from inside the company, and this question contains some ambiguity.

I find that analytical agility in SAP Business Data Cloud is fundamentally about data products. In the agile framework, we have continuous delivery and cannot wait on a waterfall framework for one-by-one delivery. The agility is excellent and has improved significantly compared to the business content approach, which came with certain flaws. For example, some objects that were previously available were not synchronized between systems, with some available in S/4HANA and others not. We had to address these issues. The agility has genuinely improved in this version.

Our company absolutely uses Universal Business Context capability. We have been developing a product that could be utilized as a data product and as a third-party product available globally. If someone needs to use it, they can acquire or import our content and utilize it for their business scenarios or context.

This feature helps in maintaining data meaning and relationships across systems. It is not based solely on data but on architecture, where we develop an architecture that pulls data from our system. When we move toward third-party exportation, the data remains with us, and only the architecture or the flow becomes available to the other parties.

I have not used SAP Business Data Cloud Connect for data integration with partner systems.

We have used the data modernization features in our SAP Business Data Cloud system.

We do not have SAP BW objects because ours was a greenfield implementation. We directly started our journey from SAP Business Data Cloud. If we had BW, we would have used the BW bridge object.

SAP Business Data Cloud support for AI and ML has enabled new use cases in my company by providing amazing freedom to develop algorithms that were previously not available with SAP. Even in SAP Data Sphere, we could bring non-SAP data, but we could not build AI-infused algorithms. However, in Databricks within SAP Business Data Cloud, we can write ML algorithms, train our models, have test cases available, bring in data sets, and have access to these capabilities. It provides so much freedom.

We are currently working with Microsoft, but we have not started with Snowflake because we already have SAP Data Sphere, so we did not pursue Snowflake.

SAP Business Data Cloud is integrated with Microsoft. It is connected with Microsoft SQL Server to bring in non-SAP data.

This integration has affected my data processes in that it did not negatively impact data processing. However, the integration was quite difficult because SAP manages its own security, and we faced issues at the firewall level for whitelisting external IPs, as SAP handles this when a public cloud is available. We faced some difficulties at the firewall level, but the information provided in their guidance and help guides was clear. Overall, we integrated seamlessly.

For SAP HANA Cloud, we are using integration through CPI. We are using it, but not directly through SAP Business Data Cloud.

We have researched the Data Product Studio in SAP Business Data Cloud, but we have not begun using data products as a live feature. However, we are planning to use data products in a new quarter.

My advice to someone researching SAP Business Data Cloud is to consider whether you already have a source system or an SAP ERP in place. If so, I would strongly recommend SAP Business Data Cloud because the ecosystem it builds creates seamless integration between your source system and destination. You will not face connection and integration challenges, which is crucial in analytics as we need real-time analysis available for our data. SAP Business Data Cloud provides a very seamless experience. Additionally, the features SAP provides exceed what the market typically offers. The market usually provides either analysis or a planning tool. Within SAP Business Data Cloud, we have three things: AI-infused capabilities, analytical features, and planning tools all available. Within one package, we gain three benefits within the ecosystem. This is why I would strongly recommend SAP Business Data Cloud. I rate this solution eight point five overall.