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

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When I was using SAP Business Data Cloud, I was working for the financial market. Considering the financial market, using the data and how I can present it is crucial. When we come to the accessibility of the data, which is in a very large amount, let's say in a day, I am going with millions and millions of records to be updated, and it has to be synced up with the database. The technology over which we are hosting our data has the capability to deliver that much data whenever it is needed. Considering the fact that as it goes with a larger amount of data, only a few products hold this particular capability to present the data whenever a request comes in, and it has to go with the bandwidth. It should not be that after one hour I'm receiving the data when I clicked. When I click, I need the data immediately or a maximum two seconds delay has to be there. That particular capacity of the hosting platform has to be provided, and that is where SAP Business Data Cloud comes into the picture, catering to this particular request.

For financial purposes, we are using SAP Business Data Cloud, and all of it lands in the same zone.

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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.

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Initially, I used the standalone modules first, starting with SAP's Analytics Cloud and then Data Sphere. Once SAP Business Data Cloud emerged, I transferred to the newer technology immediately to see what difference it might offer.

SAP Business Data Cloud has data validation features present when you're creating models. You can see what happens with the data and observe the transformation either through your actual analytic models where you can see your SQL queries and figure things out, or through the automated validation features that are there. When you click on it, it automatically detects what's wrong or what might be a concern, even if it's not necessarily something wrong, but something that looks a bit odd and that you might need to check out before you deliver a final data model.

I love SAP Business Data Cloud's integration. I appreciate that it's an integration suite into the analytics realm and offers a big data lake environment where you can access everything—the data, the models, the dashboards. It's all in one place with a more unified front and experience. When you don't have the standalone modules and only have outdated tools that are not as sophisticated as the SAP ecosystem, the difference is noticeable right away when you get on to SAP Business Data Cloud. You notice the much more refined experience when using this module.

Since I used Data Sphere and Analytics Cloud as standalone platforms before, it was interesting to see them in an all-in-one platform where everything is integrated, giving a tighter integration between the analytics side and the planning side. It definitely has better governance with handling data specifically because it has one data layer. It's not duplicated models and data scattered in various places. I also noticed how useful it was to handle non-SAP data as well as SAP data, which was more efficient than the standalone modules Analytics Cloud and Data Sphere. That's why I made the shift.

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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 Datasphere, what we created, we replaced these pipelines directly with the data flow where in the SAP Business Data Cloud framework, in the Datasphere 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 Datasphere 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 Datasphere. For any new implementation, we will definitely do it on SAP Business Data Cloud or Datasphere only.

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My primary use case for SAP Business Data Cloud is BW and BDC. It is an enterprise data integration, analytics, and reporting tool. I use it to bring together SAP and non-SAP data sources into a unified business-ready data layer, making it easier to deliver trusted insights across finance, supply chain, and operations reporting.

I have integrated and harmonized data from multiple source systems, creating business-ready data models with consistent definitions and governance. As someone with a BW HANA background, I particularly value how SAP Business Data Cloud helps modernize traditional data warehouse approaches by combining trusted SAP business content with scalable cloud-based management and analytical capabilities.

My main use case for SAP Business Data Cloud is consolidating SAP and non-SAP data for analytics and reporting. I typically use it to create a governed business-ready data set that supports SAP Analytical Cloud, data dashboards, and provides a single source of truth for decision-making across finance and operations. It helps us streamline data integration, improve data quality, and accelerate insight generation.

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One of the use cases I implemented for SAP Business Data Cloud involves data migration, specifically handling scenarios with over 1 million records, which exceeds Excel's limits. We needed to transform this massive data for fixed assets, and due to the limitations of traditional tools like Excel and its Power Query, we turned to Datasphere. We pumped the data into Datasphere, utilized its computing power, and eventually transferred this to SAP's HANA Migration Cockpit for data migration. Additionally, we used it for data validation, transformation, and intelligent lookup.

Another use case was with S/4 that connected through SAP Analytics Cloud for retrieving summarized data regarding asset classes from simulated depreciation, which is significant in size. We had to stage and transform this data in Datasphere before moving it to SAC for visualization, planning, forecasting, and budgeting purposes.

I am indeed using the integration between SAP HANA Cloud and SAP Business Data Cloud. This integration greatly enhances our data management processes by enabling seamless data flow from SAP to SAP Business Data Cloud. We can run reports and apply necessary transformations directly in SAP Business Data Cloud, freeing us from the need to execute heavy reports on S/4, thus significantly improving efficiency.

I have utilized the Data Product Studio in SAP Business Data Cloud. The Data Product Studio has facilitated building and managing data products, though the process is intricate and requires multiple steps for activation and monitoring. It varies based on data requirements; while some users find it beneficial, others revert to previous tools due to dependencies on monitoring and stability issues in SAP Business Data Cloud, which struggles with handling large jobs.

SAP Business Data Cloud has aided us mainly in data migration and in areas like planning, budgeting, and forecasting, where it proves helpful. It contributes to preparing dashboards but lacks efficiency in managing operational reports that rely on large datasets. Thus, while it serves well for summarized views, it falls short when dealing with considerable volumes of data.

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I have worked with SAP Datasphere, 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 Datasphere 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.

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I am an end user of SAP Business Data Cloud. I develop enterprise planning solutions using SAP Business Data Cloud together with SAP Datasphere and SAP Analytics Cloud. I use SAP Datasphere, which is a core capability within SAP Business Data Cloud, to integrate S/4HANA data through CDS Views and create financial planning solutions for CAPEX, OPEX, and HR modules, as well as P&L, Cash Flow, and Balance Sheet reporting.

I want to explore similar use cases with another client like MakeMyTrip. I also want to understand what additional capabilities SAP Business Data Cloud provides compared to standalone SAP Datasphere.

When using SAP Business Data Cloud, I integrate data from S/4HANA using CDS Views and bring that data into Datasphere. Depending on the business requirement, I use replication flows or remote access concepts. I perform mappings while creating dimensions and model the data using standard data warehousing concepts such as star schema. I create reusable dimensions and fact tables using graphical views, joins, and semantic modeling. I typically perform left outer joins wherever required and integrate the dimensions with fact tables based on business keys. I am implementing these concepts independently within SAP Business Data Cloud.

The concepts are similar when integrating data from S/4HANA, but I am trying to implement them using SAP Business Data Cloud architecture. The features are quite helpful and user-friendly, allowing me to understand the implementation better. They also help me debug and perform lineage analysis. While creating graphical views, joins, and semantic relationships, the system helps me understand cardinality and data relationships across the model.

I have not personally used BW Bridge. However, another team on a different project worked on integrating SAP BW data into SAP Datasphere and SAC for an organization in the Kingdom of Saudi Arabia. They exposed BW data through CDS-based models into Datasphere, where Datasphere acted as the unified semantic layer containing SAP and third-party data. The team created analytical models and directly exposed them to SAC. Most calculations, transformations, and calculated dimensions were implemented within Datasphere itself. Very minimal business logic was implemented in SAC, as the transformation and semantic modeling were handled completely within the Datasphere layer.

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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.

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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.

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SAP Business Data Cloud enables us to leverage existing BW data and BW models so that the business can continue while developing new software provided by SAP, which is SAP Data Sphere.

We are working on a project where we are doing a lift and shift of an existing BW system for a couple of countries, France and Germany. The organization has been using SAP BW for the last 15 to 20 years, so they have their models already created in BW, and they use that for their daily reconciliation or their month-end reportings. At the same time, as we are building similar models in Data Sphere, the data that will reside in Data Sphere will only be the new data after the implementation. Using SAP Business Data Cloud, we pull the data from the existing BW system to Data Sphere and then join both of them so that the organization can get the aggregated data for all the 15-20 years directly from Data Sphere. They do not have to use two different reports: the legacy report for the last 15-20 years of data and the new reports, the SAC reports for the recent data. They can find all their solutions or their analysis within Data Sphere.

We are using Data Product Generator to bring in all our transaction data. Similarly, we are bringing in master data so that not only the transaction data, but their attributes for the existing master data can also be leveraged from the legacy system. SAP Business Data Cloud provides flexibility to use or leverage the existing models without having to reload from existing or legacy systems to Data Sphere.

For example, we were building a finance report or a group reporting report in Data Sphere. We did not have to create new objects to load the data from legacy to Data Sphere in full for the last 15 years. What we can do is leverage the Data Product Generator which automatically sends data from BW to Data Sphere as and when the business wants to keep BW as well as Data Sphere in parallel. This definitely provides a cost saving of not storing data in multiple places for a very long time.

Our ECC to BW landscape is getting migrated to S/4 to Data Sphere. All the transactions from the last 15-20 years are in ECC and in BW only. In S/4, the transactions will be done as soon as it is live. Until 2025, all the data resides on ECC and BW. Starting 2026, transactions which are posted in S/4 are coming only to Data Sphere. If the business has to report or create a balance sheet, trial balance report, or P&L reports for one, two, or three years, Data Product Generator will share the existing BW data along with the transactions as well as master data from BW to Data Sphere. Within Data Sphere they can use the legacy data as well as the new data in the same report. Data Product Generator really helps with this.

We are using a use case where we have to send or use, pull as well as push data from multiple third-party applications, which is Anaplan or IBP. SAP Business Data Cloud provides the standard functionality or standard connectors to get data from these third-party systems without creating extensive integrations with a lot of third-party tools or integrators.

For multinational companies, for any organization which is in 20 or 30 different countries, not every country will be using the same ERP, whether that is SAP, Google Cloud Platform, AWS, or Oracle. SAP Business Data Cloud helps with this because it is a fabric where we bring in data from all the different sources, join them, combine them, and then create only one report that will show the combined data for all the countries in a single report. SAP Business Data Cloud's fabric architecture definitely helps with the integration.

We are using SAP HANA Cloud to get data from different non-SAP third-party systems, for example, Anaplan, and then they are updating data to SAP HANA Cloud and then we are just importing and deploying the tables from the SAP HANA Cloud to Data Sphere. It is fairly straightforward and definitely helps quicken the integration part.

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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 Datasphere, and planning to conduct reporting on SAP Analytics Cloud. SAP Business Data Cloud is a consolidated solution that combines Datasphere, 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 Datasphere, 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.

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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.

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SAP Business Data Cloud solution's main use cases center on AI-infused analytics. Previously, SAP Datasphere 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.

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I have experience with SAP Business Data Cloud and have been dealing with it for the last two years. I also use SAP Business Data Cloud myself as an architect.

Our company is a consulting company, and we have already developed many AI products by our own team. We propose these products to everyone, including our customers, for use. However, when questions arise on the analytics part, we also propose SAP Business Data Cloud to the client. We are preparing a PoV and addressing the general question from clients about converting from BW or BW/4HANA to SAP Business Data Cloud. We offer that PoV and the migration model as advisory leaders.

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SAP Business Data Cloud serves as a pass-through solution for data in my project engagement. Whenever data needs to be fed from both SAP and non-SAP data sources, I use a functionality called Datasphere, which is now part of SAP Business Data Cloud, to pass the data through and expose it to different types of visualization tools, which could be both SAP and non-SAP.

In a particular scenario, the client needed historical data maintained in an Excel file, which is a non-SAP data source, along with actual data maintained through SAP S/4HANA standard tables. I created a pipeline and an analytic model in Datasphere that makes a union of data coming from the Excel file. I created a CDS view to obtain the actual data from SAP's standard extractors and standard tables. The CDS view and the data coming from Excel are unioned together, resulting in an analytic model that contains both historical and actual data. The data is passed through to SAC reports through a live connection, which provides real-time insights into this data. SAC stands for SAP's analytics cloud tool, and the data could alternatively be passed to non-SAP tools such as Power BI or Snowflake.

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SAP Business Data Cloud serves as a central data platform while integrating with the data sources across both cloud and on-premises systems. This gives me the flexibility to work with the data regardless of where it resides.

I use SAP Business Data Cloud in a hybrid environment, and my primary cloud provider is Microsoft Azure. The platform integrates data from multiple sources, and Azure has worked well for scalability, connectivity, and data management requirements.

I have used SAP Business Data Cloud Connect to integrate data with external partners for data sharing. The biggest benefits have been faster access to information, fewer manual steps, and more consistent data across systems. Overall, it has made data sharing more reliable and efficient.

The integration between SAP HANA Cloud and SAP Business Data Cloud has helped simplify data management by making data more flexible and consistent across platforms. It reduces manual effort, improves data quality, and supports faster reporting and analytics.

I have used the Data Product Studio in SAP Business Data Cloud to help organize and manage data products more efficiently. It provides better visibility, governance, and consistency, making it easier for teams to find and use trusted data.

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Our main use case for SAP Business Data Cloud is that we are migrating from SAP BW for BW on HANA 7.5 Azure to SAP Business Data Cloud.

Currently, we are on version SAP BW for HANA SAP, specifically SPS 7.5 SPS 23 version, and our main objective is to migrate and upgrade our version to SPS 31 on SAP Private Cloud Edition. We will then be consuming SAP Business Data Cloud functionalities including data products and intelligent applications after we are on SAP Private Cloud Edition.

Regarding our use case and how we are planning to use SAP Business Data Cloud, we will be migrating our existing info providers or data providers into data products through the Data Product Generator. Whenever there is a new requirement, we will be building all new requirements in SAP Business Data Cloud by using data foundation services. At this point, we are consuming only BW on HANA providers as data products. Later, by using the Delta Share mechanism, we will be consuming them in Databricks for machine learning capabilities.

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One of the key use cases for SAP Business Data Cloud is integrating the financial information from various underlying ERPs from a finance standpoint and bringing it into SAP Business Data Cloud, harmonizing it, and creating that semantic layer where everything from across all regions comes together. We then have a global view of how the business is run as a whole, and we use it more often every single day from a financial review standpoint.

Integrating data with external parties or third-party platforms allows us to track sales progress for our consumer client, marshalling data from external sources to provide a broader picture of sales influencers, including consumer behavior and competitors' pricing. By marrying SAP data from S/4HANA with external third-party data, we can help the client make strategic decisions based on a clearer understanding of pricing, discounts, and market trends.

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I have been working with SAP Business Data Cloud for a while now, and the main use cases for it are to streamline data integration and automate processes to improve efficiency.

I use SAP Business Data Cloud to ensure that data keeps the same meaning and relationships when it moves between different systems.

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We are a implementing SAP Business Data Cloud for one of our customers, a UK customer.

We are using Datasphere from SAP Business Data Cloud and have integrated it with Databricks using the SAP Business Data Cloud Connect service. We have included SAP Analytics Cloud within this package.

We installed all the data packages available on SAP Business Data Cloud and leveraged several out-of-the-box applications from SAP for modeling purposes.

Our business decisions are taken quickly using SAC dashboards. We import all standard data products from S/4 directly with SAP Business Data Cloud, which provides data governance. We pull additional tables from S/4 through a normal connection and perform modeling in Datasphere.

Data is shared through SAP Business Data Cloud Connect from S/4 to Databricks using Delta Sharing. We have connections with CRM through Microsoft CRM via open connectors. We use a CPI tool to connect other third-party systems to Datasphere.

Datasphere serves as the central point of contact for all data, integrating both third-party systems and SAP, which makes reporting easier.

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SAP Business Data Cloud brings a unified foundation and solution for using AI from the embedded Databricks, and it is helpful for creating dashboards or reports in a short span of time using intelligent applications, which also reduces manual errors.

When creating dashboards, consider a working capital or revenue dashboard; you may have your own calculations which might not be suitable for the business you are developing for. However, with SAP Business Data Cloud, you have a unified structure for all businesses with a whole semantic structure. You won't have manual errors, and you can directly plug into the data source or data products to have dashboards and reports.

If you need dashboards or reports regarding a working capital application, you can search in the intelligent application to find a suitable application. For example, if you need a working capital dashboard, you can find it there and connect it with the data source. You can then have real-time data processing in SAP Business Data Cloud with whatever data source you have, whether it is from a third-party source or SAP source. You can connect and have working capital dashboards or reports in a small amount of time without much development. You can use it directly, and even if you need any customization or custom logic, you can make a copy of the model and make the changes accordingly to have it as a separate copy.

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My main use case for SAP Business Data Cloud is the analysis of intelligent applications and customization of intelligent applications, which also includes analytic models and SAC dashboards.

I use SAP Business Data Cloud as a copilot to install the intelligent application, but the actual customization takes place in the analytic model in Data Sphere, and also on the S/4 side. We had some customized fields that we had to bring up and then use them also in the SAC dashboards. You get an intelligent app that also gives you already standardized SAP managed dashboards, and what we do is customize those. We add those fields and then save them under our own folders.

We had a couple of attempts with the CDS views that didn't work to load it up in the customized or in the intelligent app spaces, but in the end, we found a way and we even did a KT about that internally for our IBM colleagues because this is a use case that comes up more often on projects where people already have customized fields. It makes sense to be aware of that before installing SAP Business Data Cloud. In this case, you have to reinstall the intelligent app if you have a new customized field and that needs to be taken into consideration.

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SAP Business Data Cloud is our primary solution to centralize business data from multiple sources and provide trusted analytics for reporting and decision making.

We recently consolidated financial and operational data from different business systems into a unified platform, which allowed the management team to access dashboards properly and generate reports without manual data combination from multiple sources.

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We are using SAP Business Data Cloud for reporting purposes. We work on amortization reports for a car brand company where we need amortization data. For this, we require amortization reports, and we also have purchase contract and purchase order reports. We currently use SAP Business Data Cloud for this purpose.

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My clients mainly use SAP Business Data Cloud for financial planning and financial reporting. For example, clients in the public sector use SEC reporting to evaluate projects, budgeting, and percentage from the budget according to the completion tasks. All of the financial reports on SAP Business Data Cloud as a reporting tool are very accurate and very smart.

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SAP Business Data Cloud was used for an executive-level dashboard, a CXO-level dashboard where leadership could observe and understand how multiple departments with inconsistent figures were performing.

SAP Business Data Cloud has enabled new use cases in my organization.

An example of new use cases that AI and ML support in my organization is predictive demand forecasting within our government organization, where I determine product demand, seasonal trends, inventory requirements, and procurement needs based on AI predictions for business value.

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My main use case for SAP Business Data Cloud is to utilize data primarily for intelligent application deployments, especially in finance, for working capital insights and applications, as well as for data ML/AI use cases with the use of Databricks integrated within SAP Business Data Cloud.

For an example of how we use SAP Business Data Cloud, we utilize in-built applications for finance and working capital. We activate the building content in the VDC and configure connections with the SAP side, resulting in a final dashboard layer built on the SAC side with data movement to the datasphere.

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In the current project, we are implementing an end-to-end financial planning and analysis project where we are bringing the data from S/4HANA into Datasphere and from there we are creating planning models and the dashboards in SAP SAC.

We bring the actual data of AC DOCA table of S/4HANA into Datasphere, where we automate their P&L reporting, balance sheet reporting, and on top of that in Datasphere, we are doing some data transformation, data conversion and at the end in SAC, we are doing a live models which connects real-time with S/4HANA and the business is able to generate their financial statements into SAC using SAP Business Data Cloud via S/4HANA data.

We have integrated Datasphere with S/4HANA, so whatever transactions are getting posted, I can see real-time updates in the SAP SAC dashboard.

The data is just residing in SAP Business Data Cloud because the data coming from the source, S/4HANA, we are validating it in Datasphere and at the end we are showing it in SAP SAC.

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My main use case for SAP Business Data Cloud involves installation of data products and creation of data products, and sometimes ingestion of data to non-SAP data cloud such as AWS S3 as well as ADLS Gen2 and sometimes GCP as well.

The process of creating and installing data products in SAP Business Data Cloud is very simple; I just have to find out the use case for which I am trying to find the data product. If I find any data product that is related or matching to my requirement, I just have to search in the catalog and then click a button to find the data package. Then I install it and automatically, the data gets stored in the underlying object store and if I want, I can proceed further in the datasphere and process whatever is required.

Apart from that, sometimes I use the data products from the BWPC, such as generating the data products on the BW objects using the data product generator, which is also one of my use cases. For one of my clients, I am implementing that use case.

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My main use case for SAP Business Data Cloud is that initially, we had our HR system available in BW on HANA system. SAP is ending the support for BW on HANA at the end of 2027, so the option was to move it to other SAP products or to move it out of SAP products.

Management decided the best option was to move ahead with SAP Business Data Cloud, which also provides a cloud migration. All cloud-native objects will be used, and this advancement is happening while using all the latest tools. This is the reason for moving to SAP Business Data Cloud.

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I use SAP Business Data Cloud on the cloud where I am leveraging various use cases in business data. In my workflow, CDS views to SAP Business Data Cloud provide reports for SAC Analytics Cloud, allowing templates and direct report access for users without disrupting the source from S/4HANA. My use case focuses on planning, fast access, templates, and agents, as multiple cloud versions including PCE and private editions exist, with newly added features also being a consideration.

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My main use case for SAP Business Data Cloud is primarily with SAP Datasphere, but I also help customers connect SAP Business Data Cloud with Databricks.

Currently, customers are transitioning from SAP Business Warehouse into SAP Business Data Cloud, so I am helping customers navigate through that transition.

There are other POCs that customers are trying right now, specific to Databricks, but soon we're going to do it with Snowflake as well regarding my main use case and how I am helping customers with SAP Business Data Cloud.

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SAP Business Data Cloud serves as my primary solution when I need to integrate data. I use SAP Business Data Cloud for data integration, analytics, and reporting to help consolidate data from multiple SAP and non-SAP systems into a centralized platform, enabling user access to trusted data for reporting and dashboarding. It also provides advantages in analytical performance monitoring and generation of reporting, supporting decision-making across the organization.

One specific example of how my team uses SAP Business Data Cloud in a real-world scenario is by creating a centralized executive dashboard for business performance monitoring, where we integrate data from our ERP, sales, and finance systems into a single platform, replacing the previous manual reporting generated from multiple sources, which was time-consuming and led to inconsistent data.

For analytics, we can use the data from SAP Business Data Cloud to get a comprehensive view across systems and provide a trusted foundation for business planning and decision-making.

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For SAP Analytics Cloud, I can describe a few use cases. Most of the time I work on business best practices from business data from SAP Analytics Cloud integrated with SAP S/4HANA through Calc view or through CDS views. I have experience in retail, manufacturing, oil and gas, real estate, and public sectors.

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My main use case for SAP Business Data Cloud is to connect multiple systems and derive data products using customized as well as standard solutions. This includes a data transition to use BW/4HANA and other legacy systems to transfer data to SAP Business Data Cloud PC, private cloud edition, and generate data products based on this.

SAP Business Data Cloud can be used fundamentally in the same way as Databricks where we can send the data to zero-copy sharing data with Databricks and perform machine learning, and then write back data into SAP Business Data Cloud and utilize it in SAP Analytics Cloud. The challenge is based on machine learning that we cannot implement in another tool, so we can use SAP Business Data Cloud for this purpose.

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My main use case for SAP Business Data Cloud is migration, as we have an upcoming migration from Native HANA to SAP Business Data Cloud where we need to transition from Data IQ to Data Bricks in the future.

For one of my recent projects involving HTTP and SAP HTTP, we migrated from native HANA views to SAP Business Data Cloud and built dashboard reports, including SAC and UFL reports.

We have yet to explore other aspects regarding my main use cases for SAP Business Data Cloud. From the Data Bricks perspective, we may integrate the Snow air or tickets API to generate tickets from the dashboard itself, since our current setup integrates HANA, Data IQ, and Snow tickets, and even includes LLM for text generation. This will definitely be a use case where we will leverage Data Bricks and bring SAP data to generate text and display it in the dashboard.

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I left my review on Qlik Analytics Platform and SAP Analytics Hub. We are only using SAP products currently. I have been using SAP Analytics Hub for 20 years now.

I have been using it as a partner, specifically as a partner integrator. We are using SAP Analytics Hub for two reasons: one is for cataloging and one is for sending out data from SAP products to data lakes and others.

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My main use case for SAP Business Data Cloud is reporting and data lake. A specific example of how I use SAP Business Data Cloud for reporting is pushing SAP S/4HANA data into the data lake.

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I have been using SAP Business Data Cloud solution, and typically this involved Datasphere and SAC. Earlier, when SAP announced SAP Business Data Cloud, it brought Datasphere, 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 Datasphere, 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 Datasphere. SAP Datasphere 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 Datasphere. These orchestration aspects are really seamless.

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The main use cases for SAP Analytics Cloud are to build analytics and planning, financial planning, and HR planning using SAP Analytics Cloud on top of SAP ERP, S/4HANA, and ECC.

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All our customers are using SAP Analytics Cloud for reporting purposes and data analytics. They have their data in different databases, and with SAP Analytics Cloud, we are unifying and providing reports using SAP Analytics Cloud and data spheres. View full review »

Our primary use cases for SAP Analytics Cloud are dashboarding and planning. It's integrated with our ERP systems, and we use it to pull data, create models, display charts, and develop dashboards.

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I use the solution in my company for financial planning.

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We use SAP Analytics Cloud to report and generate all our financial reports. Its robust capabilities allow us to create analytical reports using data from SAP and non-SAP sources.

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I'm an SAP consultant. It's primarily used for analytics on top of SAP data sources. It provides live reporting on SAP S/4HANA, the ERP platform. It has real-time connectivity with S/4HANA.

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Our primary use cases involve data insights. We gather data from various sources, including SAP and non-SAP systems, and use SAP Analytics Cloud to generate reports. 

We also leverage DataSphere* to connect to systems that don't have direct connectors within SAP Analytics Cloud, bringing that data into the platform.

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I primarily use it for forecasting and analytical applications.

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My clients, like Bin Quraya and Sadaras, use it. At present, it is used in paper mills for tissues and bundles. Others are construction companies and chemical companies.

I'm given different tasks with deadlines. They want to finish on time. Even if they're given a task two days before, they have to complete onboarding within 24 hours. I'm the implementor. 

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I mostly use it for data insights and industry analytics. There were two use cases that were quite opposite to each other.

One was a truck manufacturing and transportation company. That company both manufactures and runs a logistics company. They use SAP Analytics Cloud for tracking their transportation, to see exactly where the consignment is, where the truck is, what the issue is with the truck, why it failed, where it failed, why it stopped, why the driver is deviating from the defined route, etc.

For the second part, an oil and gas company from the US is using it for basically monitoring their oil wells. They track how much the well is getting explored, which well is currently being used, when it can next be used, etc. So they don't continuously explore a well. They are actually making a rotation between the wells. They keep track of which well is getting explored today versus tomorrow.

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We integrate with the SAP and it encompasses the entire effective practice for various industries. If you're activating SAP Analytics Cloud, it includes dashboards, analytics, and safety statements. It features a comprehensive library ready for use in month-end planning, development, product management, analytics, and dashboards, which is very beneficial. There is a component related to planning. If you already have a planning or budgeting process in place, you can use SAP Analytics Cloud for planning features. The tenant is available for collaboration, allowing different parties to participate in planning and budgeting for new and adaptable cycles.

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We use SAP Analytics Cloud to create executive dashboards for our organizations. It is a comprehensive analytic solution that allows users to review functional data globally in a clear and organized format, and incorporate features for data visualization and analytics.

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Our company uses the solution for planning and financial reporting. We heavily use the solution from the planning side for labor, topics, revenue, cost of sales, and operating expenses. 

We push data from group reporting to SCC and we create models for forecasting and margins. We create dashboards and allow users to comment, analyze transcripts, and compare the actual data. 

We have 150 licenses throughout our company.

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We primarily use the solution to create financial dashboards. 

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We use the product for story building. 

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SAP Analytics Hub serves as a platform for reporting and creating dashboards. It offers powerful capabilities for cross-functional reporting and dashboard creation across various modules, making it a valuable tool.

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SAP used to provide two tools, SAP BI and SAP BPC. The SAP BI tool provided analytics, while the SAP BPC tool provided budgeting and planning functionality. However, We later consolidated these two tools into one tool, SAP Analytics for Cloud. This tool provides both budgeting and analytics functionality.

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We're using the solution for a client who wanted to see live dashboards from backend data in the S/4HANA system, to be transferred into SAP Analytics Cloud.

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Our primary use cases include analytics and integration planning, dashboarding, and data reporting.

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We use this solution for real-time dashboards, modeling data and for predictive analytics. It is used on a daily basis by 300 people in our business. 

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I am a professional consultant and programmer and we are customers of SAP. 

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We use SAP Analytics Cloud for creating dashboards for higher management. Our managers use this for business planning purposes, viewing monthly and quarterly reports, particularly sales, finance, and planned maintenance reports.

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I am using it for the reporting features.

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We are in the experimental stage. We are still using other business intelligence tools. However, we are experimenting with the SAP Analytics Cloud as a possible replacement or alternative.

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I used SAP Analytics Cloud to create a functionality called Digital Boardroom, which is mainly an executive KPI form of presentation for board meetings. In Columbia in 2019, there weren't more than five implementations of this solution. All of them were made by SAP directly. 

The key solution is the implementation I made for a company with over 16,000 employees and about ten lines of business. We consolidated all the information for ten lines of businesses in the SAP Digital Boardroom.

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I work on the planning and price planning and I create dashboards.

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My company uses SAP Analytics Cloud to create reports for clients. I use the solution to develop reports for clients. The clients would be based out of different locations and do analytics, so I create those reports for clients through SAP Analytics Cloud.

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The primary use case is for our client. We implemented the BI Analytics for the executive. SAP also works with the theater boardroom. There is another license policy, but there's more that's dedicated for the dashboard with the touch screen so they can use it for their executive meetings.

The solution is used on PC or mobile. It's deployed on a public SAP cloud.

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We primarily use the solution for the dashboards. 

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We use this solution for data visualizations.

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We're using SAP Analytics Cloud for analyzing financial and commercial information.

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We use Analytics Hub primarily for consolidating different kinds of reports and queries into one, single window.

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I primarily use the solution for reporting. We talk to people in all different roles and in all different types of companies and organizations. It's just to get a more well-rounded scope.

We use it to build a human capital dashboard and I use it to report on workforce data, hires and exits, movements, and items of that nature.

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We have our data stored in SAP BW. SAP Analytics Cloud is now the main Reporting Tool from SAP. We are gradually shifting the reporting from BO Webi / BO Lumira / BEx Wad to SAC.

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We use this solution for financial planning and analysis. We definitely plan to expand our usage of this solution. 

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SAP ERP itself is not a product, it is a suite of products. There are multiple products within SAP ERP or the Business One suit. Analytics for Cloud is one of them. There are multiple other products that we could see if I had different modules. It depends on what module you are.

My primary use for SAP Analytics Cloud Planning is dashboard reporting, forecasting, budgeting, predictive analytics and so on.

SAP ERP products are mainly for business processes improvement.

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I am a developer and I work mostly on the technical side.

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My VP asked me to work with my plan number to figure out how to increase and support our sales region. On the planning admin, I created a model and then imported actual and forecasted data. From that, I was able to determine the variance. We managed to plan this with small amounts of data. 

We created a planning model and enabled it to make a planning checkmark that works with the time category in the tab dimension, in order to bring it down to the lowest granularity, by month, start date, and end date. 

We created an organization dimension. A responsible person to monitor each region is required. Then you can drag and drop the region hierarchy from the parent.

Then, we worked on the calculated numbers, for example, the gross margin, which was the total revenue minus COGS. We then divided that number by total revenue times one hundred. From there, we could pull the data from the file and select source actuality to validate it. 

We performed all of this using SAP Analytics Cloud.

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We use it for publishing financial reports. 

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We use the product for analytics across various business processes and sectors. It helps us analyze SAP ERP data.

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The solution is primarily used for dashboarding and planning. My clients come from various industries, including chemical energy, fertilizers, cement, real estate, and telecommunications.

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The solution is used for planning and budgeting.

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We use SAP Analytics Cloud mainly to get insights into the customer data, such as what type of orders, the type of customers, and correlations among the orders. For example, we also get insights on cash flow, the frequency of orders, and causes for unfulfilled orders.

The data we get from SAP Analytics Cloud is more analytical, where we try to analyze what happened. Based on our analysis, our customers can explain the pitfalls in their current systems.

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Analytics Cloud integrates your system with a platform, takes data from it, and interprets those data. We have two clients using it now.

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We have a partner relationship with SAP Analytics Cloud and use an internal domain.

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We are using it for enterprise-wide analytics. We have on-prem as well as cloud deployments.

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I am an SAP consultant and Analytics Cloud is one of the products that I work with. It is used for business intelligence and planning.

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We are using SAP Analytics for complete enterprise. We are customers and I am a business analytics manager. 

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The solution is good for handling projects via dashboards for finishing projects and understanding budgets (if we're over or not), financials, working capital, et cetera.

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We use it for all our reporting right now. Everything is happening in SAP, and all dashboards are there, and all data comes through in real-time. We have thought management there, and Azure Operations Management is dependent upon SAP.

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We are using this solution for the analysis of the daily sales with this particular project that we are working on. 

We also analyze what items are used daily, and how many items there are. We are using this solution to gather this information.

We are also using this for protection.

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We have many use cases. These include the SAP Analytics platform tool and the SAP Analytics Cloud project. Some of the tools these products provide tend to fit the same situation. But other use cases can depend on the clients' resources including on-premise servers, or on-premise application. There are many installation requirements, for example in Cloud connect. We often need consultancy support from SAP to assist us.

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We use this solution as part of an embedded analytics use case for an ERP application. SAP are starting to embed Analytics Cloud as a solution within their ERP application, which gives you the options for closed-loop analytics, as you go from insights to action within a single ERP application. It can also be used to bring together multiple data sources, different sources of data from various applications and use the application to blend and trade analytics solutions across different parts of the organization. The product suits small to large enterprise, it supports all user types. We are partners with SAP and I'm an analytics practice lead.  

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We are a solution provider and the SAP Analytics Hub is one of the products that we implement for our customers.

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We are a consultant, so we build solutions for customers. Some of their use cases are for dashboarding, business intelligence, predictive capabilities, and planning.

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The version was launched about a month ago. We are in partnership with SAP, we're gold members. We implement SAP a lot. Working with open-source data in terms of Google Drive. 

The primary use case is working with open-source data in terms of Google Drive and other platforms. The environment currently runs on SAP, so SAP Analytics Cloud is a good way to go. The client can get value for money, instead of having to bring Oracle into an environment in which the integration might be clumsy. It makes sense to have SAP on the ground because they are running currently on HANA, which is why SAP was the first option on the list.

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I use it if I want to see boardroom dashboards, or to see a combination of things in a chart. I also use it for planning analysis.

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Although we currently use version 4.2, there are upgrades very regularly. I work for multiple clients and each client has a different version. It depends on the analytics cloud SAP are distributing to their respective clients. For now, we have 10 clients but the plan is to expand this. 

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We are a solution provider and this is one of the solutions that we implement for our clients.

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I primarily use SAP Analytics Cloud for developing automated reports and for developing dashboards. The BW takes queries and provides the reports and dashboards.

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We're using the solution to analyze our clients' data to create dashboards for them to decipher the sales patterns, income generated, geographical locations of sales, etc., to get a better understanding of how to spread out the user base.

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Right now we are doing a PoC on finances and production planning. The most important part is the connectivity and visibility between our legacy system and the cloud. We are testing these things.

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We are a consulting firm and we implement SAP Analytics Cloud for our clients.

This solution is for digital boardroom purposes.

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I am a consultant and SAP Analytics Cloud is one of the solutions that I work with.

We created our queries in SAP BW and then we use them in Analytics Cloud. We have modules like MFI and reports.

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We have been using this solution for story development on the cloud.

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• We use this across the organization to share data via the cloud solution and present to businesses and clients. 
• We use it to visually graph data and view trends. 
• Having it available from the cloud helps us have real-time data and collaboration across teams.

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We use the product for grid storage, retail, and high-level management. 

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