SAP Business Data Cloud Reviews

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.

The best features SAP Business Data Cloud offers that stand out most include having all the data in one place, which is a significant advantage. With Data Bricks being introduced, the zero copy functionality is another major advantage that is really helpful for development files, allowing data to exist in one place rather than navigating between multiple systems, which creates complexity in our current setup.

I cannot confirm that SAP Business Data Cloud is saving time or reducing errors in my day-to-day work or my team's workflow, but the straightforward integration is valuable for having a business understanding and building flows easily. Currently, we are facing integration challenges in other areas that are quite difficult and require coordination with the infrastructure team to resolve.

SAP Business Data Cloud is adequate, but I feel the complexity that native HANA provided is somewhat lacking in Data Sphere. Though I need to explore it more thoroughly, at a high level it appears that the complexity capabilities in native HANA or HANA Cloud are not fully present in Data Sphere.

Data Sphere layer definitely needs to be improved, and that is my personal view on the necessary improvements.

I have not yet seen a return on investment with SAP Business Data Cloud.

I have been using SAP Business Data Cloud for over a year and have been certified in it, which has made me inclined towards this solution.

I find SAP Business Data Cloud is yet to be stable in my experience. It is good in some respects, but in certain cases it is lacking, which requires further exploration.

SAP Business Data Cloud handles growth and increased workloads adequately in terms of scalability.

My advice to others looking into using SAP Business Data Cloud would be to make use of everything in one place and to utilize SAP Joule and generative hubs, as that is the right forward approach with the coming of AI into SAP.

Private Cloud

Microsoft Azure

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.

SAP Analytics Cloud is a good analytics tool, featuring capabilities such as stories, where the end-user can create their stories and dashboard, and planning functionality for prediction, analysis, and financial planning. You can also build your data model and customize it during your connectivity with that source and build your stories with graphs, charts, and some sort of analysis and details.

You can build financial planning, headcount planning, and payroll planning with multiple versions and multiple scenarios to display actual versus budget on a dashboard.

SAP Analytics Cloud provides benefits such as time savings and cost-effectiveness because anyone using a planning tool traditionally relies on Excel sheets to build planning. Building an Excel sheet for payroll planning with a lot of data and scenarios is very hard and takes time, consuming money from resources at man-day rates. However, when using SAP Analytics Cloud, you simply connect to data, load all your data, and apply one formula to all of them at once, saving time and money.

There are new versions of SAP Analytics Cloud every quarter for customers, each containing multiple functions or enhancements in the application. Regarding the price, it has increased, not decreased.

The price of SAP Analytics Cloud varies in perception among customers. Some customers say it's overpriced while others say it's reasonable; it depends on the use case and the type of customer. For enterprise customers, it's acceptable, but for mid-sized customers, they see it as a significant expense.

I have been working with SAP BI for twenty years.

I am satisfied with SAP's technical support team; they provide very good support.

Positive

Building an SAP Analytics Cloud dashboard on top of SuccessFactors for one module on SuccessFactors or SAP usually takes about a week.

My title is BI Lead Consultant at a company named Intercom Enterprises. On a scale of 1-10, I rate SAP Analytics Cloud a 10.

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.

The best features SAP Business Data Cloud offers are Delta and Zero copy.

The Delta feature and Zero copy benefit my work because Delta helps me move data to the data lake without using more company resources.

SAP Business Data Cloud has positively impacted my organization by federating SAP data, which is now available for all to use.

One specific outcome that shows how making SAP data available for everyone has helped my organization is that we have saved 80% of our time because we are not creating custom reports in SAP anymore.

SAP Business Data Cloud can be improved by being associated with more and more data processing tools.

I have been using SAP Business Data Cloud for six months.

I rate SAP Business Data Cloud overall as nine on a scale of one to ten.

I gave it a nine because it is what the industry needed to expose SAP data into non-SAP tools.

My advice to others looking into using SAP Business Data Cloud is to look at it as a new BW.

I found this interview pretty good, and there is nothing I think should change for the future.

Public Cloud

Amazon Web Services (AWS)

I have been using SAP Business Data Cloud solution, and typically this involved Data Sphere and SAC. Earlier, when SAP announced SAP Business Data Cloud, it brought Data Sphere, SAC, and Databricks to a single platform. We had already started implementing SAP Business Data Cloud as part of our move from BW 7.5. Then we decided to move out from BW and go to SAP Data Sphere, and that migration was more of a greenfield implementation. We are almost done with the implementation and are almost live all queries on SAC, with the back-end modeling and the entire architecture setup on SAP Data Sphere. SAP Data Sphere and SAC will be moving into SAP Business Data Cloud formation going forward, with Databricks being external, so we are not going in for SAP Databricks, but for an external Databricks.

The integration aspects between SAP and SAP Business Data Cloud are pretty good and seamless. SAP has done a lot of hard work in setting up the right integration and orchestration framework. There are multiple ways to take the data, whether it is remote tables or SLT or database triggers or ABAP connections. All of them work seamlessly, and if I want to take the data out of SAP Business Data Cloud, there are multiple options where we have taken data out to Azure Data Lake using premium outbound as a service and replication flows in Data Sphere. These orchestration aspects are really seamless.

The integration and orchestration have been so good that I do not see any performance degradation or challenges in taking data out from SAP. It has worked well for us, with only a couple of challenges that we have figured out.

SAP Business Data Cloud offers new ways of working compared to the on-premise SAP BW platform. It's a complete shift for both developers and end users, which I feel is a significant improvement.

I see a positive effect from SAP Business Data Cloud on our organization as we consolidate our entire analytics offering, whether it is through traditional reports and dashboards or building a complete data foundation with a single version of truth on SAP Business Data Cloud.

Self-service from an end-user perspective has not been utilized right now. We are in the migration phase, and there is a lot of change management because the business users have to move from BW to SAC. It's a platform change, and currently, we have not enabled the self-service mode for the users; we are allowing them to adjust first. Going forward, the plan is to create models across different business verticals.

There is a long way to go with SAP Business Data Cloud. There are areas where more insight applications could be developed beyond what's currently available for people intelligence. We would like to see applications around supply chain, manufacturing, and maintenance that could provide automated insights directly from the system.

In my current role, I have been in the data and analytics field for almost 16 - 17 years.

Stability and uptime are not problems at all, with proactive notifications for planned downtimes and performance degradations.

The scalability of the platform is good as it is cloud native; I do not see any problems in scaling.

We regularly work with SAP support for any issues and interact with many SAP architects and product management team members regarding new features. The interaction has been good, and the support has been adequate without any challenges. I would rate SAP support an eight because the support is proactive, with timely updates and good resolution to problems.

Moving from SAP BW, the earlier analytics and data warehousing platform. We switched because SAP moved to the cloud with SAP Business Data Cloud, aligning with our goal to adopt a cloud-native strategy for analytics and ERP.

BW has a lot of objects, including cubes, DSOs, ADSOs, composite providers, and multi-providers, and there is a lot of flexibility in the system. One needs to  really think through what logic gets incorporated at what piece in Data Sphere, and you need to plan well in terms of translating a particular flow from BW to Data Sphere. It also involves limited access to CDS views that were not supported while we moved from ECC to S/4HANA. The entire logic was rewritten or re-implemented with SAP tables, and we needed to see what stage we were in when it comes to SAP as an ERP core versus what my strategy is to avoid any future rework.

I am proceeding with my implementation team.

We did not want to move out of the SAP platform, especially as most of our data resides in SAP BW.

What is coming out in SAP Business Data Cloud is that it is a completely managed platform. There is a lot of standard content available, such as People Intelligence based on SuccessFactors data. Our HR team will want insights from all the data available in SuccessFactors. Pre-built content in the People Intelligent Insight application allows us to install the data products and the application, making it easier to obtain insights from the data flowing from SuccessFactors.

My current plan involves using SAP Joule for some AI use cases, but on SAP Business Data Cloud, AI-related use cases have not been implemented yet since we are in the migration journey. The data foundation layer is being made to support all AI use cases going forward.

The purpose of using SAP Business Data Cloud is to maintain a single version of truth. If we take any SAP data into external platforms for AI or ML use cases, we expose the data out from SAP Business Data Cloud to ensure that the same data is delivered, avoiding scenarios of picking data from SAP into Azure directly.

We have not yet used Data Product Studio. We have started installing some insight applications and data products related to SuccessFactors but have yet to fully explore Data Product Studio.

There is a long way to go with SAP Business Data Cloud. There are areas where more insight applications could be developed beyond what's currently available for people intelligence. We would like to see applications around supply chain, manufacturing, and maintenance that could provide automated insights directly from the system. Overall, I would rate this solution a 7-8 out of ten.

Public Cloud

Microsoft Azure

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.

SAP Analytics Cloud has improved our organization by providing collaborative features, such as allowing users to chat on reports and create tasks. It supports data exploration, which our users find intuitive and useful. We are transitioning from Power BI to SAP Analytics Cloud, which allows us to drill down to detailed levels and integrate tightly with our SAP architecture.

The most valuable features of SAP Analytics Cloud are its native integration with SAP data and the ability to leverage SAP artifacts. This integration is extremely beneficial and provides something other products can't due to their lack of access to SAP data.

There are several areas for improvement in SAP Analytics Cloud. 

Firstly, features available in SAP Lumira are missing in SAP Analytics Cloud. 

Secondly, the predictive analytics functions, although promising, are currently only suitable for Proof of Concepts (POCs) and not for industrial-scale use. 

Lastly, the pricing model for the planning functionality is quite high and presents an entry barrier.

I have been working with SAP Analytics Cloud for almost one year now.

The stability of SAP Analytics Cloud is very high. I would rate it around nine or ten out of ten. The product is very stable.

SAP Analytics Cloud is highly scalable. I would rate its scalability around eight or nine out of ten.

Customer service and support are generally good, but not the best. I would rate them around seven or eight.

Positive

Before SAP Analytics Cloud, we used SAP Lumira. However, it is a non-cloud product. We also migrated from Power BI because it didn't fit well with our enterprise requirements.

The initial setup of SAP Analytics Cloud can be difficult, especially in a complex environment like ours. It took about six months for the initial integration.

The deployment involved various teams, including networking, Azure team, and cloud team. We needed around five to ten people for the integration, depending on the complexity of the landscape.

So far, there is no specific return on investment to report, as we have just gone live with some of the implementations. However, in the long run, SAP Analytics Cloud is expected to be highly beneficial.

The pricing model for SAP Analytics Cloud is quite competitive, but the cost for the planning functionality is high and can be a barrier to entry. The overall cost can be managed with better billing models during the development phase.

Before choosing SAP Analytics Cloud, I evaluated Power BI and QlikView, but SAP Analytics Cloud was the best fit for a company with an SAP ERP system.

Advice for others looking into SAP Analytics Cloud would be to be aware of feature gaps if migrating from Lumira. Understand that while integrating into your landscape can take time, SAP Analytics Cloud offers far more capabilities, especially for companies with an SAP ERP system.

Hybrid Cloud

I use the solution in my company for financial planning.

The tool's most valuable feature is its integration with other SAP products. There are no special features in the tool we are using. We are using it in a very simple manner, using it for multi-dimensions, financial reports, and reporting.

The technology used by the tool is old, making it an area where improvements are required. All SAP software tools are complex to deploy because they are built in a very complicated manner. You have a lot to learn in the software, and integrating it in general is difficult, whereas the other software tools in the industry have a lower bar set. The bar to enter SAP is high from a knowledge point of view and a thought point of view.

The tool's performance has certain shortcomings that require improvement. Our company was limiting itself in the number of products we put into it. Our pharma company's one plant has around 60,000 planned finished goods, so it can run into millions of finished goods. I don't know how SAP is planning to deploy in companies that have millions of products.

I would like to see some AI capabilities in the tool. I need to see my profitability if I reduced the cost or changed the blend between products or something like that, and it is an area I need to look into. Looking at trends or price changes, my future profitability, and the blend of product quantity, there are a lot of what-if scenarios.

I have two years of experience with SAP Analytics Cloud.

In terms of stability, our company has faced some issues with the tool's performance. When you have a large number of records, like in the case of SAP Master Data Governance, the software starts to be unstable, and so we have to limit ourselves to dimensionality.

SAP is very scalable. In general, SAP supports very big organizations, so it is scalable.

SAP is a very big company that has billions of dollars in revenue. They always give you the best people if you pay. If you pay, you get the right support. I rate the technical support a nine out of ten.

Positive

I have used SAP Master Data Governance, SuccessFactors LMS, and SAP SuccessFactors HR Products.

When it comes to the product's installation phase and if you are a SAP organization and you have good people, then it is not a complex part. If you go to such a software, and you know that your organization decided to deploy SAP, then when you decide to deploy it, you need to invest in people that know SAP and it is not complex.

The time required to deploy the solution depends on your scope. So, if you have a simple project, it will take you six months. A complex project will take you one year. It depends on your scope. Just financial planning in a simple country can take you six months. If you have a bigger project or bigger scope, it could be one year.

The number of people required to install the product again depends on the scope and the size of the project. In a simple project, a handful of people are needed, but for big projects, we need more people to install the solution. If it's a small deployment, you can do it with three people. If it's a big deployment and many countries are involved, you have to keep changing a lot of work, and we have the installation project handled by the vendor with 15 to 30 people from our side. It was a big project with a big scope, so the number of people required to deploy the tool depended on the project scope. I can play basketball in a place with ten people. I can also play it in a place with 55,000 people. Here, the basketball remains the same. The number of people required to deploy the tool depends on the company's size. You can deploy on a small project scale with three people.

The ROI comes after two years, so we will have to see if the tool is reducing our inventory. The ROI is excellent since it can be measured financially. At the moment, I cannot tell you about the tool's ROI because it will be seen after five years.

The predictive analytics in SAP is used in a limited manner.

I rate the tool a seven out of ten.

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.

SAP Analytics Cloud excels in predictive analytics, particularly when dealing with SAP data sources. 

For non-SAP sources like SQL or Oracle databases, it may not be the ideal choice. However, for SAP sources, it's the best fit for both predictive and descriptive analytics.

It's the only product that can do real-time analytics on top of SAP ERP data sources. Most other reporting and analytics tools don't have that capability. It also includes planning features, making it a single platform for analytics, planning, and predictive capabilities. It's a purely SaaS platform.

SAP has integrated a new AI capability called JUEL, which includes natural language processing features. It's still in the early stages, but SAP is investing in its development.

The main area that needs improvement is visualization. Compared to platforms like Power BI or Tableau, SAP Analytics Cloud offers fewer chart components. That's the primary area where I see potential for enhancement.

I have been using it for six years now. 

It's pretty stable. The product has evolved a lot over the past six years. There were some initial challenges, but it's a very stable solution now.

Scalability relies on the power of the backend sources, specifically S/4HANA. Most calculations and data processing happen in the backend, not in SAP Analytics Cloud. As long as your models are well-designed and you have enough power in the backend, scalability shouldn't be an issue.

The customer support is quite good. I haven't experienced any issues getting solutions or fixes when needed. They provide very good support.

Positive

SAP Analytics Cloud is excellent for SAP platforms. It understands the data structure in SAP, so you don't have to rebuild those models in another BI platform. If you try to connect Power BI or Tableau to SAP, you'd need to recreate those models. 

This is a major advantage of SAP Analytics Cloud when working with SAP data sources. However, when working with other data sources, Power BI and Tableau might be better than SAP Analytics Cloud.

It's a cloud-based platform, so no installation or deployment is needed. Integration with other systems can be a little complex, and the learning curve is slightly steep.

It's not about the challenge of integrating. It requires people with specific skills compared to other platforms. When it comes to SAP, the skill set is different, and finding the right people on time can be difficult.

There is ROI, especially with some integrations I've worked on. Many customers used to manually download data from SAP systems and then create reports using Power BI or Excel. With SAP Analytics Cloud, the reporting is done directly on top of SAP data, and everything can be automated. 

This saves a lot of time. In one implementation, users used to spend a week each month creating reports, but now it's real-time, eliminating that time investment.

I'm only familiar with the licensing in India, as models vary in different countries. In India, there's a minimum purchase of 25 users. There are a few different types of licenses:

• BI License: Costs around $30 per user per month.
• Planning and Planning Standard to S/4HANA Enforcement Licenses: I don't have the exact costs for these, as they're not publicly disclosed. You'll need to contact the sales team for that information.

Overall, SAP Analytics Cloud can be quite expensive, with costs potentially reaching $120 to $150 per user per month. However, if you're only interested in live reporting, the licensing cost is similar to other BI platforms like Tableau or Power BI.

It's difficult to give a blanket rating because SAP Analytics Cloud excels when working with SAP data sources. If 85-90% of your data comes from SAP, then it's the best solution. 

However, if you deal with more non-SAP data sources, other solutions might be more suitable. It's excellent for SAP but not necessarily for other vendors.

Overall, I would rate it a seven out of ten. 

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.

In SAP Analytics Cloud, there is a functionality called the best practice reports. SAP provides pre-built reports for certain functions and certain modules. For example, for SuccessFactors and S/4HANA Cloud, there are pre-built reports available which are commonly used by customers. This functionality is very useful, as once connectivity is done, it allows users to easily populate data and generate reports from the system out-of-the-box.

Documentation-wise, we see some gaps when trying to connect different solutions. Some generic documents are available, but the steps maintained are not accurate. There is room for improvement in documentation.

I have been working with SAP Analytics Cloud for around six months.

We faced some complexity during deployment due to the predictive analytics feature. When initial login is given, and predictive analytics is enabled from SAP for me, if done with two different IDs, then two instances are created. This is not documented, and we had to go back and forth with SAP to resolve it.

I would rate the stability of SAP Analytics Cloud around eight on a scale of one to ten.

SAP Analytics Cloud is scalable. I would rate its scalability up to nine on a scale of one to ten.

We are satisfied with the technical support from SAP because when we reached out, we were able to get very good support from SAP colleagues.

Positive

I normally do not deal with the commercials, so I am not aware of the pricing part of it.

From a client perspective, there are different competitors. Some customers compare SAP Analytics Cloud with Microsoft Power BI. However, it's important to compare features like-for-like as they have different versions and features.

At the moment, I would rate SAP Analytics Cloud between seven to eight, so we'll put it as seven, allowing some small gap for improvement. I rate the overall solution a 7 out of 10.

Public Cloud

Other