SAP Analytics Cloud Reviews

The solution is used for planning and budgeting.

The SKU, the story build all are user- friendly. For the story build one just has to drag and drop it. And for the table, you just need some sort of selections and everything there.

There is plenty of room for improvement. They have different products, and you need to integrate all of them to have one functionality. For example, data extraction happens in Datasphere. Then it would be best if you had some connection between the Datasphere and the SAP Analytics Cloud to get the data, as this is causing headaches sometimes. The knowledge base and Jedox also could be more meaningful. I have tried to search for some specific knowledge base and technology base, and I didn't find them. I have learned it by trial and error.

There is room to improve the integrations between the different products. The AFS, and the Data action, need improvement. Sometimes they release new tools and updates, but not in my area.

I have been using the solution for twelve months.

It is a stable product. I rate the stability a nine out of ten.

It is a scalable solution. Fourteen consultants are using the SAP Cloud for planning and budgeting and are impressed with it as they did not introduce any other tool. I rate the scalability a nine out of ten.

Since it is a stable tool we did not have to contact the technical support team.

The initial setup is a little difficult. It takes time to learn about the Datasphere and the SEB. Actually, I have joined an ongoing project, so I didn't know how much time it would take.

I rate the overall solution a nine out of ten.

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

It's easy to connect Analytics Cloud with other SAP solutions, and it's also effortless to deploy. You don't need much technical skill to set it up. It's as easy as setting up a tablet. I said tablet before. It's very easy to actually set up.

SAP could add more templates to the platform.

We started using SAP Analytics in 2020, then moved the system to Azure. We decided to also use Analytics Cloud as the reporting tool. Analytics Cloud is similar to Tableau, Domo, etc.

Analytics Cloud is a highly stable solution.

Analytics Cloud is scalable because it's cloud-based.

Setting up Analytics Cloud is straightforward. If you use SAP solutions, you can deploy it in a week because there are templates in the system. There are reporting templates you can leverage, but you can also build a custom template in the system. It depends on the number of reports, but it shouldn't take more than a week or two.

The license is very cheap

I rate SAP Analytics Cloud nine out of 10. It's a very useful tool.

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. 

The visualizations have been the most valuable feature.

The integration with other vendors and solutions could be improved. The visualizations and reporting capabilities could also be improved. In a future release, we would like to have access to built-in API capabilities. This would remove some of the manual work involved in reporting. 

I have been using this solution for three years. 

This is a stable solution. 

This is a scalable solution. 

The customer service team are very responsive and knowledgeable. I would rate them a four out of five. 

Positive

An in-house team implemented this solution. 

 This solution offers value for money and you get what you pay for. 

I would rate this solution an eight out of ten. 

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

The most valuable features are on the application side, where you can design applications into your analytics on the platform.

There are many scripting capabilities with a language that is close to JavaScript. It's not exactly JavaScript but it's a spin-off of it.

It has a rich number of templates included that you can enhance.

It's easier to get going on, compared to other solutions. 

Many of my clients are apprehensive when you have to deploy the solution. They ask you if the data could be transferred to visualization software.

It's cloud-based, and what's good about the cloud is that it doesn't need to store any data. It can read your data and generate it from the NetApp file. It can generate your model or how your model is going to look like. You don't need to transfer your data set to the cloud to report on.

It's quite flexible.

The pricing could be improved. It's quite expensive.

I don't know how usable it is for other platforms. 

In terms of connectivity, if you want to report on live data you have to use what is called the calculation view. It's a graphical view of SAP HANNA, but it's quite limiting as a structure.

They need support for more languages, Python for example. I know that Tableau does this quite well.

If you can integrate more features from the programming side, it would enhance analytics especially the languages that are more analytics-based such as R. I think SAP Analytics Cloud supports a measure of R but could be enhanced.

I may have a narrow view of its usage, but I think that it is quite dependent on SAP environments.

I have not encountered any clients who are using it for Oracle ERP or an Oracle database and are reporting are using SAP cloud.   

It's quite, vendor narrow. For an analytics platform, it's quiet, vendor restrictive.

I have been working with SAP Analytics Cloud for a year and a half.

It's quite stable.

It's a scalable product.

We work with medium-sized enterprise companies, but mostly large-sized clients use SAP. Pharmaceuticals can be used as an example.

It has good technical support.

Previously, I have tried Tableau but not project wise in terms of deployment. I have a lab where I can do some trials.

Also, I have worked with PowerBI a little bit but not in-depth.

It's quite expensive and costs a lot to maintain, especially with licensing.

If the client is SAP-based then I would say it's quite okay to implement this product. 

It's stable, provided they have the budget for the licensing which is, I think most of the time, the bottleneck. Also, they have to consider other supply systems, their internal users. What is the diversity, how many of them work on strictly SAP solutions, and what are the compatibility issues where you cannot be stuck with one product?

I think it's pretty much okay provided you can scale and then it depends on how technical the people are. So, we have two variants of it in SAP. 

There is the SAP Analytics Cloud Discovery, which is just mainly for discovery analytics. You basically create SAP reports, nothing advanced. Then you have the Designer, which enables you to do a little bit more scripting and other advanced features. Depending on the end-user population, you can train down towards the pure basic reporting or really develop an application on it.

I would rate this solution a seven out of ten.

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.

I have seen a lot of benefits from using SAP Analytics, but I think people have not yet fully realized its potential. I believe the system is still in its revolutionary stage because it has a lot of capabilities that have yet to be fully explored. In order to take advantage of these capabilities, we need to have a business story and our own analytics or business analytics requirements. I myself have only used SAP Analytics for a very small use case, but I can see how it could be used for enterprise-level planning, reporting, and dashboarding.

The most valuable feature of the tool is machine learning. The machine learning algorithms are inbuilt and strong. I really like that feature because we don't need to do any coding. Normally, we used to do coding in Jupyter notes or Anaconda. It's another tool for analytics or for data science. We used to write Python code, and then try to fetch the data from the backend system, and perform the analysis, based on the batch. SAP Analytics is more real-time analytics and the use case which I use the tool for, with S/4HANA itself. SAP Analytics makes it much easier for me to have the data directly in real-time, to perform this machine learning. I have also seen some good automation features for budgeting and budgeting processes. This combined feature gives a very good flavor to perform the analytics.

SAP has always had one problem with its products, they make them very closed systems that are difficult to integrate. This is not only a problem with SAP Analytics but also with other products, like middleware systems. These systems, such as GRC, reside in the second level of defense, rather than the first. All these analytical systems normally require a huge integration, because they are not working independently. They are dependent on the backend systems. In any analytical system, we don't have data. Basically, we fetch the data or we try to take the data from any recording system such as an ERP recording system, CRM recording system, or any recording system. We perform the analysis in the analytical layer, which is our analytical tool, such as frauds, business integrated screening, SAP GRC, or even the SAC, SAP Analytics for Cloud. All of these require a huge integration. The problem I faced with SAP Analytics was the ease of integration and the cost. SAP Analytics for Cloud is not cost-friendly. we encounter the same issue with all SAP tools. Although SAP has a very beautiful and seamless integration within their system, it is not as easy to integrate them with non-SAP tools, as our Enterprise system does not have all SAP systems. They instead have multiple systems, including Oracle and Microsoft systems. Even though SAP has very beautiful plugins, which we can utilize and get benefit from that, it is not as friendly compared to other tools.

In 2012 or 2013, SAP's interfaces were a big challenge because they were very engineering-oriented and dry, making them difficult for business users to understand. Fiori was introduced as a solution to this problem, and it has been successful in doing so. However, I believe that SAP still needs to work on the integration aspect.

SAC is not the number one tool for analytics. However, if an organization has SAP backend products, then SAC falls within the system of analytics. The system of analytics requires a system of recording, which is the ERP system, CRM, or any other backend system that automates business processes. I believe that a little work is required in that aspect by SAP to improve.

I have been using the tool for several years.

The tool is stable.

I give the scalability a nine out of ten.

Most of the organizations I work for have a maximum attention licensing agreement with SAP, so the support service is amazing. We've never faced any delays with that.

If we have more backend systems using SAP, it's really easy to set up SAP Analytics, but if that is not the case it becomes very difficult to integrate.

SAP Analytics can be very costly to license, which can make it difficult for organizations to implement.

I evaluated SPSS and Alteryx.

I give the tool a seven out of ten.

I was looking for a tool that could help me add value-added services to my department, such as predictive analytics from the audit perspective. I wanted a tool that could analyze text, mostly based on natural language processing. There are other heavy tools that could be applied to the audit lifecycle to improve the process. I was looking for a data analysis tool that would help me roll out the fifth generation of our internal audit department. I considered several options, including SPSS, Alteryx, and SAP Analytics. There is a generation of auditors and assurance professionals called 4.0 or 5.0 who are turning from performing basic analytics to using advanced analytics tools with AI to enhance their audit processes. They are becoming more proactive and using bottom-up analytics. This is a little bit technical for some people. In the same way that we have fourth-generation audit insurance, we have the fourth industrial revolution in the generic industry, we have a revolution in the audit department, a fourth-generation revolution, where we apply AI tools, RPA, robotic process, and advanced analytics to improve our processors. This allows us to perform more audits, 15-20 instead of 10, and to do so using a complete database rather than samples. As an auditor, we will no longer be providing reasonable assurance that we cannot provide everything, we will be able to provide assurance on the entire database. The analytics will automate this process for us, so I'm launching that strategy. In my strategy, I have, for example, some contracts I want to automate instead of reviewing them manually. Each and every contract, for example, comes to the audit department. Instead of reviewing the contract manually, and spending hours, converting this from the OCR text, and then applying the NLP on it, trying to identify the risks and the threats within this contract, and trying to audit based on that risk template, I can automate this process. I'm a certified professional in GRC and ECC. I've been working in this field for a long time. I've seen predictive analytics in action, and I've tried to compare the effectiveness of different tools, like SPSS and Alteryx, with SAP Analytics. I'm doing this because I want to see how much these tools can help me with my overall strategy. But I know that no single tool can guarantee success. We need a bunch of tools. For example, we have this SAP Celonis, which can help us understand business processes and do business process re-engineering and analysis. This SAP Celonis will help automate the process of understanding business processes, instead of having manual meetings with the business and trying to understand everyone's understanding of the process. We can rely on the data to tell us the truth. The central truth is the data. SAP Celonis will take the event log and try to analyze the process on our behalf, and try to give us the anomalies in our business process. The strategy has a different flavor, different tools, and different aspects. SAP Analytics would be more helpful in the audit execution process, and reporting stage. There is another tool that helps with fraud management. It's called business integrity screening. This tool basically fetches data and tests it for us. The tool also gathers information from SAP Analytics for Cloud and performs predictive analytics with strong machine learning algorithms. SAP Analytics is not the only thing I use to achieve my goals. It is a part of my strategy, and it helps me automate certain aspects of my plan.

An organization that has its backend systems as SAP would be making a smart move to go with SAP Analytics, but if they have a mix of SAP or non-SAP systems, I never advise organizations to go with SAP Analytics. An organization that does not have SAP in the backend and still wished to use SAP Analytics should perform a proper requirement analysis first.

We primarily use the solution for the dashboards. 

The close integration with other SAP products is great. 

The initial setup is easy.

It is quite stable.

Technical support is helpful.

The product can scale. 

It's lacking a bit in maturity and we find we can't replace our existing mode 1 analytics tool until it's improved. 

I've been using the solution for 12 months. 

The stability is quite good. It doesn't crash or freeze. there are no bugs or glitches. It's reliable. 

We have about 50 people using the solution right now. They are all business specialists. We find it to be scalable.  

Technical support has been quite good. We haven't had any issues with them. They are helpful and responsive and we are satisfied. 

Positive

We found the initial setup to be pretty simple and straightforward. I'd rate it four out of five in terms of ease of setup. 

The deployment took one to two months and I handled it myself. 

I didn't need any assistance with the setup. I was able to do it on my own. 

I'm not sure which version of the solution we're using. It's likely the latest one.

I'd advise other users that the solution isn't really mature just yet. 

Overall, I would rate the solution a 7 out of ten.  

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

This is a very easy solution to learn. It took us only one month to grasp all of the SAC concepts.

The new Application Design option offers lots of customization options by being able to script in TypeScript (similar to JavaScript).

It provides easy predictive capabilities with a large number of options to choose from, including date handling.

The what-if analysis sets it apart from other reporting tools like Qlik and Power BI!

The most valuable features of this solution are:

• It is Cloud based.
• Predictive analysis
• Application design/analytic application.
• The "what-if" analysis.
• Easy date handling including options for ytd, lytd, etc.
• There are lots of table features including adding comments.
• Responsive pages.
• Smart Insights.
• Smart discovery.

The next release could include features like:

1. A community that creates custom charts.
2. Table cell size formatting.
3. Formatting options for Data Labels.
4. Allowing comments within small teams.
5. There should be more features for the time series charts.
6. Rebuild models without affecting any chart.

SAC is already working on some of these!

My impression is that the stability of this solution is very high.

This is a highly scalable solution.

This solution has excellent support and customer service. It is the best compared to other vendors that I have dealt with until now.

I have used Qlik and Power BI, but after learning SAC I felt that it was better to move to this solution. The main reasons for changing are its ease of use and better capabilities.

Extremely easy setup, since it is cloud-based. Only in the rarest cases is there a failure.

We performed the implementation in-house.

We have realized ROI through improved Business Intelligence and Analytics.

It is a bit expensive, but really worth it, especially if you are already using other SAP tools.

We evaluated several options including QlikView, QlikSense, and Power BI.

My only suggestion is that people try SAC, and start using it.

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

The product could be improved by establishing connectivity with SharePoint because SharePoint has a similar data set that could be valuable to end users and will assist in improving the visualization of a dataset. Currently, we can connect with different major databases. However, sometimes we have difficulty connecting to a SharePoint list.

We have been using this solution for a year and a half.

The solution is scalable.

The solution is stable.

We use both Tableau and SAP Analytics Cloud, and sometimes we find that SAP Analytics performs better than Tableau.

I rate this product a nine out of ten because it is easy to use, publish, and understand.