SAP Analytics Cloud Reviews

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.

SAP Analytics Cloud is coming up with all the algorithms in-built as a function or cloud. We leverage those for predicting different scenarios. SAP has provided a good package for predictive analytics.

We were able to convert everything we came across.  

A few things are industry norms or standards. A data warehouse is available to pull data, change data types, and play with it (manipulate it). All data types don't allow easy changes. For example, if it's numbers, you cannot search with regular expressions. However, some things require exploring or finding regular expressions to show, decide, or conclude. 

In the data warehouse, you're free to make changes. You can make everything text, meaning it's always a string. Even numbers appear as text, giving you the flexibility to work with all columns.

This is a regular feature of a data warehouse, but SAP Analytics Cloud also offers an out-of-the-box visualization package. This is handy for showcasing data, and everything is scalable. You can make changes and codes to see data differently. You can add different visualizations that aren't available in the package, and connect to third-party systems easily.

You have the flexibility of reading metadata. Based on the schema details, you can make necessary changes and resend data while complying with the same schema during syncing. This is useful if you are processing data. Command-line interface (CLI) mode is also available.

Some algorithms are complex and can't be processed by just tagging the data and expecting results. Perhaps SAP could add documentation that data needs to be preprocessed before processing.  

I have been using it for four years now. 

There are two things to consider:

When we talk about SAP Analytics Cloud, it has two parts. 

• One is hardware, which you were calling the data warehouse.
• And second one is the software with machine learning algorithms, packages, or functions.
• There's a third component for coding: either the coding IDE, the in-editor environment, or the code-level integration interface (CLI). 

Both modes are available. From that perspective, it's stable.

From a development perspective, there are enough algorithms available for almost all scenarios. Where it's not available, you're free to add imports, so you're not limited. 

The hardware part is largely supported, and SAP is largely using AWS, so it's okay.

Regarding scalability, I'm referring to what we can do and update and whether there are limitations. So, limitations only apply to the service size you're on. Based on that, we can process data. But that's the hardware part, which SAP doesn't provide as part of the cloud offering. 

On the cloud, SAP allows you to scale up the server size, and then it should work. That's what we observed from a cloud standpoint.

From a scenario-capturing standpoint, I was able to capture almost every scenario I've encountered. There was no issue, even with the complex situation at the hackathon. We simulated a load of around 2,050 and were able to make that possible in the cloud, which was a good use case. 

Besides us, other companies like Accenture, IBM, Deloitte were there. We were the only small-sized company. We are small compared to other big companies participated there.

The customer service and support are okay. The response time is faster. 

Positive

I have worked with Azure as an alternative for two of our clients. They also offer cloud analytics functionality. Their prices are lower, and you might save 40% to 60% compared to SAP Analytics Cloud.

Price is the main part. The second part is their integration with Excel, since it's their own product. Because of Power BI, they have an advantage. They can enable everything they manipulate on the cloud in Excel as well. 

Although SAP also provides integration with Excel, it takes a longer route since Excel isn't an SAP product. SAP might say that Excel and Power BI licenses are subjective. Azure offers a package that includes everything, so you don't count Excel as an additional cost.

The deployment is easy and quick. You don't have to worry much. The steps are provided, and if you follow them religiously, you're done. It doesn't take much time to enable. It's actually the client side (because of their approval protocols), like user enablement, authorizations, etc., that takes more time than SAP's part (as the document and steps are quite elaborate).

If all authorizations are in place, installation takes around a week maximum. It can be done earlier, but some things take time to enable. Last time, it took one working week to enable us, and then around a week to create the tenant and environment (with integration to Backend server). So, it was a two to three-week job.

For deployment, typically, one person handles everything. We added a second person for support when the first person was unavailable. 

One person cannot be available all the time, so we added a backup. Typically, one person should be enough, but a backup should be provisioned. For continuity, a team of two would be good enough.

SAP has out-of-the-box connectors and adapters that allow us to connect to virtually all data sources. SAP has over 350 connectors and adapters combined. So it's really easy to integrate this product with other data sources and systems that we currently use. 

The ROI was faster for the oil and gas company, achieved within 18 months. For the logistics company with analytics (refer to the use case Q/A above), the ROI was achieved within 23 or 24 months. Anything within three years is considered a good investment.

SAP pricing tends to be premium, so it is slightly higher. However, in this case, the premium charges are justifiable because it comes with out-of-the-box connectors and adapters and can still communicate with your on-premise or any other system. It creates a common interface for gaining data insights.

The only suggestion I have is regarding enabling people on the platform, which requires an individual license. This is a concern among clients because even for just viewing, a license is needed since an S-user ID or P-user ID would be created (S-users are usually direct employees, and P-users are contractual employees). Only then can that person access the cloud and the analytics. This can be a bottleneck because clients need to decide who should be granted access.

For example, in a use case where vendors were considered for access to a common solution, the solution met their expectations, but they limited access to only a few vendors. It would be beneficial if this could be adaptable for certain portions, such as viewing only. Maybe a package could be offered for that, which might help SAP expand further.

So, the individual license requirement could be there. Perhaps something for only visualizing or viewing with no changes could be offered at a lower cost or bundled. This would allow companies to enable their ecosystem partners on the platform.

Overall, I would rate it a nine out of ten. It's a good product. I would definitely recommend using it. 

SAP Analytics Cloud is typically based on machine learning algorithms, which are loosely called AI-enabled. AI has three components: machine learning, deep learning, and then AI. AI isn't widely used, but even for machine learning components, we generally call it AI.

Anything beyond machine learning components, almost all algorithms are available. If, for any specific reason, you need something not available, it can be included. So, from an AI perspective, it is very compatible and ready out of the box. All of the data insights are supported by AI algorithms.

People often refer to machine learning as AI, even though AI is typically machine learning or deep learning enabled. Both are present in SAP Analytics Cloud, so it is already AI-enabled.

I primarily use it for forecasting and analytical applications.

If the application has many pages or a page with more charts, it tends to load slowly. Additionally, there are issues with time-dependent hierarchies and when BexQueries change, which can corrupt SAP reports.

Additionally, there is an area for improvement in performance measurement. Currently, it's difficult to identify which objects are causing performance issues.

I have been working with SAP Analytics Cloud for almost three and a half years.

The application has been released to approximately 7,200 users. It is scalable. 

The technical support process is time-consuming. They often request extended access and additional documentation, which can delay resolution.

Positive

SAP Analytics Cloud is superior to other tools in terms of planning and forecasting. However, other reporting tools such as Tableau are more efficient for analytical applications and dashboard design. 

Tableau allows for quicker dashboard creation without extensive scripting, unlike Analytics Cloud, where creating an application can be time-consuming.

The initial setup, particularly enabling and disabling SAML SSO, was challenging due to a lack of comprehensive documentation.

I will start managing the maintenance and development activities in the coming months.

The solution handles data integration adequately, but performance remains a concern. Drilling down on hierarchies takes a long time, which leads to user complaints. We've raised tickets with SAP to address these issues.

I would recommend SAP Analytics Cloud. However, SAP should improve white papers and performance support to enhance user experience.

I rate it a nine.

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. 

In my opinion, it is good for analytics. Everything is in the cloud. You can also use it for non-SAP sources. You can bring in visualizations for the data, for anything. It's a good feature for Analytics Cloud.

Predictive analytics is used for data sources. Sometimes, they are custom; you can bring your custom data source directly from predictive analytics, or we can use custom tables for forecasting. Forecasting and planning for sales and financial balance sheets are done here.

AI has already started this year. AI for ABAP has started, and AI for Analytics processes is there. Joule is one main feature; you can use it within SAP Analytics Cloud. It is used for planning.

All the features are there, maybe except for the one-gauge visualization, which is missing. I've already requested it from SAP. They're planning to put it in SAP. In the future, they're going to bring back a system for one gauge.

To improve the gauge and the dashboards for using the gauge. This visualization is one thing missing in the Analytics process. In Power BI, they're using these tools. Or there is a possibility in Eclipse; we can use RxScript. RxScript is rendered from the router, but on a mobile base, it's not using RxScript. It's not working.

I have been using it for almost seven years now. 

I would rate the stability an eight out of ten. 

It's scalable, and it is on average; this one is good.

I would rate the scalability an eight out of ten. Our clients are medium-sized businesses.

Customer support is good because they're relying on the HANA Cloud database. HANA is a good, fast database compared to other databases. That's why the customers are happy to use it.

Positive

The setup is okay. SAP takes care of everything with the cloud system notes. They change things from time to time, either by themselves or automatically. 

If there's any setup, it's only for your connector. You have to key in the connectors for this. Suppose SuccessFactors is there and HANA Cloud is there; there are different activities for each.

I am an implementer who does SAP implementation. Setup is easy because these days, SAP takes care of everything. They provide a URL for the SAP Cloud, and everything is maintained within SAP since it's cloud-based. If it were on-premise, we would have to set up everything in our company.

The pricing is reasonable. Compared to Power BI, we are a little bit higher. Not much, just a little bit.

I recommend it to other clients as well. The advantage is predictive analytics. We can use it directly without any customization.

Overall, I would rate it an eight out of ten. 

The most valuable feature of SAP Analytics Cloud for data analysis tasks is its compatibility with the SAP ecosystem. It is easy to integrate with SAP ERP and BW systems, allowing smooth data transfer and live connections without much development. This compatibility makes it stand out, especially compared to other systems like Power BI or Tableau, which often require more adaptation and specific development. Additionally, it supports SAP's push towards cloud solutions, integrating well with SAP BTP and other cloud offerings.

To improve SAP Analytics Cloud, I would like to see more advanced machine learning capabilities, similar to those in SAP BTP. Additionally, better support for connecting to various data sources without needing many workarounds or IT-related activities would be beneficial.

Additionally, in the future, I would like to see improved support for third-party systems, lower cost of acquisition, and better graphics and interface design. These improvements would enhance the tool's usability and presentation capabilities, especially for customer-facing reports.

I have been working with SAP Analytics Cloud for about two years.

SAP's technical support is average. Opening a ticket usually resolves issues, and depending on the support level, response times can be as quick as four hours. Overall, it is pretty standard and I would rate the support as a seven out of ten.

Neutral

The initial setup of SAP Analytics Cloud can be complex, especially with specific requests like multiple users logging in with SSOs. We have faced challenges integrating these scenarios, which reflects some complexities within the SAP ecosystem. While compatibility within SAP is an advantage, these technical challenges suggest it could be even more difficult with third-party systems.

We use SAP Analytics Cloud for real-time decision-making by sitting it on top of our ERP system to track the sales pipeline. It helps the sales and executive teams follow the pipeline stages, from data qualification to cash. We use dashboards to display created sales orders, and PRs in SAP, and send invoices, delays, approvals, and billing requests. It helps the CEO and C-level executives easily see our sales progress, expected revenue for the quarter, and overall performance of our product offerings. So far, it is working well.

SAP Analytics Cloud improves our planning by giving quick visibility into what is happening. For example, we can see which customers are interacting with our demo pages. This feedback helps sales be proactive, asking specific questions and offering help based on customer interest. It helps us respond in real-time.

The integration capabilities of SAP Analytics Cloud have benefited our business systems by making adoption easier. Since it uses familiar SAP interfaces and icons, the transition is smoother, requiring less training. While it may not compete with the design aspects of tools like Qlik or Tableau, its compatibility within the SAP ecosystem reduces the workload, thanks to the standardized icons and interfaces.

For first-time users, I would rate the user-friendliness of SAP Analytics Cloud at around six out of ten. For users already familiar with the SAP environment, I would rate it at eight. While compatibility is a strong point, aesthetics, and UI presentation are weaker areas for SAP.

I wouldn't recommend SAP Analytics Cloud for small to medium-sized companies. The cost of acquisition and support can be steep, and integration with third-party systems might be slower compared to alternatives like Tableau or Qlik, which are cheaper and more suitable for smaller businesses.

Overall, I would rate SAP Analytics Cloud as a seven out of ten.

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.

SAP Analytics Cloud has several valuable features. Firstly, it provides dashboards that display the number of candidates who have applied for specific positions, categorized by region, and the duration required to fill each position. Additionally, it shows the number of vacancies awaiting approval or already open based on relevant information. For example, it can illustrate accounts by email or location. It also offers insights into various metrics such as average gains within specified ranges. It can be customized for different domains and scenarios.

It can address specific needs. For instance, it was used by a client to validate national ID numbers for candidates who had previously applied for specific exams, preventing duplicate applications. This functionality allows users to upload relevant data and apply validation checks before proceeding with recruitment processes. It also aids in consolidation. While the product itself lacks native consolidation features, users can create consolidated statements by combining data from various legal entities. This enables users to drill down into specific values and analyze data at a granular level.

SAP Analytics Cloud allows you to quickly perform various tasks in terms of virtualization. CyberArk itself requires some enhancements to better connect with other technologies. While it's easy to connect with SAP, using analytics tools may sometimes necessitate sourcing information from different platforms. You might need data from SAP or other technologies/platforms to access specific information not available within SAP. SAP is effective for managing storage and enhancing virtualization capabilities. However, when accessing data from diverse platforms, complexities may arise.

We are building connectors with other platforms as a service. We develop functions to enhance comprehensive analytics, including predictive analysis, which is required to be integrated into its cloud. 

I have been using SAP Analytics Cloud for four to five years.

The product is not stable.

The solution’s scalability is terrible. 50 users are using this solution.
Utilizing the server in the cloud doesn't require much effort; you simply use it, by the way. It requires the administrators to use this tool.

The initial setup is moderately complex, but not highly technical. It requires someone who understands the features. This individual should know how to use the features, select appropriate storage options, choose suitable graphs for display, and determine when to use specific measurements or build custom ones. 

Since SAP Analytics Cloud is already cloud-based, there are no deployment steps involved. The process mainly entails connecting and configuring the necessary settings. This involves adding your organization as a tenant, providing the username and password, and possibly specifying a company ID or other relevant information.

Deployment and maintenance may require around 21 individuals.

You get the full benefit to assess the affordability of the product over time. The SAP platform offers various products, each serving different needs. They need to have various products available for selection. SAP Analytics Cloud is highly advantageous. 

The product is expensive and has a yearly subscription.

If we are using a scale or another device, but there is no other way to integrate. You can use all of our services. So if you compare SAP Analytics Cloud with Power BI. Power BI has different connectors that make integrations easier. When it starts with SAP Analytics Cloud, it's easy to connect to specific products when possible.

It give compliance with very good visibility. They support the key users inside the organization for identifying specific areas where SAP Analytics Cloud will decline.

Building the dashboard, analytics, and testing some use cases involves integrating with other platforms based on customer requests. 

Overall, I rate the solution an eight out of ten.

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.

The solution is quite effective for collaborative planning. 

It is time for the solution to move to SDP because it is sometimes a challenge to connect to SQL or different prompts. 

The solution requires a license to view reports but other solutions like Power BI allow you to view reports for free. 

Sometimes there are speed issues with big deletion data. The solution can be very slow in retrieving information depending on how huge the data is or how you design the model. You have to check constantly to see if there is garbage in sections that you need to clean up. 

I have been using the solution for two years. 

The solution is stable so stability is rated a seven out of ten. 

The solution can be scaled by purchasing additional licenses. 

The technical support is good so is rated a six out of ten. 

Neutral

We previously used Power BI, SAP BusinessObjects, and Oracle Hyperion. 

The pricing is based on an annual license and is rated a four out of ten. 

Our ERP is SAP so we consolidated all of our tools and implemented the solution. 

I would like to see the new upgrade. There are some things in the roadmap that I want to experience rather than relying on white papers. 

I rate the solution a seven out of ten. 

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.

There is a real-time reporting mechanism in place. SAP Analytics Cloud operates on the SAP S/4HANA database, ensuring real-time reporting is always available. This capability allows the business to monitor cash inflows and outflows at any given moment easily.

When using cloud analytics, you often need to build a staging environment and an aggregation layer if you have different applications. However, since everything is running in the SAP landscape on the HANA database, data extraction and aggregation have become much easier and more efficient at any given time.

There are definitely several areas that need improvement, but articulating them as specific priorities right now is challenging since we just implemented the project and it went live. It's difficult to pinpoint exactly what needs to be addressed.

I have been using SAP Analytics Cloud for five years.

The foundation needs to be stabilized after going live. If the requirements change, such as needing more reports or increased usage of Cloud Analytics, we must address those adjustments.

The system isn't experiencing frequent failures or timeouts, but there are instances when we deal with large datasets. We sometimes encounter high memory usage issues since it's running on our database. This can lead to errors stating that there isn't enough memory to extract data, especially if the hardware isn't adequate. If the hardware can't support the load, it becomes challenging for Cloud Analytics to function effectively.

I rate the solution’s stability a seven out of ten.

Different organizations are utilizing SAP Analytics Cloud; if I consider the end users, nearly 125 users are actively engaged. The usage numbers are relatively high because we're in the banking sector.

It is used quite frequently. Initially, it was mainly utilized for month-end closings, but now it’s used regularly. The reporting mechanism is integrated with SAP Fiori, allowing users to access data and billing reports on various devices, including tablets and smartphones.

I rate the solution’s scalability a seven out of ten.

Support is still improving, and getting support from SAP is a bit exorbitant. 

Sometimes, the queue will be on the queue, and yours may be the P1 ticket. You will be in the queue and not get the best support.

Neutral

We previously used Hyperion, and then Power BI came into the picture. Earlier, many different BW systems were also in use.

Setting up the production server takes about seven to eight working days. However, we also have a sandbox installation where we can monitor the required time, assess downtime, and determine what integrations or standard interfaces need to be enabled and how data flows. From this, we can build a comprehensive inventory of the necessary implementations, integrations, and ports that need to be enabled, including database connectivity and whether we should use the SAP Cloud Integrator or different APIs.

If you have reliable systems, setting up the SAP Analytics Cloud production system typically takes six to seven working days.

We need a basic administrator, a database administrator, an SAP S/4HANA specialist, and a Cloud Analytics expert. Four to five resources are required, but this can vary depending on the project's size, the database's complexity, and the number of reports being developed.

The implementation of SAP Analytics Cloud at British Petroleum was done with a different organization, and currently, I’m working with Standard Chartered Bank. I don't have much visibility into what improvements were made at British Petroleum, as I'm not associated with them anymore. For Standard Chartered, if there are any improvements or business needs, we will evaluate those as we move forward. 

Reflecting on the three projects I've executed, I see that the earlier ones were challenging, particularly regarding server installation and cloud integration with SAP S/4HANA. Over time, the process has become easier with the introduction of different APIs and standard interfaces by SAP. 

I rate the initial setup a seven out of ten, where one is difficult and ten is easy.

It is very expensive.

Business decisions depend on how data is utilized and structured. For example, the finance department needs to monitor revenue management, assess the impact of costs, and evaluate operational expenses. Predictive analytics is invaluable for analyzing revenue, costs, and financial performance. It provides insights on the demand and supply side, making it easier for the business to make informed decisions.

The current project where we've implemented SAP Analytics Cloud went live three months ago at Standard Chartered Bank. We plan to decommission all other reporting mechanisms, such as Power BI, Tableau, and Crystal Reports. We are currently evaluating the output from SAP Analytics Cloud regarding reporting and its collaboration with other applications. It’s too early to say whether Power BI is better than SAP Analytics Cloud or vice versa, as both tools have their strengths and address different needs.

Overall, I rate the solution a seven out of ten.

The tool's most valuable features are the BI and planning functionalities. I value being able to integrate smart planning with BI for analysis. The solution is user-friendly. 

It seems like there's a problem with the tool's licenses. If there are a lot of users, like 200, who only use the solution once a year, paying for a full-year license for each user is expensive. There's no option for users who only use the solution occasionally.

It's like having a watch user option. I want to license users for just two months instead of a year. For example, I have 200 users, but they only need the solution for two months during a process. Even though they only use it briefly, having to pay for a full year for each user can be a problem. 

I have been using the product for seven years. 

I use the tool daily in my work with various processes and customer implementations. The solution is very scalable because it's a cloud-based service. When we need to add more users, I contact IT and request more. There are no issues with scaling up.

The tool's technical support responds in a few hours. 

Neutral

A consultant company helped us with the deployment. We relied on three consultants to help us. 

I've worked with alternatives like Oracle in the past. When comparing solutions, I've learned that using the same platform as the actual data source is better. For example, if you're using SAP ERP, it's better to use SAP Analytics Cloud. Similarly, if you're using Oracle ERP, using Hyperion for analytics is better. The challenge often lies in integration rather than the usability of the solutions. I rate it a ten out of ten. 

I advise new users to design the business processes before starting the implementation. If you clearly understand the business processes beforehand, you will not face problems during implementation. Issues typically arise when there is a lack of clarity or understanding of these processes within the department.