SAP Analytics Cloud vs. SAS Enterprise Guide

>> Using SAC predictive analytics capabilities for inventory management in a Production line setup has helped generate Purchase Requisitions and Purchase Orders for raw or semi-finished goods without much head-banging into Demand management rules. It does it beautifully with seamless integration with HANA core MM and PP modules, along with BI integration. It has resulted in 30% greater warehouse storage capacity, thereby saving revenue from piled-up inventory and associated manpower costs. >> SAC sometimes shows latency in working out a large data set, thus giving a poor user experience compared to its competition. Also, it may occasionally show misinterpretations when embedding data from 3rd-party systems into the HANA core dataset.

Incentivized

For writing out longer code creation for shaping data on complicated reports, the clean UI is helpful. If exploring data though, SAS Studio would be better suited given its easier interface for GUI graph building.

Incentivized

• It makes it easier yo analyse order and related records easily.
• We can easily maintain and track the performance of employees in organisation.
• Can easily track various aspects for the growth of an organisation thus allowing real time analysis and tracking of organisation's growth and performance.

Incentivized

• It can load a huge amount of data as compared to R Studio and Excel.
• Data processing speed is very fast, millions of records are loaded into this software very easily and data manipulation is also very easy.
• Inbuilt Statistical functions and procedures make it very comfortable to use for non analytics professionals as well.

• Possibility of more advanced scripting for data transformation without analytics designer
• Provision to consider rate types from TCURR in SAC and should be able to write FX conversion logic considering rate types
• Read data directly from BW by reading aDSOs backend tables

• I would like to see advance interactions with external databases to be able to kill ongoing queries from SAS. As of now, you can stop pretty much any ongoing process besides the one running on a remote database (killing SAS/EG doesn't stop the remote process)
• When creating prompts for programs, it would be nice to be able to have conditional prompts (based on the selection of other prompts). The prompts are clearly a recent feature and constantly under development but I wish it would be more powerful.
• More of a SAS metadata issue but when loading SAS/EG (first connection to the server), it takes a few seconds which feels like a long time. I really don't understand why the initialization of the session can take so long. Don't get me wrong, this has no real impact on productivity but that 10s delay just feels really like eternity when you want to run some code in a new session.

at the very beginning you need some sort of customizing and user trainings. At the end of the day this pays off. I would highly recommend an extended evaluation phase. That ensures a proper use. Over all - after the first hurdles were taken the application worked pretty smooth

Incentivized

On account of current user experience and the organization-wide acceptance.

I landed on a 7 out of 10 for a few key reasons. The tool is flexible in the sense that we are using very very very (very) little off the shelf solutions and customizing to our needs. Users enjoy having the customized data actions, key variance calculations, and easy to use headcount/salary planning in the same tool. One downside is that users are hard to please when they are used to excel. SAP Analytics Cloud simply is not excel, and the flexibility of excel in a crunch is not there.

Incentivized

It's not all bad, but I don't believe that an enterprise purchase of SAS is worth the expense considering the widely available set of tools in the data analytics space at the moment. In my company, it's a good tool because others use it. Otherwise, I wouldn't purchase a new set of it because it doesn't have some of the better analytical functions in it.

Incentivized

I would rate SAP Analytics Cloud an 8 out of 10 for scalability. It offers a flexible, cloud-based architecture that supports expansion across departments and geographies. The platform adapts well to growing data volumes and user needs, making it a strong choice for organizations looking to scale analytics capabilities efficiently.

Incentivized

I would rate SAP Analytics Cloud’s performance an 8 out of 10. Pages generally load quickly, and reports run within a reasonable time frame, even with complex datasets. Integration with other systems is smooth and doesn’t noticeably affect performance. Overall, it’s a responsive and efficient tool for business analytics. But

Incentivized

Since the implementation stage, the support team has been very helpful and assisting. Even in the later stages, the tech team had quite a rapid response. In general, SAP has provided us with great customer support, let it be for a specific product of SAP or for integration of different modules.

Incentivized

Although I use SAS support for information on functions, these are SAS related and haven't really come across anything that is specifically for SAS EG.

Incentivized

Good videos and reference material available in SAP Portal.

Incentivized

In hindsight, it would have been easier to have someone there in person. Questions were answered, but with 11 participants, it got a bit chaotic online

Incentivized

SAC is a simple solution ad it works fine when connecting it to other SAP tools. On the other hand, connecting it to third party solutions brings difficulties when there's no previous design and the objetives are not clear. It is really important to integrate Business users from the start to provide with valuable business insights

Incentivized

I've not worked hands-on with the implementation team, but there were no escalations barring a few hiccups in the deployment due to change in requirement & adoption to our company's remote servers.

SAP Analytics Cloud and Power BI are both tools that help businesses understand their data, but they have some differences. SAC, made by SAP, works well if your company already uses other SAP products. It's in the cloud, easy to use, and has features for analyzing data, getting insights, and planning for the future. Power BI, made by Microsoft, can be used in the cloud or on your own computers. It fits well with Microsoft tools, is easy to use, and can do advanced data analysis. SAC has built-in planning tools, while Power BI needs extra tools for detailed planning

Incentivized

Python-based platforms like Pandas or Spark are very good too at displaying data and do exploratory analysis. I definitely prefer them to SAS EG. It's just too slow, and doesn't let you peek into the data very easily. Lots of clicking, and I'd rather just write some code, rather do clicking.

Incentivized

Is good for use across multiple locations. It allows users to access data and reports from anywhere, regardless of their location. Can consolidate data from various sources, including different SAP systems and external sources, which facilitates cross-location analysis. SAC enables access to data and models from SAP Datasphere to create new stories. Detailed permissions can be defined for cross-departmental use.

Incentivized

• Optimized our budgeting and forecasting processes. The platform facilitates real-time collaboration among our teams, allowing for more accurate and agile financial planning. This has led to improved precision in budget allocation, ensuring that resources are strategically deployed to support the most promising startups within our portfolio.
• SAC's intuitive dashboards and visualizations provide a consolidated view of key performance indicators, startup health metrics, and portfolio analytics. This heightened data visibility enables our teams to make informed decisions promptly, identify emerging trends, and proactively address challenges.
• Routine tasks, such as performance tracking and reporting, are automated, allowing our teams to focus on more strategic initiatives. This has resulted in time savings and increased productivity across various operational processes.

Incentivized

• Faster decision making, through powerful big data handling functionalities.
• Faster operations on daily basis, once the project tree is built, unskilled personnel can use it in their daily operation.
• Don’t need to choose SAS EG if you are not going to be handling big data. (such as over 1 million rows and 50 columns)
• You need skilled personnel to build the initial project tree.

Incentivized