Dataiku vs. SAP Analytics Cloud

Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.

Incentivized

SAP Analytics Cloud is great for big companies that want advanced data analysis and planning, especially when they need to work together in real-time or when people need to access data on their phones. It's like a super tool for predicting future trends in industries like retail or finance. SAC also works well for companies that use different types of computer systems because it can easily connect them. But, for small businesses that only need basic reports or don't have a lot of technical resources, a simpler tool might be better. If a company doesn't always have a good internet connection or if they're just starting with analytics, there might be other tools that work better.

Incentivized

• The intuitiveness of this tool is very good.
• Click or Code - If you are a coder, you can code. If you are a manager, you can wrangle with data with visuals
• The way you can control things, the set of APIs gives a lot of flexibility to a developer.

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

• End product deployment.

Incentivized

• Complexity in Data Modeling
• SAC supports various data sources, but improvements in the ease of connecting to and integrating with certain data repositories, especially non-SAP databases, would enhance the platform's versatility and integration capabilities.
• An offline mode for SAC could be valuable for users who need to access and analyze data without an internet connection. Additionally, optimizing performance for large datasets and complex visualizations would contribute to a smoother user experience.

Incentivized

There’s no doubt I will renew SAP Analytics Cloud. It is the most vital tool in our organization that makes it seamless to make rapid business decisions by collecting, modeling and visualizing data in real-time.

As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.

Incentivized

Considering the feedback and improvements made over time, users often rate SAP Analytics Cloud's usability in the range of 7 to 9 out of 10. Positive aspects include its integration capabilities, collaborative features, and the ability to create visually appealing dashboards. Some users, however, may note a learning curve or desire additional customization options.

Incentivized

The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.

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

Good videos and reference material available in SAP Portal.

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

Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.

Incentivized

SAP is a product/solution that contains extra capabilities that might be considered an enhancement; SAP Analytics Cloud models are based on a huge data collection, and numerous models can be integrated. When coupled with different SAP systems, Analytics Cloud has a common dataset architecture; this software also includes improved analytics capabilities.

Incentivized

• Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration.
• Platform also ease tracking of data processing workflow, unlike Excel.
• Build-in data visualizations covers many use cases with minimal customization; time saver.

Incentivized

• In general, SAC is a comprehensive analytics platform that offers a range of capabilities for data visualization, reporting, planning, and predictive analytics. It is particularly well-suited for businesses that use SAP systems and are looking to gain insight into their data in a single, integrated platform.

Incentivized