The Dataiku platform unifies data work from analytics to Generative AI. It supports enterprise analytics with visual, cloud-based tooling for data preparation, visualization, and workflow automation.
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SAP Business Data Cloud
Score 8.6 out of 10
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SAP Business Data Cloud is a fully managed SaaS solution that unifies and governs all SAP data and seamlessly connects with third-party data—giving line-of-business leaders context to make even more impactful decisions.
Dataiku is an awesome tool for data scientists. It really makes our lives easier. It is also really good for non technical users to see and follow along with the process. I do think that people can fall into the trap of using it without any knowledge at all because so much is automated, but I dont think that is the fault of Dataiku.
SAP Business Data Cloud is suited mainly for SAP data integration. We could able to easily consolidate the data from S4 and service cloud V2 system. SAP Business Data Cloud enables realtime data replications. We could able to leverage the AI core features. As my previous data warehousing skill is from SAP BW, I am missing some basic features comparing to BW. Master data manual maintenance, Time dependant masterdata, language independent text is also not straightforward.
Support for AI/ML use cases with SAP Data bricks and without the need to physically transfer the data from datasphere environment.
Provide near realtime data for analytics from S4C public cloud via data products which was the primary business problem that our customers were concerned with
Provides support to use the best of both the worlds like SAP and Databricks
New releases that support for the zero-copy delta share via SAP Business Data Cloud connect to other products like snowflake, google big query and other products in roadmap
Moving towards the lakehouse architecture or similar architecture from the former warehouse architecture to meet the increasing demand for the data
The integrated windows of frontend and backend in web applications make it cumbersome for the developer.
When dealing with multiple data flows, it becomes really confusing, though they have introduced a feature (Zones) to cater to this issue.
Bundling, exporting, and importing projects sometimes create issues related to code environment. If the code environment is not available, at least the schema of the flow we should be able to import should be.
In the new analytics world, BDC has been a game changer for SAP Analytics. Extending the SAP data for the usage in Databricks, snow flake, GCP has opened new doors for Analytics . Shift from traditional data warehousing to Business Data fabric adapting to the change in the analytics world is the need of the hour and Sap has managed to pulled it off with BDC
The user experience is very good. Everything feels intuitive and "flows" (sorry excuse the pun) so nicely, and the customization level is also appropriate to the tool. Even as a newer data scientist, it felt easy to use and the explanations/tutorials were very good. The documentation is also at a good level
SAP Business Data Cloud offers robust capabilities that enable me to analyze data and extract valuable business insights. It creates a single source of truth with seamless SAP integrations that enable faster, more reliable reporting. It has freed my team from complex engineering efforts by simplifying data analytics, giving us more time to focus on generating insights.
SAP Business Data Cloud has been highly available and reliable for our day-to-day activities. We have experienced very few disruptions, and the platform generally performs consistently. The reason for not awarding a perfect score is that occasional maintenance activities or cloud service issues can occur, as is common with any enterprise SaaS platform. Overall, availability has met our business needs very well.
SAP Business Data Cloud provides solid overall performance, with pages and standard reports generally loading within an acceptable timeframe. The platform handles enterprise-scale data and analytics workloads effectively. While very large datasets, complex reports, or extensive integrations can occasionally impact response times, overall performance has been reliable and suitable for business operations.
The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.
support team is generally responsive and knowledgeable, and most issues are addressed within acceptable timelines. Documentation and standard guidance are helpful for common scenarios.
It will be more effective. Higher Engagement and Focus. we can ask questions and get the clarity on the spot. Better Knowledge Retention. Stronger Collaboration and Networking. Overall it will be a rich Communication. Sensitive or complex topics are often easier to discuss in person. Informal discussions during breaks often lead to valuable knowledge sharing.
One of the best training session I attended and they covered most of the topics and answered all our questions. participants joined from different regions, infact they all had a different questions and it was different thoughts from all of then and helped to learn better. Though I was on travel, I could able yo attend the session.
I have done implementation of models in traditional bw and Using BDC. The integration of BDC with S4 hana for creating sap data products is seamless and reduces lot of implementation effort. The intelligent app feature is BDC also eases the implementation effort. If i have to compare the previous world with new BDC, implementation effort is largely saved
Anaconda is mainly used by professional data scientists who have profound knowledge of Python coding, mainly used for building some new algorithm block or some optimization, then the module will be integrated into the Dataiku pipeline/workflow. While Dataiku can be used by even other kinds of users.
With a S4 backend a lot of core functionality is made simpler - authorization, data types, currency conversion. In particular if the front end choice is SAP Analytics Cloud. The lack of a good connection from Power BI to the datasphere application (instead of the underlying HANA cloud) is a major drawback in that scenario.
I would rate the contract terms and pricing structure of SAP Business Data Cloud as 7 out of 10. The pricing model is generally aligned with enterprise-scale deployments and provides flexibility for organizations looking to consolidate data, analytics, and governance capabilities on a single platform. The contract terms are comprehensive, and SAP offers multiple licensing options to support different business requirements and growth scenarios.The primary reason for this rating is that the pricing and licensing structure can be complex to understand, particularly when estimating long-term costs as data volumes, users, and workloads increase. Greater transparency around consumption-based charges, usage forecasting, and future scaling costs would make planning easier. I would also prefer simpler licensing bundles and more predictable pricing tiers. Overall, the model supports enterprise needs well, but additional simplicity and clarity would improve the customer experience and make budgeting more straightforward.
SAP Business Data Cloud provides strong scalability for enterprise data management and analytics, supporting growth in data volumes, users, and business use cases. The platform's extensibility and integration capabilities make it adaptable across departments and sites. The reason I did not rate it higher is that large-scale deployments may require additional effort around governance, integration, and advanced customization to fully realize enterprise-wide adoption
The professional services team demonstrated strong technical expertise and a solid understanding of data integration, analytics, governance, and cloud architecture. They provided valuable guidance during planning, implementation, and configuration phases, helping accelerate deployment and reduce potential risks. Their recommendations aligned well with best practices and supported a smooth transition to the platform.The reason I did not assign a higher rating is that some specialized requirements required additional consultation cycles and coordination between different teams, which occasionally extended timelines. In certain cases, deeper industry-specific examples or more tailored implementation guidance would have been beneficial. Despite these challenges, the team remained responsive, collaborative, and focused on achieving business outcomes. Overall, the professional services engagement added significant value and helped maximize the benefits of the SAP Business Data Cloud investment.
