IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.
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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.
It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
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
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
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.
I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path
support team is generally responsive and knowledgeable, and most issues are addressed within acceptable timelines. Documentation and standard guidance are helpful for common scenarios.
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
The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.
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.
