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.
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SAP Datasphere
Score 8.5 out of 10
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SAP Datasphere, the next generation of SAP Data Warehouse Cloud, is a comprehensive data service that enables data professionals to deliver seamless and scalable access to mission-critical business data. It provides a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization. SAP Datasphere enables users to distribute mission-critical business data — with business context and logic preserved — across the data…
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Pricing
SAP Business Data Cloud
SAP Datasphere
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
SAP Business Data Cloud
SAP Datasphere
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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SAP Datasphere is available as a subscription or consumption-based model. The SAP Datasphere capacity unit (CU) offers an adaptable approach to pricing that enables any workload on any hyperscaler. The number of CUs required is determined by the unique workload, with the ability to tailor the combination of required services within SAP Datasphere utilizing a flexible tenant configuration. The services that contribute to CU consumption are the core application (compute and storage), data lake, BW bridge, data integration, and data catalog (crawling and storage).
The reason is pretty straight forward. Majority of our data originates from SAP source systems like SAP S4 private cloud, S4C public cloud and Bydesign. So SAP Business Data Cloud stands tall when compared to other solutions and i honestly believe this is best suited solution …
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 …
Business data cloud is one tool that takes care of extraction, modelling, and AI ML use case in the landscape, whereas in other tools I was using multiple services to take care of each of the functions, hence BDC is a cool tool im action for our use cases. Low low-code option …
BDC is a significant development over Datasphere in the sense that it unifies not only the transaction and olap systems but also other olap systems which may have existed in the landscape. Pce migration and availability of data from and 7.5 or B4 HANA system as a data product …
SAP BW is a long standing datawarehouse platform. We had powerful options to construct a data model in SAP BW. But, SAP will stop supporting latest version BW4Hana by end of 2040. To work in BW4Hana more experience is needed. But, SDS can be easily learnt and user-friendly as …
It is an SAP tool. SAP and non-SAP integration. Reusable data products. The future roadmap is a data sphere with AI enhancements. It provides a cloud-based architecture.
We used SAP BW for modeling and loaded the data into SAP Analytics Cloud for reporting. In this scenario, we had to store data physically in SAC for reporting. Live Model reporting caused a performance issue when displaying data in SAC. After Datasphere came into the picture, …
with the support for SAP BW 7.5 ends by 2027 and extended support by 2030, also the support for BW/4HANA ends by 2040. Every organization is looking towards modernizing their data warehousing solution. SAP Datasphere stands tall as a solution for this and well suited if …
SAP Datasphere is cloud based, also it is designed for Logical data modeling where no much ETL needs to be used, also it has faster onboarding of business use cases, it can integrate with S4HANA CDS views with real time data extraction. Datasphere complements BW4HANA rather …
Snowflake, Databricks, Azure Data Factory... why do we choose? Strong SAP landscape, single source of truth for sensitive data, cloud capabilities, etc.
SAC with SAP Datasphere works like a charm, and it uses the Live connectivity. Negative side:-Clients cannot use SAC for regulatory reports, or they have to download the entire Data for sending it to government agencies.
SAP BW was the old world tool from on on-prem world. It lacks the cloud tool integration. Very limited scalability option. Even with robust modelling options, AIML scenarios were not possible. It was a tool for the past. Now DSP has evolved and taken over the place of BW in all …
Microsoft Asure database is the source for Databricks dataproduct for one of our projects. SAP Datasphere uses this source to develop Graphical view combined with the other data products to get the reports from Analytical Models. Also data is combined from various source in SAP …
SAP Datasphere is an exciting way to modernize our data stack, and what clinched it for us was how deep we're already in with SAP - it only made sense to try and leverage the synergies between Datasphere and our other SAP products.
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.
SAP Datasphere is well suited for scalable cloud based data integration scenarios which also opens up the doors for AI driven insights which are much harder to achieve with on-prem data warehouses. Considering the licensing model of SAP Datasphere being based on consumption driven capacity units cost can be a big consideration for organizations with large volumes of data that can be a pre-requisite for data mining and AI use cases. So this can be a bottleneck or not so well adopted scenario for SAP Datasphere.
SAP Business Data Cloud help in arranging data at one single place reducing cost of maintenance for multiple platforms and governance.
Once data is arranged , it can be modelled as needed using Datasphere and in data bricks for AI needs
Data fabric provided in SAP Business Data Cloud helps in reducing man efforts to design models needed for PNL reporting as data fabric helps in quickly designing the solution with great accuracy.
SAP Data Warehouse Cloud offers free trial for 90 days with free 128 GB of storage and 64 GB memory.
Availability of self-service data modeling and analytics on SAP Data Warehouse Cloud enables users to access and analyze data without getting support from the IT team.
Without zero coding while collecting, connecting, analyzing and modeling data, it saves us time and operational costs of partnering with external IT support experts.
The platform provides strong values in terms of centralized data management, scalability, and integration with the SAP ecosystem. It supports enterprise reporting, governance and analytics effectively. While there is always room for improvement in usability and cost transparency, the long term benefits in performance, data consistency and cross functional collaboration and expanding within the organization
Datasphere can come with its own challenges which can feel like a mountain to get over. However, once one has an understanding of how the product works it becomes easier to use. Once the time is spent to get it setup and working correctly very little is needed to keep it running smoothly. Its a great tool it just takes time to learn.
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 has suggested that BW 7.5 will be sunset soon. Usability is good in SAP BW Modernization. Instead of going with other non-SAP tools, staying with SAP will be suitable for existing users. Across the board, many of them are moving to DataSphere.
support team is generally responsive and knowledgeable, and most issues are addressed within acceptable timelines. Documentation and standard guidance are helpful for common scenarios.
I would greatly acknowledge the services of Sap Data [warehouse Cloud] because we were struggling before its arrival where we used to get manual data connections and this used to consume a lot of time but after its use, we now are able to connect data easily saving a lot of time and finances.
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 reason is pretty straight forward. Majority of our data originates from SAP source systems like SAP S4 private cloud, S4C public cloud and Bydesign. So SAP Business Data Cloud stands tall when compared to other solutions and i honestly believe this is best suited solution for the warehousing and reporting to our organization.
Each of these listed software has its own unique strength and capacity that scales well. SAP Datasphere on its end up against them with more suitability for large establishments with complex data ecosystems with scalability support. Also, it avails a pay-as-you-go pricing for users, and it is widely up for data quality, data governance, and data discovery.