SAP Business Data Cloud

Score8.5 out of 10

74 Reviews and Ratings

What is SAP Business Data Cloud?

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.

Categories & Use Cases

#1 most frequent

Manufacturing

29.4%

52 installations of 177

“Our organisation uses SAP Business Data Cloud as a modern data warehousing and analytics platform.”
— Domain Analytics Lead, Bosch Home comfort (10,001+ employees)

#2 most frequent

Professional, Scientific, and Technical Services

14.1%

25 installations of 177

“State-of-the-art and faster Data extraction, mapping, and transformation both from SAP and non-SAP data sources.”
— SAP BTP Technical Architect, Ernst and Young (10,001+ employees)

#3 most frequent

Retail Trade

9.0%

16 installations of 177

Harper Miller

Data Analyst in Information Technology at Agile Infoways (201-500 employees employees)

Use Cases and Deployment Scope

SAP Business Data Cloud makes it easy to monitor and manage data from different sources. It helps me locate insights across various attributes, such as product and customer. The SAP data is in one place, enabling quick user analytics and effective planning. I have been able to contextualize data from SAP and non-SAP sources.

Pros

Pooling SAP data under one place.
Provision of unified data analytics.

Cons

Dependency on SAP ecosystem slows down adoption.
Complexity and learning curve are quite challenging.

Return on Investment

Strong data governance and security features have enhanced positive ROI.
It has reduced data discrepancies and improved analytics.

Usability

Other Software Used

ClickUp, IBM Aspera on Cloud, Adobe Marketo Engage

Deva Anand

Principal in Manufacturing at Arthrex (501-1000 employees employees)

Use Cases and Deployment Scope

for SAP table replication and data modelling

Pros

Real time data replication
o delta share
Data modelling

Cons

Performance optimization

Return on Investment

Positive

Usability

Suman Kandasamy View profile

Senior Consultant in Information Technology at Bosch global software technologies (5001-10,000 employees employees)

Use Cases and Deployment Scope

Mainly we use Datasphere which is integrated with SAC and also to align SAP and non-SAP data products. Since I'm from analytics teams most use case I see is for real time analytics and to process large data. Recently started using Datasphere which is planned for replacing wonderful SAP BW system. Looking for leveraging AI in S/4 system. Also to provide the customer a refreshed experience who are still using AFO reports. Data quality management is also a factor to consider. It helped to bridge the gap between on premise SAP data with cloud applications

Pros

Helped in solving complex data integration
Creating Sales order from unstructured data, AI usage
Ability to predict in supply chain management
Data Governance

Cons

Pricing model is looking complex not able to justify with products like Azure
Integration with non-SAP system can be made more simpler if possible
Joule is good but still this can be made strong to handle complex analytical queries
Modeling Planning in SAC can be made user friendly

Return on Investment

Operational efficiency is increase for sure
Risk mitigation is improved
High implementation cost while setting up
No Standard SAP connectors to integrate legacy non-SAP manufacturing systems

Usability

Alternatives Considered

SAP Business Warehouse, SAP Datasphere and SAP Analytics Cloud

Other Software Used

SAP Business Warehouse, Azure Data Lake Storage, Microsoft Power BI, SAP Datasphere

Verified User

Consultant in Information Technology (10,001+ employees employees)

Use Cases and Deployment Scope

Our organisation uses SAP Business Data Cloud as a modern data warehousing and analytics platform. We were using the BW 7.5 on Oracle database. As SAP decommissioned the BWA feature in BW 7.5, we were facing performance issues. Moving to BW on Hana or BW4Hana looks short term solutions at that point. To overcome that, we were looking for the next options. Here, SAP Business Data Cloud suits better for our needs. The SAP tool for the SAP data would be a better and more reliable solution. SAP Business Data Cloud helps to transform the raw data to a semantically rich dataproduct. We are using replication flows for some premium outbound use cases as well. With this SAP Business Data Cloud suite, we were doing seamless planning for project cost. This reduces a lot of the data transfer process. Using the analytical model, we built multiple statistical dashboards. In addition to that we could able to achieve the realtime data replications which increases the accuracy and reduce the lag.

Pros

We have created the semantically rich dataproducts which are residing in the object store. We use the same dataproduct for the dashboarding and for the external non-SAP demand planning tool (maestro). This ensures data uniformity and a single source of truth.
We implemented the Capex planning model in SAP Business Data Cloud's SAC tool. Here, we could fetch the realtime data from the S4 source system and write back the planning data to the same source system via the SAP Datasphere using the seamless planning option.
An AI core model has been deployed in SAP Business Data Cloud for the service cloud V2 data. This trained model will identify the potential customers from the opportunities and automatically propose the quotation with higher accuracy.

Cons

There are no layer concepts or guidelines for the structured implementation. This leads to a lot of doubt where to use which object model and struggled to create an optimised dataflow.
There are no options in the application area to reuse the logics. If we want to manipulate the same logic between multiple source and target object means, we need to create multiple transformation flows. Future maintenance will be taken care of in multiple places to be in sync.
SAP is suggesting to keep the dataproducts in the object store space. To refine the dataproduct, we don't have extensive operation skills inside the object store. To add complex logics, we may need to flow the data to HANA space, perform those operations, and bring it back to the object store.

Return on Investment

It provides nearly realtime data. This ensures fast and accurate decisions by the user department. The planning models are accurate now. We could able to automate some planning functions as well. This reduces the manual efforts.
Single source of truth ensures the data uniformity. Due to this, the Demand planning team and the Sales and Operations department are looking at the data with zero deviations. This ensures the smooth operations in our manufacturing plants.
IT cost estimations are reduced after the required dataproducts are generated. Self service from the user department is increased. They should able to make the changes with the same time window of Business Requirement document creations. Catalogue features also an added advantage which significantly reduces the dependencies.

Usability

Other Software Used

SAP BW/4HANA, Azure Databricks, Maestro, IBM Planning Analytics

Verified User

Consultant in Information Technology (10,001+ employees employees)

Use Cases and Deployment Scope

Our current data warehousing solution is SAP BW4HANA 2023 version. Our SAC tenants and datasphere tenants are migrated to SAP Business Data Cloud environment already. SAC being the primary reporting tool and we are positioning datasphere replication flow is the strategic direction for the data transfer from S4,S4C environments to non SAP analytics world. Our main business problem is the delayed availability of data for reporting with our current warehousing solution and lack of support for AI/ML use cases with the current set up. We are confident that by modernizing our analytics world from BW4HANA to SAP Business Data Cloud via data product generator and by gradually moving towards custom data products, current business problem can be addressed efficiently ( real-time reporting). With data architectures are evolving from data warehouse to data Lakehouse and increasing demand for data for analytics, we see that SAP Business Data Cloud can fulfill this by combining the power of object store with Apache engine

Pros

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

Cons

Limited support for direct connection with legacy ERP systems and data has to be transferred via BW systems
Limited support for calculated columns inside datasphere with filter on hierarchy nodes
Limited support for data transfer from SAP Business Data Cloud/Datasphere environment back to on premise systems like BW4HANA ( for special use cases )
The service is pretty new and there are scope for fixing the bugs in different areas.
This may not be directly related but definitely can be improved. The costing model is not completely transparent and support team not able to explain the API call details from object store. Customer needs to know on what they are paying for.
So far i haven't seen any official release for the connection with AI platforms like Claude and MCP server from the analytical world for the innovations. i see innovations from consulting companies in this direction. i would love to see official support from SAP on these directions as well in the future.

Return on Investment

With the support for AI/ML use cases via SAP Data bricks and via zero copy delta share to enterprise data bricks, it has really made a bigger impact since this was our bigger pain point with the legacy warehouse solution
With the working capital intelligent app, it was the biggest game changer and it really made big impact on the customer to understand the SAP Business Data Cloud and its capabilities
with public cloud Saas , it has reduced the maintenance effort from IT to the greater extend. With traditional BW, IT has to take the overhead of database upgrade , patch upgrade, service pack upgrade etc. This is one of the key capabilities that provides high ROI in my opinion
with the support for the zero-copy delta share to other products like snowflake and google analytics, i think we are moving towards the good direction and i think the best-selling point to the customer
With the replication flow capabilities of datasphere which is also part of SAP Business Data Cloud, it resolves another main business problem of data transfer from S4 to Microsoft fabric.

SAP Business Data Cloud

What is SAP Business Data Cloud?

Categories & Use Cases

Most Frequent Users

Manufacturing

Professional, Scientific, and Technical Services

Retail Trade