SAP Datasphere

Formerly SAP Data Warehouse Cloud

SAP DataSphere provides significant contributions to companies in the field of data management and analytics. With the advantages it offers in data integration, quality, security and accessibility, it allows business processes to become more efficient and strategic decisions to be taken based on information. As a result, SAP DataSphere stands out as a strong supporter in companies' digital transformation journey.

SAP Datasphere is the hub for all of our data. We are connected to various source systems and store the data into datasphere. We have a very decentralized business, so the goal of implementing datasphere was to centralize to a single source of truth.

We are trying to leverage SAP Datasphere for our ETL process, we did not have any dedicated ETL tool in our organization till now. We use Qlik currently, we are trying to be SAP centric and leverage Datasphere capabilities and seamlessly connect with SAP Analytics cloud. With Datasphere we can reuse the Analytics models in multiple SAC stories, which was not possible in Qlik. (we use/used Qlik for extraction and visualization)

We use Datasphere as our Enterprise Warehouse. The native connections to S4HANA, ECC, and SuccessFactors helped us rapidly get there. Our scope is to build a Data Fabric with all our sources to consume, mainly from SAC. We have seen continuous improvement in the product since we started two years ago.

To replace BW

SAP Datasphere simplifies the traditional bw activities

Now we are using this tool for our sales department. We have the reporting tool Tableu. And we cannot integrate Tableau and our SAP ECC. Because of that, we implemented SAP Datasphere solution to integrate all data.

We sell it to customers and implement it.

We implement SAP Datasphere (DSP) at our clients to be used as the datawarehouse of choice. On top we use SAP Analytics Cloud to build front end reporting. In DSP both SAP and non SAP (Excel /...) sources are combined, transformed, used to create calculations and business logic uppon. DSP is in that case the sole source of truth for our reporitng.

Productive usage to distribute all relevant SAP BI Data to our customer. For e.g. Qlik Sense and Google BigQuery.
Actual problem, is the integeration in nonSAP tools. The consumtption for openSQL Connection is not that smart as for SAP Analytics Cloud. We want an bi-directional functionality for all interfaces. Neither its an SAP Product or not.

we use Datasphere to produce sales reporting among multiple instances of SAP to have one source of truth

Having troubles with data repository
Single version of truth
Data trace problems
Complex environment

We used SAP Datasphere to integrate data from various sources as we had on-premises data servers, cloud applications and IoT devices. This tool allowed us to present the data to non-technical people blatantly and improve the business processes, make better decisions and identify the lacking features in our current application. Overall, SAP Datasphere is a versatile and powerful tool that can help organizations to get more value from their data.

SAP data sphere played an import role in data unification in cases where data from multiple sources is to be ingested into single platform for processing. Theoretically it can support data ingestion from both SAP and non-SAP data sources. It can even access data from foreign sources. SAP has good team of professionals to help you with onboarding and support requirements.

We use SAP as the inventory, and pricing database for all products globally at out company. I personally use it for web pricing and inventory, however the retail team can also separate things by retail, and warehouse. So we can have separate pricing for retail stores and web store.

Over the years, SAP software has been used by our team to address data routine. Specifically, we use SAP Datasphere to integrate data from diverse sources both on-premise and in the cloud. The software assists with cataloging structured and unstructured data assets, which is profoundly useful in saving time as the team is easily all caught-up on their available data.

SAP helps me integrate, visualize and process data effectively and efficiently. Data retrieval and analysis using SAP is much easier and more robust comparatively. Also, it is easy to connect and join data at elsewhere and integrate them and/or remove the redundancies more smoothly. The cloud linkage and workflow are the best suite.

Previously, we were using Google Analytics on all our sites to visualize user analytics, behaviors, etc. But recently, we made the switch to SAP Datasphere, which is also a SaaS. As our organization was already using SAP BTP, we were able to make the switch to SAP Datasphere conveniently, which helped us in Data Discovery and distribution. This was particularly needed in our organization as we have a vast number of data-oriented platforms and have a huge number of clients using those. Hence, we started using SAP Datasphere for tracking, managing, and modeling those data across all our platforms.

We now have all of our data catalogued and unified with SAP Datasphere. We are using it to create new visuals for our data reports and delviering bettern analysis in general. Some of our researchers can be really granular but the ecosystem adjusts to it well.

It is a new Data management tool from SAP with tight integration with SAP BTP. The positioning is little confusing since not sure whether it replaces SAP BW, or any other CDP platform. It is a combination of individual components like SAP analytics cloud and help in all processes of data in the organization

I use SAP Datasphere on a daily basis at workplace. I am able to relish a lit of issues with the help of this program. It is seamless, rapid and accurate to model, prepare and visualize data across varied sources.

With SAP Datasphere, I am able to reduce manual data modeling, integration and visualization procedures through automation.

We recommend our clients use SAP Datasphere to bring their data from their ABAP system and make it ready for consumption in various BI applications.

Implementing the views to support SAC for Business purpose.

Effectiveness with getting insights for data collected from different sources. Elegant and robustness with data visualization for apps on the cloud. Tantalizing with ETL data virtualization.