In March 2024, SAP announced the latest capabilities in SAP Datasphere, focusing on streamlining the business data fabric, which seamlessly connects various SAP and third-party data sources. These advancements are set to transform how enterprises manage and report data, providing a unified platform for real-time data integration and analysis. For example, Hershey’s is using SAP Datasphere in combination with SAP S/4HANA to build a modern data analytics platform that enables business self-service and trusted data models for decision-making.
These new features include the integration of SAP Analytics Cloud with SAP Datasphere for seamless planning and analytics. Business users can now take advantage of advanced capabilities like Monte Carlo simulation for risk analysis and planning adjustments, all powered through a simple chat interface. This kind of integration enhances operational and financial planning by providing a unified model for data preparation, analytics, and planning.
Moreover, SAP has collaborated with leading partners like Collibra and Confluent to expand its data and AI governance capabilities. Collibra AI Governance ensures trusted and compliant use of data within AI models, while the Confluent integration allows for real-time data streaming to and from SAP Datasphere, making the data management ecosystem more robust and user-friendly. These partnerships emphasize SAP's commitment to creating a comprehensive, open data ecosystem that can effectively meet the diverse needs of enterprises.
With all these updates, SAP Datasphere stands out by providing an advanced and integrated data foundation, allowing enterprises to set up cross-system reporting efficiently without sacrificing context, security, or performance. Let’s now dive deeper into the steps you can take to set up cross-system reporting with SAP Datasphere and leverage its latest innovations for your organization.
What is SAP Datasphere?
SAP Datasphere is a cloud-based data integration and management platform that evolved from SAP Data Warehouse Cloud. It helps businesses connect, integrate, and model data from various systems, both SAP and non-SAP. This allows organizations to create a central repository of data that can be used for reporting, analysis, and decision-making.
With SAP Datasphere, you can unify your data landscape, breaking down silos and ensuring that data is accessible in real-time. It supports data federation and replication, allowing you to choose the best method to access your data without unnecessary duplication. Additionally, SAP Datasphere integrates seamlessly with tools like SAP Analytics Cloud, enabling you to visualize and analyze data effectively.
This powerful platform makes cross-system reporting, data governance, and business analytics much easier, offering advanced capabilities that keep your enterprise ready for the future.
How to Set Up Cross-System Reporting in SAP Datasphere: Step-by-Step Guide
In this section, we’re going to set up cross-system reporting using SAP Datasphere—step by step. Follow along, and by the end, you'll have a unified reporting solution that brings together data from all your systems.
Step 1: Connect Your Data Sources
The first thing you need to do is connect your data sources. Whether it's SAP or non-SAP systems, cloud, or on-premises, SAP Datasphere has pre-built connectors for a smooth integration.
Open SAP Datasphere and navigate to the "Connections" section. Here, you will see a list of connectors available. This includes SAP S/4HANA, SAP BW, cloud databases like AWS, and even third-party systems such as Google BigQuery.
Select and Configure a Connector:
Click on the relevant connector, such as SAP S/4HANA.
Provide the credentials required (server name, user ID, etc.). SAP Datasphere’s connector guides you step-by-step, and you can follow the SAP Datasphere Connection Guide to get detailed instructions.
3. Test and Save the Connection. Once configured, test the connection to ensure everything is working smoothly. If successful, save it, and move on to connecting your next data source.
Step 2: Model Your Data
Data Builder Modeling Overview: SAP Datasphere
Once you’ve established your data connections, the next step is to model your data. Data modeling helps in creating a unified and user-friendly structure for your reporting.
Navigate to the Data Builder Tool:
The Data Builder is where you set up data models. It has a simple drag-and-drop interface, which makes it easy to use even for beginners.
Here, you can add data from different sources and link them together. For instance, you can integrate customer data from SAP S/4HANA with CRM sales data.
2. Create Relationships:
Establish relationships between the tables you imported. Drag and drop to create links between datasets.
Tip: SAP recently introduced Semantic Onboarding, which automatically maintains hierarchies and units while creating these relationships—saving you time and ensuring consistency.
Step 3: Harmonize and Transform Data
With data coming from different systems, you need to make sure it is consistent for analysis. Harmonizing and transforming the data is key here.
Use the Data Builder for Transformation:
Within the Data Builder, choose Transformation Flows to clean and standardize your data.
For instance, you may have customer names stored in different formats across systems. Use transformation rules to standardize these fields.
2. Remove Duplicates and Set Rules:
Set up filters to remove duplicate entries or use built-in algorithms to merge datasets effectively. This ensures all teams have a single version of truth when working with the data.
Step 4: Set Up Dashboards Using SAP Analytics Cloud (SAC)
Once your data is unified, it’s time to visualize it. SAP Analytics Cloud (SAC) works seamlessly with SAP Datasphere to provide real-time analytics and dashboards.
Integrate with SAC:
Head to the “Connections” section in SAC and add SAP Datasphere as a data source.
Select the datasets or models you’ve created. This integration allows SAC to pull real-time data from Datasphere without requiring manual imports.
2. Create Dashboards:
In SAC, use Charts and Widgets to create dashboards that make your data easy to understand.
For example, you could set up a dashboard that shows sales data across regions and includes predictive insights for future trends. With the integration of Joule AI Copilot, you can also ask natural language questions and get insights instantly—like, "Which region performed best last quarter?"
Step 5: Secure and Manage Data Access
Data security is critical, especially when dealing with cross-system data. SAP Datasphere makes it easy to control who can see and interact with which data.
Create Spaces in SAP Datasphere:
Use “Spaces” to create isolated environments within SAP Datasphere. For example, create separate spaces for your finance, sales, and HR teams. Each space can have its unique access permissions.
This is also helpful when integrating sensitive data like payroll details. You can create a secure space where only HR has access, while still allowing aggregated financial data to be available to other teams.
2. Manage Permissions:
Assign specific roles to different users—e.g., some users may have "read-only" access, while others have full editing rights. Refer to the Permissions Guide to ensure you set these correctly.
Step 6: Automate Data Pipelines
Automation can save you a lot of time and effort when it comes to managing data.
Set Up Automated Data Pipelines:
SAP Datasphere now supports automated replication tasks. This means you can set up data pipelines once, and they’ll handle both the initial load and any future updates automatically.
Whether you are pulling in data from SAP ECC or SAP BW, these pipelines can replicate large amounts of data without manual intervention. This feature is a game-changer if you need to keep your reporting real-time and up-to-date. I recommend reading more about this in the SAP Datasphere Guide here.
Step 7: Validate and Monitor Your Setup
Once everything is set up, make sure it works properly and keeps performing well.
Use the Data Integration Monitor:
SAP Datasphere has a Data Integration Monitor that lets you see the health of your data flows. You’ll know if a connection is broken or if there’s a data delay, and you can quickly take action.
2. Testing
Run some tests on the dashboards to ensure all the data is coming through correctly. Check for any discrepancies or mismatches. It’s always better to catch any issues early rather than finding out after generating a critical report.
How to Customize Your SAP Datasphere Space for Cross-System Reporting
Now that we’ve set up cross-system reporting, let's talk about making your SAP Datasphere environment work specifically for your team’s needs. Every organization has unique requirements, and customizing your SAP Datasphere spaces helps you maximize the efficiency and usability of your reporting setup. Below, we’ll explore how to tailor SAP Datasphere for specific teams, like finance or supply chain, and how to enhance the usability of reports through semantic customizations.
Configuring SAP Datasphere Spaces for Specialized Needs
Spaces in SAP Datasphere are like individual work zones where different teams can store and work with the data they need without worrying about cross-team data conflicts. Here’s how to customize spaces for your specialized needs:
Create Separate Spaces for Different Departments:
Start by creating dedicated spaces for each department—like finance, HR, supply chain, etc. This ensures that each team has secure access to only the data they need while keeping sensitive information compartmentalized.
For instance, if you need to integrate payroll data from HR into financial planning reports, you can set up restricted shared spaces that allow limited access between finance and HR, making sure sensitive information stays secure.
2. Assign Roles and Permissions:
For each space, set roles and permissions. Assign roles like Data Consumer (users who can view and use data) and Data Engineer (users who can build and maintain data models).
A useful resource to learn more about how to effectively manage spaces is the SAP Datasphere Roles and Permissions Guide.
3. Monitor Performance and Resource Allocation:
Each space has its own allocation of memory and compute resources. You can monitor these metrics to ensure optimal performance and adjust resources as needed during high-load periods—such as end-of-year financial reporting.
Walkthrough on Customizing the Semantic Layer for Enhanced Usability
A well-designed semantic layer helps business users make sense of data. It allows them to use the terms and metrics they’re familiar with, instead of having to understand raw technical data. Let’s make your semantic layer work for your reporting needs:
Use the Business Builder to Add Semantics:
Business Terms: Instead of using technical names like cust_id, use readable terms like “Customer ID.” You can define these terms in Business Builder, making reports more intuitive for non-technical users.
Hierarchies and Calculations: Set up hierarchies such as Product Categories or Organizational Units and add calculated fields like Total Sales or Profit Margin directly in the semantic layer. This way, business users can perform high-level analyses without complex calculations.
2. Semantic Onboarding of Data:
SAP recently introduced Semantic Onboarding, which brings over not only the data but also its semantics from SAP systems, such as units, hierarchies, and business rules. This means your users will get data that retains its original business context, improving accuracy and reducing the learning curve for reports.
3. Create Business Models for Reporting:
Using Business Builder, you can create models that group related metrics together into logical units—like a “Sales Dashboard” model that combines sales, inventory, and return metrics. This way, you’re setting up reports that are ready for consumption, without users needing to dig into raw data tables.
You can also leverage templates from the SAP Datasphere Marketplace, which offers pre-built business models and content packages to speed up the customization process. These templates can be adapted to meet the specific needs of your team, saving time and effort during the setup.
Wrapping Up!
You're now ready to take full advantage of SAP Datasphere for cross-system reporting. By following these steps, you can bring all your data together, create insightful reports, and ensure your entire organization is working with the same information. The goal is to transform scattered data into unified, actionable insights—without the complexity.
I encourage you to get started today. Dive into SAP Datasphere, connect your data sources, and see the difference for yourself.
References:
Getting Started with SAP Datasphere
SAP Datasphere - Space, Data Integration, and Data Modeling Best Practices
About the Author
Ndz Anthony is a certified SAP analytics consultant with an extensive portfolio in SAP BI consulting and tutoring. He enjoys sharing his knowledge through pieces of writing relating to BI and enterprise analytics.