Getting Started with SAP Datasphere

After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

  • Provide an Overview of SAP Datasphere

SAP Datasphere Overview

SAP Datasphere enables a business data fabric architecture that uniquely harmonizes mission-critical data throughout the organization, unleashing business experts to make the most impactful decisions. It combines previously discrete capabilities into a unified service for data integration, cataloging, semantic modeling, data-warehousing, and virtualizing workloads spanning SAP and non-SAP data. SAP Datasphere preserves the full meaning and context of SAP data across systems and clouds, and integrates with other data vendor’s platforms, to deliver seamless and scalable access to one authoritative source of your most valuable enterprise data. SAP Datasphere leverages existing data investments and doesn’t require moving data into yet another data store, it radically simplifies your data landscape ensuring inherent governance throughout the data life-cycle.

From March 8th, 2023, SAP presented the successor product for the SAP DataWarehouse Cloud, SAP Datasphere. Existing implementations in the SAP DWC can continue to be used as usual, investment security is guaranteed. Since the software update is managed by SAP, the customer does not have to take any action. SAP Datasphere is characterized by the stronger, functional integration of SAP Data Intelligence, as well as the new Analytic Model as the central data model type. In addition, the data catalog will be expanded so that a central metadata repository is made available.

In addition, SAP has announced strategic partnerships with leading data and AI companies including Collibra, Confluent, Databricks, and DataRobot. These partnerships expand SAP Datasphere and enable companies to build a unified data architecture that securely brings together SAP software and third-party data.

Collibra is intended to be integrated with SAP through a customized integration. This allows customers to implement a strategy for enterprise-wide data management, building a complete data catalog with information about the data's origin across their entire data landscape, including both SAP data and third-party data. Collibra ensures that every company can find and utilize trustworthy data.

Confluent plans to integrate its data streaming platform with SAP, enabling companies to unlock valuable business data and connect it to external applications in real time. Confluent's cloud offering is the central platform for continuous real-time data streams from various sources within an organization.

Databricks allows its customers to integrate their data lakehouse into SAP software, enabling data exchange while preserving semantics. This helps them simplify their data landscape.

DataRobot enables customers to utilize automated machine learning capabilities for multimodal data on SAP Datasphere and integrate it directly into their data fabric for business data management, regardless of which cloud platform they are on.

SAP Datasphere provides a multi-cloud, multisource business semantic service for enterprise analytics and planning. SAP Datasphere is the latest innovation in the data warehousing portfolio of SAP. It is based on the SAP HANA Cloud and follows a clear DWaaS (Data Warehouse as a Service) approach in the public cloud with very fast release cycles.

The following shows a high level architecture of SAP Datasphere.

Typical SAP Datasphere use cases are extending existing on-premise data warehouses by enhancing existing on-premise data with cloud sources to define new data models for broader insights. Another flavor is providing flexible data marts in control of business users to create new and agile models based on different sources and take the burden from the IT departments. In addition, there are tools available to connect data without duplication across business applications to provide a new and consistent view of the data.

Using SAP Datasphere, you can reduce data movements by accessing data remotely – with data federation - and still get fast response times (SAP HANA Cloud powers SAP Datasphere). In this regard, SAP is a market leader for real-time data federation across clouds.

Extracting data from your business applications is also a significant challenge. For example, if you copy data from your SAP application and store it on a data lake in the cloud, you lose the business meaning of that data. In SAP, critical business objects like customer, product, or order are represented with many tables, each with many attributes labeled with cryptic acronyms. Relationships between objects are also hard to infer. Just understanding what table and attributes you need takes a long time, and so does having to transform and model the data copy for analysis. With SAP Datasphere, you can reduce data movements by accessing data remotely – with data federation - and still get fast response times (SAP HANA Cloud powers SAP Datasphere). As a matter of fact, SAP is the only vendor to offer real-time data federation across clouds.

SAP Datasphere comes with an out-of-the box-understanding of SAP applications data, allowing you to preserve the business context of your data and save a lot of time. This means that you are instantly ready to leverage SAP data and combine it with non-SAP data to provide the comprehensive business view that your company needs.

The overall SAP Datasphere architecture consists of the following components:

  • Space Management: Create spaces tailored to your business needs and monitor them. You model your data within spaces. Spaces are decoupled, yet open for flexible access. Decide on the size, storage type, and importance of your spaces. Add users and connect your sources in the spaces.
  • Data Integration and Data Flow: Access data from SAP and non-SAP on-premise and cloud sources. Connect data virtually or replicate it in real time or scheduled via data flows powered by SAP Data Intelligence. Use APIs or tools to access data. Implement data preparation with transformations and scripting for advanced requirements.
  • Data Builder: Define data models for your data using a technical, model-driven approach in the graphical tools or in the powerful SQL editor of the data layer. As a data engineer, model, combine, and harmonize data in a unified, standardized way. Flexibly update data models
  • Business Builder: Model your business scenarios in the graphical tools of the business layer independently of the data layer. As a BI analyst, model in a demand-driven way using business language to answer common questions independently of IT. Map your models to the data layer.
  • Administration and Security: Manage settings on system level, such as connectivity and data integration settings, security, auditing, and monitoring settings. Manage self-service IP allowlists, database access, and others. Define security on all layers. Manage access on tenant, functional, and space level, and configure secure connectivity to sources. Manage data access by defining row-level security on data and business layer. Enable auditing for read and change operations.
  • Business Catalog: Access, maintain, and manage all objects in your system based on provided tools.
  • Business Content: A large set of SAP delivered and partner managed content is available to accelerate application development.
  • Consumption: Connect your standalone SAP Analytics Cloud solution or consume available models with your SQL tool or BI clients of choice.

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