SAP Datasphere

Analytics-Applications - fast and agile

Roland J. Merz

Managing Director / Vice Chairman

Why use SAP Datasphere?

How do you effectively transform your critical business processes? With SAP Datasphere, you and your colleagues can easily and efficiently access your data. When needed, you can enrich your own data with market data in seconds. Connections become crystal clear, and new ideas emerge effortlessly. This way, you prepare every important decision thoroughly and based on facts—ensuring that well-founded decisions are understood by everyone. You embrace change as an opportunity and lay the foundation for sustainable success. Democratize data access with SAP Datasphere.

SAP Datasphere provides businesses with a reliable and secure way to manage their data. Previously known as SAP Data Warehouse Cloud, SAP rebranded it on March 8, 2023, introducing new features and partnerships. Collaborations with Databricks, Collibra, Confluent, and DataRobot further enhance the SAP Analytics ecosystem.

SAP Datasphere combines various cloud-based services and technologies such as SAP HANA, SAP Cloud Platform, and AI Operations into a powerful data platform. Therefore, we recommend SAP Datasphere to customers in these three key use cases:

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Self-service for business users who need to combine data sources or enrich the existing data model.

Data Lakehouse: The combination of cloud data, such as S3 Bucket (AWS) or Azure Data Lake, with data from the enterprise data model, such as S/4HANA or BW/4HANA.

As well as ad hoc analysis sets for Data Science and Advanced Analytics.

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What is SAP Datasphere capable of?

SAP Datasphere offers a wide range of features for domains and data sharing. Customers can create dedicated workspaces for their team members, where they can collaborate, store files and information, share data, and gain insights from their datasets.

Additionally, the platform provides various data-sharing options, allowing customers to securely exchange large datasets with external third parties or partners. This includes support for distributed file systems like Amazon S3 and Google Drive, as well as direct database connections via ODBC/JDBC.

Furthermore, users have access to various services and tools that enable them to monitor data usage rights, grant or revoke access to specific datasets, and track who has accessed what data over time.

These two innovative concepts set SAP Datasphere apart from other data management solutions. They ensure that users do not accidentally alter other data models but can selectively share their results. The cloud-based approach allows on-demand usage and supports the latest development technologies.

The various SAP Datasphere features are categorized into six core capabilities:

Self-Service Data Access

• Data Discovery

• Orchestration

• Processing and Persistence

• Data Governance

• Data Ingestion

Self-Service Data Access:

With SAP Datasphere, users can take advantage of self-service data access to quickly and easily retrieve trusted business data. This self-service access is designed to allow users to explore their own data without relying on IT teams or other resources.

Additionally, SAP Datasphere offers features such as cloud data management, data integration, and low-code/no-code modeling tools. These capabilities ensure that companies keep their data secure while providing teams with the insights they need for informed decision-making.

Data Discovery:

SAP Datasphere offers a comprehensive suite of business content, a data marketplace, and intelligent search functions.

With the Business Content Library, users gain access to thousands of pre-built datasets and insights collected from around the world. These include real-time market segmentation data, customer reviews and ratings, as well as news articles relevant to their industry.

Additionally, the Data Marketplace helps businesses quickly and easily find the right datasets for their specific needs.

Finally, SAP’s Intelligent Lookup feature allows users to search for information in SAP Datasphere in various ways, including:

• Entity relationships and keyword associations derived from natural language processing (NLP) algorithms

• Advanced search criteria, such as country- or geography-based filters

All these features make SAP Datasphere a powerful platform for discovering valuable business content and uncovering new insights.

Orchestration:

SAP Datasphere provides a comprehensive set of tools for data transformation, SQL and Python programming, and data operations.

For data transformation, businesses can use the Flowgraph Editor to quickly create flows that allow them to link, filter, clean, and transform their data.

Advanced SQL and Python users can work directly within the data flow, leveraging a wide range of functions to manage data over time and ensure its accuracy and relevance.

Key features include:

• Task scheduling for automated processes

• Automated workflows to efficiently manage data changes

These capabilities ensure that organizations can orchestrate their data processes seamlessly and efficiently.

Processing and Persistency:

SAP Datasphere provides a comprehensive toolset for Data Warehousing, Business Semantics, and Knowledge Graphs.

• Data Warehousing: Companies can leverage the platform’s advanced analytics capabilities to store, manage, and analyze large volumes of business-critical data in their cloud environment. This enables faster and more cost-effective insights.

• Business Semantics: The platform offers a suite of services that allow users to link data with rules and logic, driving automated processes and decision-making within the system.

• Knowledge Graph Modeling: Users have access to various tools, including the Knowledge Graph Builder (KGB), which enables them to create graphs and link different entities to uncover hidden relationships within their data.

With these capabilities, SAP Datasphere empowers businesses to efficiently process and persist data, unlocking deeper insights and improving decision-making.

Data Governance:

SAP Datasphere offers a comprehensive suite of tools to help businesses manage metadata, catalogs, lineage, confidentiality, and data quality.

For metadata management, companies can use the Metadata Manager to store and categorize enterprise-related data, improving information organization and making it easier for decision-makers to access and analyze data.

For data cataloging, users can leverage the Data Catalog application to create custom taxonomies and hierarchies for their datasets.

The platform also includes a Lineage Manager, enabling businesses to track data evolution throughout its lifecycleand ensure accuracy across different stages.

To support data privacy and quality management, SAP Datasphere provides services like Privacy Shield and Data Quality Insight, allowing customers to protect sensitive information while maintaining the accuracy and reliability of their datasets.

Data Ingestion:

SAP Datasphere offers a variety of data ingestion options, enabling customers to quickly and easily import data from different sources for further analysis.

The platform supports multiple ingestion methods, including:

• Direct database connections via ODBC/JDBC

• File uploads from CSV, JSON, or text files

• Custom ingestion programs written in SQL or Python

• Real-time data streaming, allowing businesses to ingest large datasets instantly into the system

To ensure security and data protection during the ingestion process, SAP Datasphere provides encryption featuresthat protect sensitive information during transmission.

Overall, SAP Datasphere offers a powerful suite of ingestion capabilities, making it easier for businesses to securely and efficiently load data into the system for advanced analysis and insights. With robust encryption, direct database connectivity, and real-time streaming support, the platform ensures data security while enabling fast and scalable data processing.

How do you use SAP Datasphere

Build Your Own Data Model – Fully in Control of Changes and Costs

Create a custom data model tailored to your needs while maintaining full control over all modifications and costs.

• Intuitive Modeling & Visualization: Designed for business users, requiring no SQL or programming skills.

• Independent Workspaces (“Spaces”): Ensure autonomy by launching prototypes within minutes while protecting your own data model.

• Clear Requirement Definition: Your custom model effectively illustrates business needs, serving as a strong foundation for extending the central data model in SAP BW/4HANA.

• Seamless Handover to IT: Once finalized, your model can be easily transferred to IT for integration into the main data architecture.

Your way into SAP Datasphere

SAP Datasphere – Flexible, On-Demand Cloud Solution

SAP Datasphere provides all the benefits of a cloud solution, ensuring cost-efficiency, flexibility, and ease of use:

• Pay-as-you-go: Only pay for what you use.

• Short-term commitment: No long-term binding contracts.

• Easy onboarding: Get started effortlessly with a 30-day free trial.

Simple & Fast Deployment:

• Order directly via the web with automated provisioning.

• Can be set up by business users without IT support.

• IT assistance is only required for source system integration.

SAP Datasphere functionalties

… at a glance!

Dashboards

• Based on SAP Analytics Cloud • Broad compatibility with SAC Stories • Planned integration of the Application Builder • SAC Tenant included in DWC

Extraction and Modeling

• Replication of data from source systems • Transformation of data using visual or SQL-based tools • Semantic layer for improved data comprehension by business users

Source System Connectivity

• Easy configuration • Connection to SAP systems via Data Provisioning Agent • No firewall changes required, connection established through internal network • Enhanced security with IP whitelisting

Spaces

• Individual spaces for departments or single users • Encapsulation of all developments within separate spaces • Simplified change management through isolated environments • Planned shared objects between spaces • Easy allocation of additional resources per space

… and in detail!

Link to SAP introductory documents

SAP Datasphere: Source System Connectivity

The connection to on-premise systems is established using a Data Provisioning Agent, which is installed within the internal network. This significantly simplifies the connection setup, as it generally eliminates the need for firewall adjustments.

Once the connection is established, all tables from the source system are immediately available for further use. IP whitelisting provides additional security, ensuring that only authorized agents can access the respective Datasphere tenant.

Spaces

In SAP Datasphere, data models are stored in individual spaces. Each space is allocated its own resources, which can be scaled up or down at any time.

Spaces also allow for the isolation of individual applications, whether by departments, reports, user groups, or developers. This encapsulation simplifies development, administration, maintenance, and billing. For example, it would be possible to delegate user management for specific areas to the business unit or easily handle billing based on assigned resources.

Additionally, the development and maintenance of applications are simplified. Errors can be isolated more quickly, and adjustments to applications carry much less risk, as there are significantly fewer dependencies to consider.

Federation

Data Federation is a technique that allows users to combine and analyze data from multiple external sources using SQL queries. With Data Federation, users in Datasphere can quickly and easily query data from external sources (e.g., Amazon S3) using Athena, without the need to manage infrastructure or other storage services.

Federating Queries in SAP Datasphere from Amazon Athena to Gain New Insights

AWS S3 is a powerful cloud storage service that offers secure, durable, and scalable object storage. Athena is a serverless query service that allows users to easily analyze data in Amazon S3 using standard SQL. With AWS Athena, users can quickly run interactive queries on their data stored in S3 without the need to manage infrastructure or databases.

SAP Datasphere Consumption APIs

The Datasphere Consumption API is available to enable SAP Analytics Cloud (SAC) and third-party tools to access Datasphere data.

The first version of the Datasphere OData API was released in 2022.11, with access limited to the use of SAC. The general availability was released in 2022.20.

To integrate, follow these steps:

1. Identify the OData source in Datasphere (Data Service URL).

2. Find the Redirect URI in SAC.

3. Create an OAuth client in Datasphere.

4. Establish an OData connection in SAC.

Next, import data from the OData connection by selecting a dataset and creating a query for it.

Here is our relevant Blog. Or directly to the SAP-Blog.

Share data

Sharing tables and views with other spaces

SAP Datasphere offers the ability to share tables and views with other spaces. This feature allows users to quickly and securely share their data with colleagues in other locations or departments.

When sharing a table or view from one space to another, all available access options are considered.

Additionally, each object shared in a new space receives a newly generated ID, allowing it to be tracked even after being moved. Any changes made to the original object are automatically reflected in all shared versions.

In addition to SAP BW/4HANA, SAP NetWeaver BW 7.5 is also supported as a source for existing analysis authorizations to be imported into SAP Datasphere. See SAP Note 3123815.

Here is the link to the SAP-Blog

Delta calculation in local tables

Track the changes made to your local table after it has been deployed.

Local tables can be used as source or target data by SAP Datasphere applications. For certain business scenarios, you may need to keep track of changes made to your local table after deployment. For example, when importing a new CSV file or executing a replication flow, you might want to know which data has been updated or deleted. See…

Permissions

How do data access permissions work?

Data access controls enable data security at the row level.

Permission criteria are defined in a view, to which user IDs from SAP Datasphere are assigned accordingly.

A data access control can be applied to multiple views.

Special attention should be given to securing sensitive transactional and master data.

The diagram shows a typical environment where a permission entity is maintained by business users in one space and shared with a second space.

Remote permissions from SAP BW/4HANA for SAP Datasphere

Using existing analysis permissions from SAP BW/4HANA in SAP Datasphere through replication and generation of corresponding Data Access Controls.

The process consists of four steps:

1. Defining the scope in BW/4HANA

2. Importing the permission table into Datasphere

3. Creating the Input Permission View

4. Generating the Data Access Control

Remote connections are used to remain in sync with the original objects in SAP BW/4HANA.

This approach reduces development effort related to row-level permissions.

In addition to SAP BW/4HANA, SAP NetWeaver BW 7.5 is also supported as a source for existing analysis permissions to be imported into SAP Datasphere. See SAP-Hinweis 3123815.

Here is the link to the SAP-Blog.

What is the BW Bridge? In which scenario can I use it?

SAP Datasphere BW Bridge is a powerful solution for companies that want to migrate from SAP Business Warehouse (BW) to the cloud.

The BW Bridge provides a familiar BW environment to manage BW data models.

It offers an easy way to quickly and efficiently transfer data, objects, and hierarchies between systems.

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