SAP BW/4HANA and Big Data

SAP BW/4HANA and Big Data — Integration and processing of big data in a BW/4HANA system

The importance of big data in today’s business world cannot be undere­sti­mated. Companies in all indus­tries are faced with the challenge of collecting, storing and analyzing large amounts of data in order to remain compe­titive. This data comes from a wide variety of sources and includes both struc­tured and unstruc­tured data. The ability to gain meaningful insights from this data is crucial for data-driven decisions, process optimization and the development of new business models.

SAP BW/4HANA plays a key role in the big data strategy of many companies. As an advanced data warehouse solution based on the powerful in-memory technology SAP HANA, SAP BW/4HANA offers the speed and flexi­bility needed to process large amounts of data effici­ently. It enables fast and flexible data modeling, improved data management capabi­lities, and powerful analysis tools.

Companies benefit from SAP BW/4HANA through accele­rated data analysis, improved reporting capabi­lities, and the ability to respond to data changes in real time. These features are essential to meet the growing demands for data processing and analysis in the era of big data.

SAP BW/4HANA in the context of big data

SAP BW/4HANA plays a crucial role in big data scenarios by enabling companies to effici­ently manage and exploit complex data landscapes. As an advanced data warehouse solution based on the powerful in-memory platform SAP HANA, SAP BW/4HANA offers the agility and perfor­mance needed to integrate, process, and analyze large amounts of data from various sources. This is especially important in today’s data-driven world, where fast and informed decisions represent a decisive compe­titive advantage.

The relati­onship between SAP BW/4HANA and other SAP solutions such as SAP Data Hub is also of great importance. SAP Data Hub offers a compre­hensive solution for data integration and management across complex systems and environ­ments. In combi­nation with SAP BW/4HANA, companies can develop a compre­hensive and integrated data management strategy. This combi­nation makes it possible to collect data from a wide variety of sources, process it and make it usable in real time to enable deeper insights and analysis.

Integration of external data sources

The integration of external data sources in SAP BW/4HANA is an essential part for companies to gain a compre­hensive view of their data. SAP BW/4HANA supports various methods to integrate and analyze data from external sources.

Tradi­tional DataSources provide a standar­dized method to extract data from SAP and non-SAP systems. They enable data to be collected from a variety of sources and integrated into SAP BW/4HANA.

Opera­tional Data Provi­sioning (ODP) is another important method for data integration. ODP supports various scenarios, including extra­ction from SAP Business Suite systems, SAP BW, and other sources. It provides a powerful platform to extract data in real-time or in batch mode and make it available for analysis.

For more complex integration scenarios, SAP offers tools such as SAP Data Services and SAP Data Intel­li­gence. SAP Data Services is an ETL tool that enables compre­hensive data integration and quality. It is parti­cu­larly useful for extra­cting, trans­forming, and loading (ETL) data from various sources.

SAP Data Intel­li­gence extends these capabi­lities by integrating advanced data processing and machine learning. It provides a unified solution for integrating, processing, and managing data from a variety of sources, including cloud appli­ca­tions, IoT devices, and big data systems.

SAP Data Hub and its role

The SAP Data Hub plays a crucial role in the context of big data warehousing by providing a central platform for integrating and managing a wide variety of data types and sources. It enables companies to effici­ently orchestrate complex data landscapes and gain a compre­hensive overview of their data.

One of the core functions of the SAP Data Hub is the ability to integrate data from a variety of sources. This includes not only tradi­tional data sources such as corporate databases and SAP systems, but also more uncon­ven­tional data such as sensor and video data, as well as unstruc­tured data from social media or the Internet of Things. This versa­tility enables companies to gain a compre­hensive picture of their business opera­tions and make data-driven decisions.

SAP Data Hub not only supports the integration of this data, but also provides tools for data processing and analysis. It enables the perfor­mance of complex data processing tasks, such as data streaming, data quality checking, data prepa­ration, and data cleansing. In addition, it offers advanced analytics capabi­lities that make it possible to gain valuable insights from these large and diverse data sets.

The integration of SAP Data Hub into the SAP BW/4HANA data warehousing system extends the capabi­lities of SAP BW/4HANA to include important aspects of data integration and processing. This combi­nation enables companies to use their data more effici­ently and make their data strategy more flexible.

Processing and analyzing big data

SAP BW/4HANA plays a crucial role in processing and analyzing big data, especially in scenarios that involve large amounts of data, such as those found in social media and the Internet of Things (IoT). This advanced data warehouse solution from SAP is speci­fi­cally designed to effici­ently process and analyze large and complex data sets, which is essential for companies in today’s data-driven world.

Data generated in social media is often unstruc­tured and voluminous. SAP BW/4HANA can collect, store and process this data to gain valuable insights. For example, by analyzing social media data, companies can better under­stand customer opinions and market trends and adjust their marketing strategies accor­dingly.

In the area of ​​the Internet of Things (IoT), SAP BW/4HANA enables the processing of sensor data generated by a variety of devices and sensors. This data can be used for predictive maintenance, real-time monitoring and optimization of opera­tional processes.

Another important tool in this context is SAP Vora. SAP Vora extends the capabi­lities of SAP BW/4HANA by enabling the processing of big data directly in the HANA database. It supports advanced analytics on Hadoop and other big data sources, enabling the integration and processing of big data in real time. [20] SAP Vora can, for example, be used to analyze data from different sources to gain deeper insights into business processes and make data-driven decisions.

Hadoop integration in SAP BW/4HANA

The integration of Hadoop in SAP BW/4HANA is an essential step to optimize the analysis of big data in companies. The Hadoop connector in SAP BW/4HANA makes it possible to effici­ently integrate and process large amounts of data from various Hadoop data sources. This integration offers companies the oppor­tunity to access a variety of data that lies outside their tradi­tional corporate data systems.

The SAP Data Hub plays a central role in this. It serves as an orchestration and integration platform that not only facili­tates the connection to Hadoop systems, but also enables the management, processing and analysis of this data. With the SAP Data Hub, companies can combine and prepare data from various sources such as Hadoop, SAP systems and other databases. This integration provides a unified view of the data, facili­tates data analysis and enables companies to gain deeper insights into their business processes.

Use cases and examples

SAP BW/4HANA, as an advanced data warehouse solution, offers a variety of appli­cation possi­bi­lities, especially in big data processing. Some specific use cases and examples are:

Social media and customer behavior: Companies use SAP BW/4HANA to analyze large amounts of data from social media. This enables them to better under­stand customer behavior, identify trends and adapt marketing strategies accor­dingly.

IoT and sensor data: In the manufac­turing industry, SAP BW/4HANA is used to collect and analyze data from sensors and IoT devices. This data helps companies optimize production processes, anticipate maintenance opera­tions, and improve quality assurance.

Financial and risk analysis: Financial insti­tu­tions use SAP BW/4HANA to analyze large amounts of data for risk assessment, fraud detection, and compliance monitoring. This supports effective decision-making processes and improves risk management strategies.

Healthcare: In the healthcare sector, SAP BW/4HANA is used to analyze patient data. By processing patient records, clinical trials, and research data, healthcare providers can gain better insights into patient care and treatment methods.


SAP BW/4HANA has estab­lished itself as a crucial tool in the world of big data processing. It offers a modern, flexible platform speci­fi­cally designed to process large amounts of data in real time. Thanks to the powerful in-memory technology of SAP HANA, SAP BW/4HANA can effici­ently process and analyze complex data from various sources.

A key aspect of SAP BW/4HANA is its ability to integrate big data from a variety of sources. This includes tradi­tional data sources as well as newer sources such as IoT devices, social media, and sensor data. The integration of Hadoop systems and the use of SAP Data Hub extend these capabi­lities by enabling seamless orchestration and analysis of data origi­nating from a mix of on-premise and cloud-based platforms.

SAP BW/4HANA helps companies overcome the challenges associated with big data, such as storing, processing, and analyzing large volumes of data. It enables deeper insights into customer behavior, improves decision-making, and supports innovative business strategies. The case studies and examples highlighted in various sources such as the SAP blogs, technical articles, and the official SAP help page illus­trate the diverse use cases of SAP BW/4HANA in various indus­tries.

In summary, SAP BW/4HANA plays a key role in the Big Data landscape. It not only offers powerful tools for data processing and analysis, but also a flexible and scalable archi­tecture that adapts to the ever-changing needs of modern businesses.