The use of data for artificial intelligence and advanced analytics requires platforms that can efficiently process large volumes of data and flexibly make it available for a variety of use cases. SAP Databricks extends existing data platforms with precisely these capabilities, enabling the scalable implementation of data-driven analytics and AI applications.
In the context of the SAP Business Data Cloud, SAP Databricks is specifically used to complement SAP functionality. As part of a best-of-breed approach, SAP Databricks enhances the existing data architecture with powerful capabilities for data engineering, machine learning, and advanced analytics, without replacing the existing solutions. Through bidirectional integration within the SAP Business Data Cloud, data can be seamlessly exchanged between platforms and used for further analysis and AI applications. SAP solutions, such as SAP Datasphere, provide data that is structured by business domain and semantically enriched, while SAP Databricks converts this data into data structures optimized for AI and analytics applications.
This enables business units to flexibly implement data-driven use cases, for example in reporting and data analysis, in risk forecasting, in fraud detection, or in sales-related scenarios such as Next Best Action and the analysis of customer interactions. Departments benefit from a variety of evaluation and analysis methods, and queries can be flexibly implemented in common programming languages such as Python, SQL, R, or Scala.
This results in a powerful extension of the data architecture that seamlessly integrates modern analytics use cases and artificial intelligence into existing data platforms.
The use of data for artificial intelligence and advanced analytics requires platforms that can efficiently process large volumes of data and flexibly make it available for a variety of use cases. SAP Databricks extends existing data platforms with precisely these capabilities, enabling the scalable implementation of data-driven analytics and AI applications.
In the context of the SAP Business Data Cloud, SAP Databricks is specifically used to complement SAP functionality. As part of a best-of-breed approach, SAP Databricks enhances the existing data architecture with powerful capabilities for data engineering, machine learning, and advanced analytics, without replacing the existing solutions. Through bidirectional integration within the SAP Business Data Cloud, data can be seamlessly exchanged between platforms and used for further analysis and AI applications. SAP solutions, such as SAP Datasphere, provide data that is structured by business domain and semantically enriched, while SAP Databricks converts this data into data structures optimized for AI and analytics applications.
This enables business units to flexibly implement data-driven use cases, for example in reporting and data analysis, in risk forecasting, in fraud detection, or in sales-related scenarios such as Next Best Action and the analysis of customer interactions. Departments benefit from a variety of evaluation and analysis methods, and queries can be flexibly implemented in common programming languages such as Python, SQL, R, or Scala.
This results in a powerful extension of the data architecture that seamlessly integrates modern analytics use cases and artificial intelligence into existing data platforms.
SAP Databricks: The platform for analytics and artificial intelligence
From Traditional Data Analysis to Machine Learning and AI Scenarios
The use of data for artificial intelligence and advanced analytics requires platforms that can efficiently process large volumes of data and flexibly make it available for a variety of use cases. SAP Databricks extends existing data platforms with precisely these capabilities, enabling the scalable implementation of data-driven analytics and AI applications.
In the context of the SAP Business Data Cloud, SAP Databricks is specifically used to complement SAP functionality. As part of a best-of-breed approach, SAP Databricks enhances the existing data architecture with powerful capabilities for data engineering, machine learning, and advanced analytics, without replacing the existing solutions. Through bidirectional integration within the SAP Business Data Cloud, data can be seamlessly exchanged between platforms and used for further analysis and AI applications. SAP solutions, such as SAP Datasphere, provide data that is structured by domain and semantically enriched, while SAP Databricks converts this data into data structures optimized for AI and analytics applications.
This enables business units to flexibly implement data-driven use cases, for example in reporting and data analysis, in risk forecasting, in fraud detection, or in sales-related scenarios such as Next Best Action and the analysis of customer interactions. Departments benefit from a variety of evaluation and analysis methods, and queries can be flexibly implemented in common programming languages such as Python, SQL, R, or Scala. This results in a powerful extension of the data architecture that seamlessly integrates modern analytics use cases and artificial intelligence into existing data platforms.
Our expertise
Implementation of SAP Databricks Solutions for AI, Analytics, and Data Management
We can help you evaluate SAP Databricks and integrate it effectively into your existing data and analytics architecture. Working with you, we identify relevant use cases, develop specific deployment scenarios, and define the platform’s role in conjunction with existing systems—for example, within the context of the SAP Business Data Cloud or in standalone data architectures.
Based on this, we support the implementation of specific use cases, from design through prototyping and development all the way to integration into your analytics and reporting processes. In doing so, we closely involve your departments and lay the groundwork for the flexible use of SAP Databricks for advanced analytics, machine learning, and AI applications.
Seamless Integration of SAP Databricks into Your Data Architecture
Our focus is on integrating SAP Databricks into existing data landscapes and on the targeted provision of data for analytics and AI applications.
We design and implement integration scenarios in which data is structured and made available in SAP Databricks and managed via the Unity Catalog as a central metadata and governance layer, including features such as row-level security and column masking.
In addition, we develop high-performance data pipelines based on Delta Tables and implement data processing workflows for batch and real-time scenarios, as well as full and delta loads. We address the traceability of data flows through automatic lineage tracking, which makes the transformations transparent and analyzable.
Implementation and rollout of SAP Databricks as a central platform for big data analytics, data engineering, and machine learning. We help you design and implement a scalable data architecture that addresses both traditional reporting needs and advanced analytics and AI use cases.
Design and integration of data from various source and target systems—including both SAP and non-SAP systems, whether on-premises or in the cloud. We integrate SAP Databricks into your existing data and system landscape, enabling end-to-end use of your data throughout the entire process chain.
Migration of existing data pipelines, data models, and analyses from existing system landscapes to SAP Databricks. We’ll help you optimize your data processing workflows and lay the groundwork for advanced analytics and reporting capabilities.
Integration of SAP Databricks into the SAP Business Data Cloud to expand your data platform with advanced analytics and AI capabilities. We support you in defining the target architecture and integrating it into your SAP data environment so that data can be prepared and used specifically for further analysis, machine learning models, and AI applications.
Implementation and rollout of SAP Databricks as a central platform for big data analytics, data engineering, and machine learning. We help you design and implement a scalable data architecture that addresses both traditional reporting needs and advanced analytics and AI use cases.
Design and integration of data from various source and target systems—including both SAP and non-SAP systems, whether on-premises or in the cloud. We integrate SAP Databricks into your existing data and system landscape, enabling end-to-end use of your data throughout the entire process chain.
Migration of existing data pipelines, data models, and analyses from existing system landscapes to SAP Databricks. We’ll help you optimize your data processing workflows and lay the groundwork for advanced analytics and reporting capabilities.
Integration of SAP Databricks into the SAP Business Data Cloud to expand your data platform with advanced analytics and AI capabilities. We support you in defining the target architecture and integrating it into your SAP data environment so that data can be prepared and used specifically for further analysis, machine learning models, and AI applications.
SAP Databricks Implementation
Implementation and rollout of SAP Databricks as a central platform for big data analytics, data engineering, and machine learning. We help you design and implement a scalable data architecture that addresses both traditional reporting needs and advanced analytics and AI use cases.
Integration into the existing Overall Architecture
Design and integration of data from various source and target systems—including both SAP and non-SAP systems, whether on-premises or in the cloud. We integrate SAP Databricks into your existing data and system landscape, enabling end-to-end use of your data throughout the entire process chain.
Transformation of Data Pipelines
Migration of existing data pipelines, data models, and analyses from existing system environments to Databricks. We’ll help you optimize your data processing workflows and lay the groundwork for advanced analytics and reporting capabilities.
Using SAP Databricks in the Context of the SAP Business Data Cloud
Integrate SAP Databricks into the SAP Business Data Cloud to expand your data platform with advanced analytics and AI capabilities. We support you in defining the target architecture and integrating it into your SAP data environment so that data can be prepared and used specifically for further analysis, machine learning models, and AI applications.
