Introduction

In today’s fast-paced digital landscape, organizations are rapidly adopting hybrid multi-cloud strategies to harness the immense benefits of multiple cloud platforms. Recently, data platform providers have joined this wave by embracing data from diverse sources. Tech giants like Snowflake, Google Data Cloud, and Cloudera have announced their support for the open table format Apache Iceberg, signalling a collective ambition to integrate a wide array of datasets into their ecosystems.

Embracing Hybrid Multi-Cloud Strategies

Imagine an enterprise with the bulk of its data residing in a SAP landscape, while scattered bits are strewn across non-SAP systems. Their vision is to construct a scalable data analytics platform on Microsoft Azure that retains the connections between SAP datasets even when they venture beyond SAP’s confines. The reference architecture outlined here offers a blueprint to build such a powerful analytics platform.

The Integration Challenge

This article ventures into the fascinating realm of hybrid multi-cloud data platforms, with a specific focus on bringing data from SAP S/4HANA, a leading enterprise resource planning (ERP) system operating in AWS Cloud, into Azure Data Lake Storage (ADLS). This integration journey relies on Datasphere within SAP BTP as a data federation layer and harnesses Azure Databricks as an integration workhorse, facilitating the seamless transfer of data from Datasphere to ADLS. This innovative fusion of technologies streamlines data integration across diverse cloud platforms.

Leveraging Datasphere as a Data Federation Layer

SAP is on a mission to empower its customers to effortlessly integrate SAP data with non-SAP data from third-party applications and platforms, ushering in a new era of insights and digital transformation.

At the heart of this transformation is SAP Datasphere, an ingenious concept involving an open table format and a headless data warehouse. The goal is to enable data analysts working within the SAP analytics environment to work on data wherever it resides, even outside of SAP.

Datasphere assumes a pivotal role as a data federation layer within the hybrid multi-cloud data pipeline. It acts as an intermediary bridge between SAP S/4HANA and Azure Data Lake Storage, presenting a unified interface for accessing and managing data from a myriad of sources. Datasphere ensures the seamless extraction of data from S/4HANA, preserving data consistency and integrity throughout the transfer process. Most notably, it retains the semantic richness of SAP data, even as it ventures beyond the SAP landscape boundaries.

Ensuring Seamless Data Consistency and Integrity

• Using Azure Databricks as an Integration Tool
  Azure Databricks emerges as a potent cloud-based integration tool, playing a pivotal role in the hybrid multi-cloud data pipeline. This tool offers a collaborative and scalable environment for data engineers and data scientists to conduct advanced data processing and transformation tasks. Azure Databricks simplifies the data integration process, empowering organizations to efficiently transfer data from Datasphere to Azure Data Lake Storage.
• Bi-Directional Integration with SAP Datasphere
  SAP confirmed a series of agreements and partnerships as part of DataSphere, including with Databricks. Databricks and SAP delivers bi-directional integration between SAP Datasphere—with SAP data’s complete business context—with its Data Lakehouse platform on any cloud platform.

Conclusion

At Invenics Ltd (www.invenics.com), our data and analytics practices, fuelled by Digital SAP and Digital Microsoft technologies, empower enterprises to leverage data for informed decision-making. We have implemented a scalable architecture integrating SAP and Microsoft Data and Analytics tools. By adhering to best practices in data governance and analytics, we drive business growth and maintain a competitive edge in the digital landscape.

Contact Us

For further information or specific inquiries, please contact us.

Introduction:

In today’s digital landscape, organizations are increasingly adopting hybrid multi-cloud strategies to leverage the benefits of multiple cloud platforms. In the recent past, a significant trend emerged among data platform providers as they began embracing data from external sources. Companies like Snowflake, Google Data Cloud, and Cloudera announced their support for the open table format Apache Iceberg, indicating a shared goal of integrating diverse datasets into their environments.

Imagine an enterprise with the majority of its data stored in SAP landscape , while some data is scattered across non-SAP systems. They aim to construct a scalable data analytics platform on Microsoft Azure that preserves the links between SAP datasets even after data leaves SAP landscape boundaries. The outlined reference architecture provides a solution to build such an analytics platform.

This article explores the concept of a hybrid multi-cloud data platform and focuses on onboarding data from SAP S/4HANA, a leading enterprise resource planning (ERP) system deployed in AWS Cloud, to Azure Data Lake Storage (ADLS). This integration utilizes Datasphere in SAP BTP as a data federation layer and Azure Databricks as an integration tool to seamlessly load data from Datasphere to ADLS. The combination of these technologies enables efficient data integration across different cloud platforms.

The reference architecture integrates system configurations from both SAP and Azure environments, in addition to orchestrating data pipelines and transformations.

Leveraging Datasphere as a Data Federation Layer

SAP wants to help its customers “easily and confidently integrate SAP data with non-SAP data from third-party applications and platforms, unlocking entirely new insights and knowledge to bring digital transformation to another level.”

SAP Datasphere, an approach from SAP on open table format and headless dataware house , the idea is to allow data analysts working in the SAP analytics environment to work on data wherever it resides, even outside SAP.

Datasphere plays a crucial role as a data federation layer in the hybrid multi-cloud data pipeline. It acts as an intermediary between SAP S/4HANA and Azure Data Lake Storage, providing a unified interface to access and manage data from various sources. Datasphere ensures seamless extraction of data from S/4HANA, maintaining data consistency and integrity during the transfer process and most importantly, allows to maintain semantic richness of SAP data even after it leaves the SAP landscape boundaries.

Using Azure Databricks as an Integration Tool

Azure Databricks is a powerful cloud-based integration tool that is instrumental in the hybrid multi-cloud data pipeline. It provides a collaborative and scalable environment for data engineers and data scientists to perform advanced data processing and transformation tasks. Azure Databricks simplifies the data integration process, enabling organizations to efficiently load data from Datasphere to Azure Data Lake Storage.

SAP confirmed a series of agreements and partnerships as part of DataSphere, including with Databricks. Databricks and SAP delivers bi-directional integration between SAP Datasphere—with SAP data’s complete business context—with its Data Lakehouse platform on any cloud platform.

Conclusion:

At Invenics Ltd (www.invenics.com), our data and analytics practices, fueled by Digital SAP and Digital Microsoft technologies, empower enterprises to leverage data for informed decision-making. We have implemented a scalable architecture integrating SAP and Microsoft Data and Analytics tools. By adhering to best practices in data governance and analytics, we drive business growth and maintain a competitive edge in the digital landscape.

For further information or specific inquiries please contact us.