Dharma Teja Atluri - SAP Data Intelligence: The Comprehensive Guide

Welcome to the first comprehensive guide on SAP Data Intelligence. SAP is constantly on its own innovation journey to provide the best services to organizations. Aligned with that vision, SAP Data Hub was released in 2017 with the primary objective of deploying data orchestration and management capabilities based on Kubernetes. With the introduction of much more enhanced features, along with its place as a managed service on SAP Business Technology Platform (SAP BTP) and on-premise, SAP Data Hub evolved into what is now known as SAP Data Intelligence. In 2019, SAP decided to make SAP Data Intelligence a one-stop shop for integration, metadata management (data profiling, data lineage), connectivity, and orchestration, along with the machine learning services that support both built-in and bring your own model (BYOM)-based scenarios. Now, critically, organizations can have one tool to support multiple personas including data engineers, data stewards, data analysts, data scientists, and administrators. This flexibility allows organizations to reduce their implementation, maintenance, and operational costs with artificial intelligence (AI)/machine learning scenarios while increasing productivity and flexibility with both cloud and on-premise deployment options.

With data as the new oil, many organizations have focused on data and analytics strategies to establish data-driven platforms that not only help with the consumption of SAP and non-SAP data sets (structured and unstructured) but also can process data in real time to derive insights and support business users in making insight-driven decisions. Your business can take advantage of the current market model of dynamic data processing rather than surviving on a traditional multiplatform approach for loading and processing data. This shift in priorities introduced many changes in recent years, first with SAP Data Hub and now with SAP Data Intelligence in the current context. Furthermore, the rapid pace of innovation that come alongside those changes have resulted in a need for more expertise and experience with SAP Data Intelligence from an architectural point of view, which is critical to achieving the desired strategy. We know that information is available for certain aspects of SAP Data Hub and SAP Data Intelligence, but we believe that other sources only cover a subset of the overall information and/or only address a specific audience. With this book, we hope to provide a comprehensive overview of many different aspects of SAP Data Intelligence from multiple industry, business, and technical perspectives.

In this book, well also share our experiences from different client scenarios, as well as discuss common challenges and how to address them, with best practices and business content. In addition, weve identified a need to prepare customers the use cases where SAP Data Intelligence stands out compared to other extract, transform, and load (ETL) tools available and a need to provide customers with the right setup to put together the business case.