SAP Data Intelligence is a comprehensive solution used for data management, orchestration, monitoring, and AI/machine learning applications to consume enterprise data to generate insights.
The solution is the response to data challenges companies are facing, including storing and processing large amounts of data, and harnessing the true potential of business-sensitive data.
SAP Data Intelligence Capabilities and Objectives
SAP Data Intelligence is a combination traditional extract, transform, and load (ETL) tools, enhanced by machine learning capabilities that can be applied on top of data. The solution brings together siloed capabilities – big data, machine data, social data, IoT, and SAP S/4HANA – allowing for a stronger, integrated connection.
The key capabilities of SAP Data Intelligence include:
- Modular data pipelines with access to all necessary data operations—from data ingestion to data sharing.
- Browser-based single entry point for the entire data orchestration process, including modeling, design, deployment, monitoring, task automation, distributed processing, and system management.
- Built-in operators that can be directly used in a pipeline or customized for specific use cases.
- Ability to combine and orchestrate open-source frameworks like TensorFlow, R, or Python with SAP frameworks like Predictive Analytics Library (PAL)/Automated Predictive Library (APL) in SAP HANA.
Some objectives of using SAP Data Intelligence include the following:
- Achieve excellence in customer engagement by responding to information and events with intelligent data and actions, all enhanced by machine learning.
- Build powerful data pipelines to handle data streams, data preparation, transformations, and complex processing.
- Rapidly deploy comprehensive machine learning scenarios that are managed from a single solution, supporting all key users involved (data engineers, data scientists, business analysts, etc.).
The solution accelerates AI development and deployment with an enhanced developer and data science experience, rapid development of experimental and production environments, and comprehensive landscape management. SAP Data Intelligence helps to avoid vendor lock-in by adopting a fully portable container architecture that can easily move data across data centers and hyperscalers.
About the SAP Data Intelligence book
If you’re ready to take a deep dive into SAP Data Intelligence and all that it has to offer, we’ve published a comprehensive guide to help you learn.
Get started with an overview of SAP Data Intelligence and the basics of democratizing enterprise data assets. Readers will explore the solution’s architecture and deployment options.
Move on to setup and installation details, including step-by-step instruction for building and configuring cloud and on-premise systems. Once you gain a general understanding of a typical data science project and the different personas involved in delivering data-driven insights, you’ll be ready to explore the available applications and different activities carried out by each persona.
Next, applications in the context of data management, data orchestration, and machine learning are explained. You’ll also learn about modeling data processing pipelines and creating operators and data types. This part of the book continues with details on product features such as Docker, Jupyter Notebook, and the Python SDK.
Readers will then jump into all-things integration, learning how to connect ABAP systems, non-SAP systems, big data workloads with SAP Vora, SAP Data Warehouse Cloud, and SAP Analytics Cloud.
The book includes a section on administrative applications, focusing on System Management, License Management, and Connection Management, which are user interface-related applications. Then, learn about security and compliance requirements for administrator and user roles.
Discover how maintenance of SAP Data Intelligence is performed and then explore the different operational modes for the system. From there, learn about different components involved when it comes to application lifecycle management for AI/machine learning data science projects.
In addition to showing readers business use cases for your organization, the final chapter emphasizes how SAP Data Intelligence can serve as the one-stop shop to address all your data-driven platform requirements.
Who Is This Book For?
This book is useful for CxOs, data stakeholders, data scientists, data engineers, administrators, business data owners, enterprise architects, and project managers who need a consolidated overview of SAP Data Intelligence. It is intended for those seeking information on products like SAP S/4HANA, SAP BW/4HANA, SAP HANA, SAP Analytics Cloud, SAP Data Warehouse Cloud, and non-SAP solutions for data lakes to support the digital transformation.
About the Authors
Dharma Teja Atluri is an executive architect and AI/machine learning evangelist at IBM.
Devraj Bardhan is an accomplished global leader for SAP Innovations at IBM. He has led several large transformation projects, driving business growth agenda through innovation and digital efficiencies.
Santanu Ghosh is an SAP analytics practitioner working as a consultant for more than 15 years in the data warehouse space.
Snehasish Ghosh is an enterprise information management (EIM) consultant and data engineer working at IBM Australia.
Arindom Saha is an SAP business intelligence consultant with more than 11 years of experience working with the SAP analytics portfolio.
How to Purchase
If you’re interested in purchasing SAP Data Intelligence, follow this link and choose the format that works best for you: e-book, print edition, or bundle (both e-book and print).
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