
SAP Data Intelligence
The Comprehensive Guide
- 765 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
SAP Data Intelligence
The Comprehensive Guide
About this book
Manage your data landscape with SAP Data Intelligence! Begin by understanding its architecture and capabilities and then see how to set up and install SAP Data Intelligence with step-by-step instructions. Walk through SAP Data Intelligence applications and learn how to use them for data governance, orchestration, and machine learning. Integrate with ABAP-based systems, SAP Vora, SAP Analytics Cloud, and more. Manage, secure, and operate SAP Data Intelligence with this all-in-one guide! In this book, you'll learn about: a. Configuration
Build your SAP Data Intelligence landscape! Use SAP Cloud Appliance Library for cloud deployment, including provisioning, sizing, and accessing the launchpad. Perform on-premise installations using tools like the maintenance planner. b. Capabilities
Put the core capabilities of SAP Data Intelligence to work! Manage and govern your data with the metadata explorer, use the modeler application to create data processing pipelines, create apps with the Jupyter Notebook, and more. c. Integration and Administration
Integrate, manage, and operate SAP Data Intelligence! Get step-by-step instructions for integration with SAP and non-SAP systems. Learn about key administration tasks and make sure your landscape is secure and running smoothly. Highlights include: 1) Configuration and installation
2) Data governance
3) Data processing pipelines
4) Docker images
5) ML Scenario Manager
6) Jupyter Notebook
7) Python SDK
8) Integration
9) Administration
10) Security
11) Application lifecycle management
12) Use cases
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Information
Table of contents
- Dear Reader
- Notes on Usage
- Table of Contents
- Preface
- Part I Getting Started
- 1 The Data Fabric for the Intelligent Enterprise
- 2 Architecture and Capabilities
- 3 Setup and Installation
- 4 Using SAP Data Intelligence Applications
- Part II Data Management, Orchestration, and Machine Learning
- 5 Metadata-Driven Data Governance
- 6 Modeling Data Processing Pipelines
- 7 Creating Operators and Data Types
- 8 Building Docker Images
- 9 Machine Learning
- 10 Jupyter Notebook
- 11 SAP Data Intelligence Python SDK
- Part III Integration
- 12 Integrating with ABAP Systems
- 13 Integrating with Non-SAP Systems
- 14 Integrating Big Data Workloads with SAP Vora
- 15 Integrating with SAP Data Warehouse Cloud
- 16 Integrating with SAP Analytics Cloud
- Part IV System Management, Security, and Operations
- 17 Administration
- 18 Security
- 19 Maintenance
- 20 Application Lifecycle Management
- 21 Business Content and Use Cases
- A Outlook and Roadmap
- B The Authors
- Index
- Service Pages
- Legal Notes