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SAP Data Intelligence - Get more from your data with data intelligence.

How can the data (streams) from different locations be used efficiently and intelligently?
SAP Data Intelligence makes it easier for companies to understand and use their data to improve their business processes and achieve competitive advantages.

Table of contents

1. what is sap data intelligence?

SAP Data Intelligence is part of the SAP Business Technology Platform, a powerful data management solution for database and data management. This solution enables companies to connect, discover, classify, and manage data from disparate sources and systems for intelligent integration and use in business processes. The solution consists of data governance, integration and orchestration components, as well as machine learning content to help organizations better understand and leverage data. As a result, business processes can be optimized and competitive advantages can be achieved.

2. what are the advantages of this solution?

Simple data integration

With SAP Data Intelligence, you can quickly and easily integrate data sources, whether your data is structured or unstructured. This enables faster and more accurate data analysis and better decision making.

Automated processes

With SAP Data Intelligence, you can automate processes such as data cleansing, data governance, and data quality control. This enables more efficient processing of data, reduces error rates, and saves time and resources.

AI-based analytics

SAP Data Intelligence uses artificial intelligence to perform complex analyses and generate forecasts. This enables companies to make better decisions based on data-driven insights.

Cloud-based model

SAP Data Intelligence is available as a cloud-based model that allows companies to flexibly process and analyze data without investing in IT infrastructure. This ensures fast implementation, easy maintenance and scalability.

3. features of SAP Data Intelligence

3.1 Connection Management

In this feature, the various connections to data sources can be established and managed. This functionality includes support for a wide range of data sources such as databases, files, and cloud services, as well as support for data encryption and security.

3.2 Metadata Explorer

This tool provides functionality that allows users to easily find, understand, and manage their data assets. This functionality includes tools for browsing and searching metadata, viewing data provenance, and understanding data relationships.


Viewing the data and metadata, profiling, publishing, customizing the data. Connecting and monitoring the data.


Quality criteria can be set, can be monitored to see if the data meets the criteria, etc.

Business Glossary:

Creating tags to make data accessible to different departments and people.

3.3 Pipeline Modeler

This is a type of workflow builder that allows users to easily design, test and deploy data pipelines. Features include a drag-and-drop interface, a library of pre-built pipeline components, and support for real-time data processing.

Here, by means of various operators, data can be retrieved from the different databases, cleaned, transformed and further processed, and finally saved again. It is possible, for example, to integrate Python operators, machine learning operators and applications.

3.4 ML Scenario Manager

This allows users to easily create, test and deploy machine learning models. Features include a library of pre-built models, a drag-and-drop interface, and support for different programming languages.

4. application cases

Possible use cases in practice may include:

Monitor the performance of assets or machines using IoT sensors and use machine learning models to predict failures and schedule maintenance.

Integrate data from multiple sources, such as CRM systems, social media platforms, and transactional data, and use machine learning models to identify patterns and trends in customer interactions and improve customer engagement.

Monitor processes in real time using IoT sensors and leverage AI algorithms to automatically optimize processes and use resources more efficiently.

Integrate data from disparate sources, such as transactional data, customer data, and external data sources, and use machine learning models to detect suspicious activity and prevent fraud.

Integrate data from disparate sources, such as ERP systems, IoT devices, and external data sources, and use machine learning models to optimize inventories, production schedules, and supply chains.

SAP Data Intelligence provides a flexible platform to implement these and many other use cases by providing data integration, data pre-processing, machine learning and AI capabilities.

5. what opportunities are you missing without SAP Data Intelligence?

Data integration

Without SAP Data Intelligence, you will struggle to merge data from disparate sources, limiting the ability to analyze and make decisions.

Data Quality Management

Without SAP Data Intelligence, you lack the tools to review and improve data quality, which can lead to inaccurate insights and decisions.

Machine Learning and AI

Without SAP Data Intelligence, you lack the tools to develop and run machine learning models and AI applications, limiting the ability to automate and optimize processes.

Data preprocessing

Without SAP Data Intelligence, you lack the tools to prepare data for analysis, which limits your ability to analyze and make decisions.

Data visualization

Without SAP Data Intelligence, you lack the tools to create engaging and intuitive data visualizations, limiting your ability to analyze and make decisions.

Know more?

Do you still have questions or are you interested in implementing SAP Data Intelligence in your company? Then we look forward to a personal exchange. Simply get in touch with us!


Your SAP Analytics contact
Nadine Matt_2
Nadine Matt
Inhouse Sales Analytics

Published by:

Christopher Maier

SAP Analytics consultant


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