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?
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.
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?
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!