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Distributed Data Orchestration

Transform structured, unstructured, and streaming data into business insights.

Unified view of data across the enterprise

Streamline data integration, orchestration, and processing of all kinds of enterprise data across fragmented landscapes.

Flexible, reusable data pipelines

Design powerful data pipelines that use open-source and reuse on-premise and cloud processing engines with more than 250 operators.  

Centralised management of distributed data

Get visibility into all data sources and pipelines across your landscape with centralised management features. 

Operationalize Machine Learning

Bring your machine learning innovations to production quickly to maximise business value and increase innovation.


Machine learning project management

Leverage a machine learning cockpit to treat algorithms as a data asset.

Connected machine learning projects

Leverage a single tool to orchestrate complex data flows enriched with scalable,repeatable, and production-grade machine learning pipelines.

Comprehensive workflow automation

Enable automation across machine learning workflows – from data preparation to model selection, validation, and deployment.

Data Catalog, Metadata Management, and Governance

Know your data and help ensure it is fit for use with next-generation data management features.


Data catalog

Use metadata crawlers to explore, classify, and label data assets across your connected landscape.

Data lineage features

Review transformation history and metadata to quickly understand how, where, and why data has been altered.

Data profiling

Understand your data prior to performing data transformation or machine learning.

Business glossary

Build a business glossary to provide a unified definition of business terms with associated business rules. 

Developer Flexibility and Productivity

Get intelligent processes up and running quickly with straightforward and flexible tools.


Support for open technologies and developer tools

Use a wide range of open-source and SAP technologies, including SAP HANA, Python, Apache Spark, and TensorFlow.

Simplified data preparation and exploration

Prepare data using an intuitive user interface without any technical scripting requirements.

Ability to reuse existing tools and code

Reuse any data asset, pipeline,  or custom operator from scripting languages. 

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