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Features of SAP Data Hub

Orchestrate and govern all your data across a distributed data landscape to deliver intelligent data for the Intelligent Enterprise.

Trusted data landscape management

Achieve a comprehensive, open data landscape by enabling your users to work across diverse data sources and applications with relevant governance and security processes in place.

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Launchpad

  • Provide quick access to tools that can be applied to end-to-end business scenarios        
  • Embed related tools or create custom links to frequently used tools and pages

Landscape management

  • Support, view, and control a variety of options for digital landscape connections        
  • Administer zones and systems that are essential for different security concepts

Security and policies

  • Establish security settings and policies for identity control for users, groups, and roles       
  • Streamline best practices and proceses for policy management and security logging

Efficient delivery of intelligent data through data pipelines

Create complex, multistep, reusable data pipelines to process, refine, and enrich data at the source. Execute powerful data flows quickly by using distributed local processing with scheduling and monitoring across the data landscape.

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Workflows

  • Unify workflows and orchestrate and execute them in a given order
  •  Define and execute several tasks including data pipelines, file operations, and data flow graphs

Data discovery and preparation

  • Explore your data by accessing, profiling, and transforming it as you navigate a connected system 
  • Accelerate data discovery results with self-service data preparation processes

Effective governance with metadata policy management

Ensure consistent and proper handling of data quality, integrity, and security across the enterprise with a full landscape view of data lineage and quality.

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Metadata management and cataloging

  • Manage metadata intuitively to see how different data sets fit together 
  • Translate different data formats and objects semantically with proper schemas by interpreting the information

Data discovery

  • Create comprehensive profile data sets and provide insightful metrics 
  • Establish proper metadata descriptions with sourced data sets

Product Road Map

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