sap data hub top5 reasons deck...sap hana hadoop, object storage sap data services etl, batch, data...
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INTERNAL
Your Top 5 Reasons Why You Should ChooseSAP Data Hub
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Top 5 reasons for choosing the SAP Data Hub solution
Universal view of the enterprise and Big Data: Get a consolidated view of all data from all data sources, covering
business processes and applications
Efficient data enrichment: Employ distributed data pipeline processing and refinement using a variety of
computation techniques such as OLAP, graph, time series, and machine learning
Intelligent discovery of data relationships: Improve data quality through self-service preparation and get a graphical
view of data correlations across your enterprise
Scalable data operations (DataOps) management solution: Orchestrate data end to end, process data where it is
located, and avoid expensive data movement
Optimal compliance and data governance across the enterprise: Maintain your security policy dynamically in one
place and help ensure that policy measures are in place to meet regulatory and corporate requirements
UNIVERSAL
1
INTELLIGENT
2
EFFICIENT
3
SCALABLE
4
COMPLIANT
5
INTERNAL© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Universal view of the enterprise and Big Data: Get a consolidated view of all data from all data sources, covering business processes and applications
UNIVERSAL
1
§ Improve landscape visibility to identify and utilize Big Data sources in and beyond your enterprise
§ Create and manage landscape connections, zones, and systems (landscape management*)
§ Generic processing logic for data from several sources no matter whether data is in the cloud or on premise, in Big Data systems or enterprise applications, and in SAP systems or Non-SAP systems
§ Enable your business users to improve their daily work with self-service interfaces (cockpit*)
* Solution feature
SAP Data Hub Cockpit
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§ Cleanse and prepare your data and centrally manage the connectivity of distributed data (Data Discovery and Preparation*)
§ Apply system and metadata discovery to browse connected systems (Metadata management and cataloging*)
§ Expose data sets, model data pipelines and manage your meta data (modeler*)
§ See how data flows through or in connected systems – including the touch points to other processes (landscape management*)
Intelligent discovery of data relationships: Improve data quality through self-service preparation and get a graphical view of data correlations across your enterprise
INTELLIGENT
2
* Solution feature
SAP Data Hub Discovery
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Efficient data enrichment: Employ distributed data pipeline processing and refinement using a variety of computation techniques such as OLAP, graph, time series, and machine learning
EFFICIENT
3
§ Incorporate complex analysis and enrichment from third-party systems such as location-aware systems and others
§ Flow-based applications consisting of reusable and configurable operations such as ETL, preparation, code execution, and connectors (modeler*)
§ Extensible operator concepts such as machine learning operators ranging from simple regression to TensorFlowapplications (modeler*)
§ Openness for co-innovation: Call to build your own operators
* Solution feature
SAP Data Hub Data pipeline
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§ Processing of the data where it is located (cloud, on premise, or hybrid) to avoid unnecessary data movement (modeler*)
§ Schedule and monitor workflows across a connected data landscape using the intuitive UI (monitoring and scheduling*)
§ Schedule task workflow executions and keep track of the status of these workflows (monitoring and scheduling*)
Scalable data operations (DataOps) management solution: Orchestrate data end to end, process data where it is located, and avoid expensive data movement
SCALABLE
4
* Solution feature
Distributed runtimeKubernetes cluster
Connected systemsSAP integration and open connectivity
SAP Data Services softwareData services job
Heterogeneous landscapes
SAP Data Hub solutionSAP HANA extended application services, advanced model
Storagefor example, Amazon S3,Hadoop
SAP HANA smart data integration flowgraphs
Data integration into SAP HANA
SAP Business Warehouse applicationProcess chainsData warehousing processes
3rd party and open sourceDirect connectivity
Storage, messaging, APIs
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Optimal compliance and data governance across the enterprise: Maintain your security policy dynamically in one place and help ensure that policy measures are in place to meet regulatory and corporate requirements
COMPLIANT
5
§ Manage metadata assets across your enterprise: Discover, understand, and consume information about data with the ability to synchronize, operate & share (cataloging*)
§ Detect quality errors and solve them during data pipeline flows, and create complex validation rules to check and prove underlying data quality (modeler*)
§ Include automated mappings, taxonomy suggestions, and semantic discovery in data governance to proactively create insights about usage and data quality
§ Establish and manage security settings and policies for identity control (security and policies*)
* Solution feature
INTERNAL© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Secu
rity
SAP Data Hub
SAP Data Hub modeler Self-service data prep SAP Data Hub cockpit
Applications Analytics Target data stores§ Enterprise –
IoT, CRM, ERP, mobile§ Dashboards§ Standard and ad hoc
reporting
§ Business warehouses§ On-premise data stores§ Cloud and hybrid stores
On premise Cloud Hybrid
§ SAP HANA and SAP BW/4HANA
§ 3rd party
§ Cloud object storage§ Cloud Hadoop
§ Cloud and on-premise Hadoop
Such as Such as Such as
User experience
Data discovery and governance
Data refinery and orchestration
Data ingestion andonboarding
SAP Data Hub distributed processing
SAP HANA Hadoop, object storage
SAP Data ServicesETL, batch, data integration
StreamingApache Kafka
Exte
nsio
ns
Attachment
GRAPHICS
X
Applications Analytics Data stores§ Enterprise applications:
CRM, ERP, HRM, …§ Dashboards§ Standard reports§ Ad hoc reporting
§ EDWs and data marts§ Big Data stores§ On-premise stores§ Cloud and hybrid stores
On premise, cloud, and hybrid
SAP Data Hub
Thank you.