Data Hub Architecture.

Data hub architecture enables data producers and data consumers to exchange data freely, reliably, and at scale.

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Advantages of data hub architecture

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Free exchange
of data

Put an end to the point-to-point, hard-wired interfaces used for data sharing.

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Mediation and
acceleration

Provision data in real time to fuel both operational and analytical workloads.

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Pervasive
governance

Enforce data quality, security, privacy, and accessibility policies, centrally.

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Master your data

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Data hub architecture enables the seamless flow and governance of data, between producers and consumers.

Commonly used to manage master data for business entities of interest (e.g., Customer 360, Product 360, Location 360, etc.), a data hub is increasingly used to manage transaction and interaction data, for a complete 360 view of business entities.

Data Orchastration

Stream and govern

A data hub is an architectural pattern used to stream and govern data. As opposed to data lakes and warehouses, data hubs cater to operational use cases.

Data producers and consumers connect with each other in the framework of common governance controls, for optimized data sharing.

Data hub architectures are generally used to support operational workloads, such as streaming data to consuming applications (e.g., integrating customer data to a cloud-based CRM application), and allow for in-flight data orchestration, transformation, persistence, as well as a range of data integration and delivery styles.

Key principles of
data hub architecture

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Operational focus

Data hub architectures drive real-time operations, with continuous bi-directional data movement between source and target systems.

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Real-time data integration

Data transformation, enrichment, preparation, and delivery are performed in-flight, in milliseconds, across the architecture.

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Data persistence

A data product approach to the data hub architecture unifies and stores each instance of a business entity in its own Micro-Database™, to deliver a trusted 360 view of the business entity,

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Data flow orchestration

Data hub architectures orchestrate data flows to unify, transform, and enrich data, for seamless sharing of data between data producers and consumers.

Data Product Platform
deploys as a data hub

The K2View Data Product Platform may be deployed in a data hub architecture, to provide real-time data management capabilities – from integration and preparation, through orchestration and governance, to masking and delivery.

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Data Integration
Ingest and unify data from multiple sources, then pipeline it to target systems, always ensuring data integrity.
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Data Virtualization
Provide a logical abstraction layer to underlying systems, to make it easy to access trusted data.
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Data Preparation
Make data lakes and data warehouses instantly and always ready for analytics.
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Data Orchestration
Control data movement and data transformation, from source to target systems, code-free.
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Data Catalog
Discover and visualize metadata structure and lineage, from source to consuming microservices.
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Data Governance
Control data synchronization, access, integrity, and security – using configurable rules and processes.
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Data Masking
Protect data at rest, in use, and in transit – across production, testing, and analytics environments.
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Microservice Automation
Generate, debug, and deploy web services in minutes, with an easy-to-use, no-code/low-code framework.
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Data hub growth

“By 2024, 75% of organizations will have deployed multiple data hubs, to drive mission-critical data analytics, sharing and governance.”

Garner 2021 Strategic Planning Assumption

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Implement a data hub architecture with data products

K2View Data Product Platform empowers data teams to create and deliver data products, quickly and easily, to fuel operational and analytical workloads.

Check out our Customer Data Hub