Organizational silos create an inability to share data from heterogeneous source systems in a cost-effective way. 

Current approaches to managing data requests require manual data transformation and delivery, which can be time-consuming and impede the ability of organizations to keep up with growing volumes of data requests. 

IBM Data Product Hub helps streamline data sharing and automates the delivery of data products to data consumers across the organization. It breaks down silos by connecting to disparate source systems to simplify the onboarding of reusable data products, no matter where the data resides.

Organizations gain data lifecycle management capabilities to manage data-as-a-product and cost-effectively deliver fit-for-purpose data and analytics products to data consumers.

Features

• **Share and exchange ready-to-use data products: **Enable faster data sharing by automating the delivery of data products to consumers using methods such as files, APIs and natural language queries, depending on their use case.
• **Manage data as a product across the lifecycle: **Own the data product lifecycle from onboarding to retirement with a robust system for versioning, maintaining and updating data products.
• **Onboard data products from disparate source systems: **Simplify the onboarding and sharing of reusable data products, no matter where they reside, through integrations with IBM and third-party data lakehouses and source systems.
• **Govern the data exchange process: **Define and enforce data contracts like service level agreements, terms of use and data sharing agreements to embed trust in the data exchange process between data producers and data consumers.

Benefits

• **Reliable data exchange and internal data marketplace: **Discover and access the right data product curated for your use case through a reliable data marketplace.
• **Share data products from disparate sources: **Enable large-scale sharing of data and analytics products sourced from disparate source systems, such as data lakehouses and data catalogs.
• **Governed data sharing: **Embed governance mechanisms to provide assurance that data products are shared and used in a compliant manner across all use cases.
• **Automation of data product delivery: **Accelerate data request fulfilment by automating the delivery of data products using methods such as files and application programming interfaces (APIs), based on data consumers’ preferences and use cases.
• **Simplify data lifecycle management: **Gain efficiencies in how data products are packaged, shared and consumed by managing data as a product across the lifecycle.
• **Reusable data products: **Create and curate data products that can be quickly used by data consumers across multiple use cases to minimize duplicate efforts and reduce costs.