We are excited to announce the launch of IBM® Data Product Hub, a modern data sharing solution designed to accelerate data-driven outcomes across your organization. Today, we’re making this product generally available to our clients across the world, following its announcement at the IBM Think conference in May 2024.

Data sharing has become the lifeblood of modern organizations, fueling growth and driving innovation. But traditional approaches to data sharing can often be a bottleneck constricting the seamless sharing of data. Siloed data, locked away in disparate systems and environments, remains inaccessible. Valuable insights are delayed, as data requests crawl through cumbersome processes. And, to make matters worse, limited data access and democratization create a bottleneck, stifling collaboration and decision-making. Meanwhile, lax data governance and security put the entire data sharing ecosystem at risk. It’s time to shift gears and revolutionize the way organizations share data.

The need for a modern data sharing solution

A modern data sharing solution can solve these challenges inherent in current data sharing mechanisms by enabling organizations to:

  • Unlock data sharing across disparate source systems and heterogeneous environments
  • Give data consumers of all skill levels the freedom to access and explore data on their own terms
  • Embed governance into the data sharing process, ensuring trust and compliance
  • Revolutionize data management by treating data as a product, reducing inefficiencies and maximizing reuse

IBM Data Product Hub: Governed data sharing made easy

IBM® Data Product Hub enables organizations to effectively share data at scale between data providers and thousands of internal data consumers, such as line-of-business users and business analysts. With this solution, data producers can easily package and share data products, sourced from heterogeneous systems and environments, and make them discoverable by data consumers across the organization.

Data Product Hub integrates with leading data stores such as IBM watsonx.data™, as well as with other IBM and non-IBM data sources to help unlock value from enterprise-wide data and reduce data silos. Data consumers can take advantage of an internal data marketplace to easily search for data products and review use cases, terms of usage and other business contexts, and subscribe to the right data product for decision-making.

Orchestrate data delivery from heterogeneous environments and data sources

IBM Data Product Hub allows data providers to package data products from various source systems using a broad range of connectors to popular data sources. This enables organizations to seamlessly share data products from on-premises sources and cloud data sources such as data warehouses, data lakes and data lakehouses to overcome the challenge of data silos.

Enforce data governance and maintain data quality

Define and enforce data contracts—data sharing agreements, terms of use and data sharing agreements—to enable governed data sharing across various uses cases. With data contracts, data consumers can trust that the data they receive is high-quality and compliant, giving them the confidence to make informed decisions. With Data Product hub, organizations can easily import metadata and reuse governance rules from data catalogs to control data access and customize search results based on user profiles.

Empower data consumers of all skill levels to easily discover and use the right data

IBM Data Product Hub facilitates data democratization. It builds on the capabilities of data catalogs such as IBM Knowledge Catalog to enable nontechnical consumers to discover and access the right data, eliminating long wait times and dependency on centralized data teams. It offers data subscriptions, which are virtual views (queries as products) that deliver data in the required format to solve business problems. These can be securely downloaded as CSV file extracts or accessed through API in Python/R based on Apache Flight connector. This approach makes sure that data is delivered in the shape and format needed by data consumers, making it more accessible and usable for a wider audience.

Unlock efficiencies by managing data as a product

Current ad hoc approaches to data requests result in long lead times, duplication of effort and high data operating costs. IBM Data Product Hub promotes an approach called data as a product and provides capabilities to package data products from various data sources. These data products can be infused with the right context including use case, value proposition, data contracts and more to enhance their discoverability and reusability across various use cases. It supports a robust system for versioning and data lifecycle management to facilitate easy maintenance and updating of data products.

Get started on your journey to modernize your data sharing approach

With IBM Data Product Hub, you can reimagine data sharing and accelerate data-driven outcomes across your organization. To discover how this solution can help your organization overcome traditional data sharing challenges, schedule a live demo with an IBM expert.

Join us for this upcoming IBM webinar on 16 July 2024, to learn about best practices to modernize your data sharing approach and maximize data dividends.

Visit the Data Product Hub webpage

More from Artificial intelligence

Applying generative AI to revolutionize telco network operations 

5 min read - Generative AI is shaping the future of telecommunications network operations. The potential applications for enhancing network operations include predicting the values of key performance indicators (KPIs), forecasting traffic congestion, enabling the move to prescriptive analytics, providing design advisory services and acting as network operations center (NOC) assistants.   In addition to these capabilities, generative AI can revolutionize drive tests, optimize network resource allocation, automate fault detection, optimize truck rolls and enhance customer experience through personalized services. Operators and suppliers are…

Re-evaluating data management in the generative AI age

4 min read - Generative AI has altered the tech industry by introducing new data risks, such as sensitive data leakage through large language models (LLMs), and driving an increase in requirements from regulatory bodies and governments. To navigate this environment successfully, it is important for organizations to look at the core principles of data management. And ensure that they are using a sound approach to augment large language models with enterprise/non-public data. A good place to start is refreshing the way organizations govern…

IBM announces new AI assistant and feature innovations at Think 2024

4 min read - As organizations integrate artificial intelligence (AI) into their operations, AI assistants that merge generative AI with automation are proving to be key productivity drivers. Despite various barriers to AI, these assistants combine generative AI and automation. This integration helps improve productivity by transforming how we work, offloading repetitive tasks, enabling self-service actions, and providing guidance on completing end-to-end processes. AI assistants from IBM facilitate enterprise adoption of AI to modernize business operations. They are purpose-built, tailored to specific use cases,…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters