## Summary:

Data monetization is a crucial business capability for organizations to create value from data and AI assets. By leveraging data products and AI, businesses can drive growth, gain a competitive edge, and explore new revenue streams. This article delves into the significance of data monetization, managing data as a product, data products and data mesh, and building a solution capability for data management. It also highlights the importance of accelerating data monetization and achieving scale with a platform approach. Additionally, the article discusses enterprise artificial intelligence and how to leverage technology to accelerate data monetization.

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Data Monetization: Unlocking Business Growth with Data Products and AI

In today’s digital age, businesses are increasingly realizing the potential of data monetization. Leveraging advanced data management software and generative AI, organizations have the opportunity to create and realize value from their data and AI assets. By adopting a value exchange system built on data products, businesses can effectively drive growth, gain a competitive advantage, and explore new revenue streams.

Why Data Monetization Matters

A single data product at a national US bank feeds 60 use cases in business applications, highlighting the significant impact of data monetization on reducing losses and generating incremental revenue. In the public sector, Transport for London provides free and open data across 80 data feeds, contributing significantly to London’s economy. Data monetization is not solely about selling data sets; it’s about improving work, enhancing business performance, and realizing the economic benefit from the created value.

Data Monetization Strategy: Managing Data as a Product

The key to successful data monetization lies in managing “data as a product,” where organizations apply product development practices to data. By treating data as a strategic asset and adopting a user-centric product approach, organizations can build trust in their data and AI by demonstrating transparency, ethics, data privacy, and security.

Data Products and Data Mesh

Data products, assembled data from various sources, can be packaged into consumable units, each with its own lifecycle environment. This facilitates flexibility in data collection and enables the delivery of data products to a variety of endpoint types. Implementing data mesh architectures emerges as a cost-effective way to serve data products and ensure robust usage tracking, risk and compliance measurements, and security.

Building a Solution Capability for Data Management

Developing a solution framework for data monetization includes three key stages: creating raw data into data products, serving these products as services via a platform, and realizing the value through transactions and measurements. However, organizations need to ensure careful management of enterprise systems, external data, and personal data to comply with regulations and handle data privacy effectively.

Accelerating Data Monetization

To accelerate data monetization, organizations can leverage enterprise artificial intelligence to power their business processes and customer offerings. Generative AI offers new options for data product design, delivery, and operational management, enabling the creation of advanced AI models and innovative data analyses.

In Conclusion

With the right technology solutions, such as IBM Cloud Pak for Data and IBM Cloud Pak for Integration, organizations can shift to using data as a strategic asset and drive innovation through enterprise AI technology. By embracing data monetization, businesses can unleash the full potential of their data and AI assets to fuel growth and gain a competitive edge in the digital era.

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FAQ

1. What is data monetization?
Data monetization is a business capability where organizations create and realize value from their data and AI assets, driving growth, gaining a competitive advantage, and exploring new revenue streams.

2. How can organizations accelerate their data monetization strategy?
By leveraging advanced data management software, generative AI, and adopting a user-centric product approach, organizations can accelerate their data monetization strategy and achieve scale with a platform approach.

3. What role does enterprise artificial intelligence play in data monetization?
Enterprise artificial intelligence enables organizations to power their business processes and customer offerings, develop advanced AI models, and innovate data analyses to accelerate data monetization.

4. What are the key components of a solution capability for data management?
A solution capability for data management includes creating raw data into data products, serving these products as services via a platform, and realizing the value through transactions and measurements, while ensuring compliance with regulations and data privacy.

5. How can organizations leverage technology to accelerate data monetization?
By utilizing technology solutions such as IBM Cloud Pak for Data and IBM Cloud Pak for Integration, organizations can effectively shift to using data as a strategic asset and inject innovation into their business models through enterprise AI technology.