Today, every business leader understands the importance of having a strong data strategy. Data-driven decision-making enables businesses to respond more quickly to market changes, gain competitive advantage, decrease operating costs and improve the customer experience. In fact, analysis from 451 Research shows that 66% of enterprises claim that most, or nearly all, of their strategic decisions are driven by data.
In today’s fast-moving digital environment, so much real-time data is being collected across mobile networks and connected devices. However, as soon as that data sits still, or is hoarded, its value plummets and businesses lose out on these advantages. To avoid this and leverage data to its full potential, enterprises need to keep pace with this rate of change and will require faster, more open access to data.
The key to this is having a data marketplace. Just like how any other product or service can be traded, data can be exchanged too – for buyers (businesses wanting to accelerate their digital transformation and make more intelligent decisions in a more agile way), data marketplaces can deliver rich, up-to-the second data from sources all around the world in a secure and streamlined manner. For sellers (data-rich businesses), a data marketplace provides a wealth of new revenue streams, allowing them to prosper within the new global data economy and help future-ready enterprises stand out from the crowd.
Though early iterations of data marketplaces may not have had the means to support the unique characteristics of various data types, the current wave of data marketplaces are becoming increasingly sophisticated in their underlying technologies and value propositions, particularly through the use of distributed ledger technology (DLT) and AI/ML orchestration for federated learning.
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Enabling the rapid and secure exchange of data
In the data economy, some of the biggest challenges is the collection and use of the data itself, especially in today’s IoT connected world where vast volumes of data are being created from thousands of different points. While organizations can collect the data themselves, this can be a time-consuming and complex process, thus many opt to acquire it from a data provider – yet even this has its own issues. For instance, buyers can still struggle with the time-consuming effort of going through governance checks to ensure data from an external provider is trustworthy and reliable.
Equally, sellers are faced with issues around data privacy, as well as the loss, theft or misuse of their data and data products. This can result in significant delays, as complex legal procedures around data compliance and liability mean data agreements are painstakingly reviewed with a fine-toothed comb. Additionally, to generate truly valuable insights from data, businesses need to leverage technologies such as Artificial Intelligence (AI) and Machine Learning (ML) – this cannot always be done internally, therefore there can be a loss of privacy when data is shared with AI or ML vendors for improvement.
As enterprises accelerate their AI/ML initiatives, they need to train their models on large valid datasets to ensure accuracy of results. Not all of this data is available within the business, so there is a need for supplementary external datasets. Aggregating this data centrally for analysis is often challenging due to data movement regulations – this is where federated learning comes in. With data marketplace capabilities like AI/ML orchestration, AI models can now be collaboratively trained on distributed data stores without the need to directly share sensitive data. This is particularly important in areas like healthcare where medical research institutions today struggle for permissioned access to a wide variety of real world data to identify the best options for treatment
Endless opportunities for any industry
The opportunities presented by a data marketplace can be applied to any business from any industry. For instance, retailers and payment providers or e-commerce platforms can exchange transaction data to gain insight into customer preferences to optimize their merchandising strategy and fine-tune the purchasing experience across various digital touchpoints. Multinational companies with large global supply chains can improve supply chain transparency and efficiency through seamless trusted exchange of data between participants In financial services, fintechs, lending providers, insurance companies and investment managers can work together to create premium, subscription-based retail banking accounts with packaged services to drive customer acquisition and recurring revenue.
- Jishnu Dasgupta, Head of Global marketing for Enterprise and Vertical markets at Nokia.
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