The most successful organizations strive for excellence in their products, their processes, and especially in their workers. Excelling in a profession goes beyond simply meeting short-term and long-term goals to devising and applying creative, innovative solutions. To achieve this level of excellence, companies must provide their workers with the tools that let them convert their best ideas into productivity- and revenue-boosting actions.

The data that drives the ideas powering today’s business innovations is now more likely to be found in a data marketplace that makes data assets available to parties inside and outside the organization via data sharing agreements. Data marketplaces are designed to simplify access to data and reduce data management costs. However, the most important benefit of data marketplaces for organizations is their ability to put powerful new data-driven tools in the hands of managers and employees.

What Is a Data Marketplace?

A data marketplace is an online platform that allows data providers and consumers to buy, sell, and trade data in digital storefronts. Data sellers can exhibit their wares to data users, who can compare and buy datasets from various vendors using intuitive self-service tools. Most data marketplaces are open to the public, but some are intended as data exchanges for private or internal users only.

As companies depend increasingly on data analysis for their success, the value of internal and external data resources skyrockets. Organizations turn to data marketplaces to maximize the value of their in-house data by making it available for sale or trade and to acquire data from third parties to enhance their operations and boost profitability. The data in these open marketplaces may be sourced from open-data government platforms, sensor data collected by smart cities, and urban data exchanges. Still, most of their datasets are offered by commercial data providers.

To serve the needs of data consumers and providers, data marketplaces must meet four requirements:

1. Data quality and integrity. The platforms apply data validation and quality assurance techniques to confirm that the data is accurate, accessible, and relevant to its intended tasks.
2. Security and privacy. Sensitive data must be protected as required by applicable regulations for the jurisdictions in which it will be used. The marketplaces safeguard data through the use of established security protocols.
3. Accessibility. The self-service interfaces used to search for, evaluate, and purchase datasets must be intuitive and comprehensive to ensure businesses can find the best options for their specific data needs.
4. Transaction management. Data licensing, payment systems, and other aspects of the purchase must include clear licensing agreements stipulating each party’s rights, limits, and obligations.

How Is a Data Marketplace Used?

Shopping at a data marketplace is no different than buying products from vendors in real-world or online markets. According to data vendor Datarade, the marketplaces provide the same shopping experience as retail websites and movie streaming platforms. The five stages of data commerce are browse, compare, sample, purchase, and review:

• Browse using sophisticated search tools. Data can be surfaced by type, price, geographic location, and other parameters. Potential buyers can read customer reviews of data sellers and choose from a number of potential sources for the datasets they need.
• Compare data sources. Data marketplaces allow vendors to establish a virtual storefront for their data products to facilitate feature and price comparisons, as well as benchmarks and necessary certifications. This allows businesses to make objective, unbiased comparisons.
• Request data samples. Data vendors typically offer potential customers samples of their data that shoppers can use to test the products for specific use cases before making a purchase. Business customers must also ensure that the data integrates seamlessly with their existing data processes and security requirements.
• Purchase the data in the appropriate formats. The data may be “shipped” using an API or in the form of bulk databases transferred as Amazon Simple Storage Service (S3) drops. Alternatively, the purchased data can be delivered via continuous data streams and feeds in the case of ongoing subscriptions or usage-based data licenses (as opposed to one-off purchases).
• Post a review of the data product. Data marketplaces encourage the organizations purchasing their products to review them as a way to promote transparency in the burgeoning industry. In the short term, the reviews give would-be buyers a sense of the vendor’s quality and service. Over time, the reviews help establish a community of data consumers.

The data sold and exchanged on data marketplaces encompasses all types represented in the data economy, including consumer demographic data and information on businesses and other organizations (firmographic data). Other common data types sold on the marketplaces relate to markets, geography and logistics, financial and other business transactions, social media, the Internet of Things (IoT), and public data generated by governments and nonprofit organizations.

How Do Data Marketplaces Operate?

The three components of a data marketplace are the data providers, data consumers, and data platform:

• Data providers are organizations that collect data on consumers, markets, industries, and other areas of interest to businesses and government entities. The data may be gathered from social media, e-commerce services, or data brokers, among other potential sources. Providers include data aggregators, data brokers, and research organizations, as well as businesses and individuals.
• Data consumers (or data buyers) search the marketplaces for datasets to support decision-making and planning related to their marketing, product development, risk assessment, and other operations. Businesses shopping at data marketplaces include financial and insurance firms, advertisers and marketing companies, researchers, and government agencies.
• The data platform is an online service that brings providers and consumers together in an environment designed to facilitate sharing information about the design, content, and use of various data products. The platform lets buyers know the type of data, its source, quality, and price to help them compare competing offerings. It also provides buyers with tools for analyzing and testing the data to ensure it meets their needs.

Other stakeholders in data marketplaces are government agencies and regulatory bodies charged with monitoring data governance, and the individuals whose anonymized data serves as the foundation for analytics activities. Best practices for data marketplaces include data provenance to confirm the source of the data and how it was created, confirmation that the data has been anonymized or otherwise de-identified, and formalized dispute resolution to protect the marketplace’s integrity.

What Are Different Types of Data Marketplaces?

The two primary types of data marketplaces are those that can be accessed by the public, and those intended for use by a single organization, typically a large enterprise. 

• Public data marketplaces are used primarily for business-to-business (B2B) transactions and offer data products for a range of industries. 
• Internal data marketplaces serve as a central repository for all data used by and residing within a single enterprise. They are intended for use by the company’s employees. 

Public data markets sell data as a service (DaaS) to organizations of all sizes. Data providers post a sample of their data product to the marketplace and deliver the complete product directly to customers, typically in the buyer’s preferred format. Internal data marketplaces are designed to facilitate data sharing, discovery, and usability within an organization by generating higher-quality data search results and applying more sophisticated use cases than are available with standard data platforms.

Other types of data marketplaces are hybrid, private, white label, personal, and IoT:

• Hybrid data marketplaces make some data products available to the public while reserving other offerings for approved clients due to the value or sensitivity of the underlying data. For example, a company may give its employees access to a complete dataset while making only portions of the product available to the public.
• Private data marketplaces are owned by a single data provider who restricts access to the products and maintains control over the market for the data. Private data vendors collaborate with their clients while still providing easy self-service access for data consumers.
• White label data marketplaces sell the underlying data platform to organizations to brand as their own and use to offer data products to their customers. Companies can customize their offerings and control the customer experience, but they are responsible for all data governance, rights management, and access controls.
• Personal data marketplaces allow consumers to capitalize on their own data while maintaining a level of control over its use. Individuals agree to share their personal information in exchange for a direct payment that’s based on the value of their data to the organizations purchasing it.
• IoT data marketplaces collect data generated by sensors and other IoT devices and offer it to organizations that use it to gain insight into consumer behavior, market trends, and the impact of new technologies. The services aggregate IoT data and allow the companies generating the data to increase the value of their data assets.

How Do Data Marketplaces Differ from and Interact With Other Data Platforms?

Just as the databases of the 1980s morphed into the data warehouses of the 1990s and the data lakes of the 2010s, data marketplaces are part of the continuing evolution of data management. As such, data marketplaces share many characteristics with their predecessors:

• Data marketplaces include a warehouse component that tracks the lineage of data, catalogs the data’s defining elements, and protects the quality and security of the data.
• AI techniques applied by data marketplace vendors such as Databricks and Snowflake promise to enhance the value of enterprise data by operating on unstructured data, such as images and audio files, that represent up to 90% of all enterprise data.
• Cloud-based data platforms provide businesses with the ability to “rent out” their data tools without requiring that the assets be transferred to or from any internal systems.

Data warehouses are distinguished from data lakes and data marketplaces in being limited to storing structured data, typically in relational databases. They are primarily used for online transaction processing (OLTP) and rely on SQL queries to generate business intelligence and other decision-support tools.

With the advent of big data in the 2010s, data lakes became the standard platform for storing structured data as well as the unstructured data generated by smartphones, IoT, social media, and e-commerce. Data lakes offer greater scalability and flexibility than data warehouses by supporting advanced analytics and machine learning applications without requiring the use of predefined schemas. Data lake characteristics include distributed computation and storage, schema-on-read (constructed only when data is read), and support for a broader range of file types, including audio, video, email, social media, and sensor data.

Preparing for the Data-Sharing Mandate

The European Union’s Data Act, which took effect in January 2024 but doesn’t apply until September 12, 2025, mandates that businesses and public agencies share their data equitably by negotiating fair data-sharing agreements with partners. Data marketplaces are seen as the most effective platform for buying, selling, and sharing data between businesses, individuals, and third parties.

• Data marketplaces feature a robust infrastructure for managing all types of data processes, including discovery, exchange, consumption, and analytics.
• The technology supports multiple business models for data monetization, such as dispute resolution and transparency to ensure fairness.
• The marketplaces make it easy for data vendors and consumers to integrate data products via APIs and standard protocols that facilitate search, cataloging, and metadata.
• The transaction layers, payment gateways, and price-tracking features of data marketplaces support cross-border financial settlements.
• Data marketplaces provide the quality assurance and legal and industry certifications to validate and warranty the data products. They support the compliance requirements of the EU Data Act and other regulations.

Data marketplaces help businesses realize the full value of their data assets by serving as a safe and effective conduit between data providers and data consumers, whether organizations or individuals. They turn the standard marketplace model on its head by allowing organizations to act as both buyer and seller, and to thrive in both roles.