In this era of data-driven decision-making and actionable insights, businesses are increasingly recognizing the value of harnessing vast data sources to stay competitive. If you’re looking to uncover new opportunities, anticipate market trends, or tailor your products and services for your customers, consider data marketplaces.

So, what is a data marketplace? It’s a  digital platform where data providers and consumers come together to exchange data assets. It facilitates data providers to market, manage, and sell their data. On the other hand, data consumers can browse, compare, and purchase data from multiple sources available in an easy-to-navigate marketplace.

These platforms play a pivotal role by offering access to diverse datasets. With easily accessible high-quality data, even smaller businesses can tap into data marketplaces for efficient decision-making. Let’s look into the details of such marketplaces for data assets.

Different Types of Data Marketplaces

Data marketplaces typically host diverse datasets spanning various industries and domains. Common types of data sold include advertising, consumer behavior, demographics, personal information, research, and market data.

A data marketplace for data assets is often confused with a data exchange network. It’s essential to understand that with data exchanges, firms see value in exchanging their data with another company rather than selling it. Instead of paying for data, companies exchange it and earn mutual benefits.

Based on the target audience and origin of the data, there are four broad categories of data marketplaces.

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1. Personal Data Marketplaces

These data marketplaces, like decentralized marketplaces, were created because customers didn’t want tech businesses exploiting their personal, sensitive data without receiving commercial benefits. In personal data marketplaces, customers get compensated for consent-managed data sharing.

If you consent to the personal data marketplace sharing information about your online behavior and location, you will be compensated for every piece of shared information; the data is acquired and managed with your consent.

Examples of personal data marketplaces include Datawallet, SynapseAI, and Datum

2. Business-to-Business (B2B) Data Marketplaces

B2B data marketplaces are for data trading between businesses and organizations. Typically, it’s businesses, and not individuals, who want to purchase data. Firms with an abundance of data often want to monetize it at scale for profit. You can register to the data marketplace platform on behalf of the firm you own or work for.

B2B data marketplaces make it easy to buy and sell data, helping businesses reach their commercial and operational goals effectively. Generally, these data markets serve as a demand-creation platform for commercial data suppliers and SaaS vendors.

Rather than obtaining data from open-source alternatives, businesses prefer B2B data markets due to the availability of analytics-grade data. The sophisticated datasets and APIs available in such data markets can provide your firm with access to meaningful insights. Since these are exclusively available for purchase, your competitors might likely not have such information, giving your firm a competitive advantage.

Examples of B2B data marketplaces include AWS Data Exchange, Snowflake, Eagle Alpha, and Datarade

3. Internal Data Marketplaces

In response to the demand for improved analytics, several businesses have created internal data markets and catalogs, which are available only to the enterprise’s employees and customers. It involves users navigating the marketplace and choosing the appropriate data for their project. Then, the information and the associated metadata will be immediately available.

Data providers can list their data in these internal data marketplaces to connect with in-market buyers of Alation and SAP. A straightforward approach to do this is to join a Data Commerce Cloud (DCC), which allows you to join both marketplaces with a single account.

Examples of internal data markets: SAP Dataspehere and Alation Marketplace

4. IoT Data Marketplaces

An IoT data marketplace is a platform for buying and selling the intelligence produced by the IoT. The data available for purchase on such a marketplace is exclusively sourced from a web of interconnected devices, giving buyers real-time signals from millions of digital touchpoints.

These data marketplaces aim to unify global information streams. When harnessed and processed, such information can yield significant insights into consumer behavior, internet trends, and technology advancements.

Since the open network supports these types of data markets, IoT marketplaces are often very accessible, with variable pricing options like pay-per-hour.

Examples of IoT data marketplaces: IOTA Data Market and Streamr

Key Requirements for a Robust Data Marketplace

  • Data Governance and Protection: Cloud-based data marketplaces require a strong data governance framework to protect sensitive data. This involves implementing appropriate access controls and encryption, preventing unauthorized access.
  • Data Integration and Management: Building a data marketplace requires integration with multiple databases and platforms. This requires building data pipelines and implementing data quality checks.
  • User Experience: Data marketplaces require filter functions, clear navigation, search and reports, and interactive dashboards to ensure an intuitive user experience.
  • Accessibility: A data marketplace needs to be accessible to a wide range of users of different technical expertise and abilities. This requires building a simplistic, user-friendly interface.
  • Data Quality and Reliability: Having accurate, complete, and up-to-date data in the data marketplace is crucial for making informed business decisions. This could include monitoring data sources and implementing data validation rules.

Benefits of a Data Marketplace

Data marketplaces offer a range of benefits that help reshape how organizations access, utilize, and leverage data. Here are some key benefits:

  • Access to Diverse Data Sources: You can access a large data collection from various industries and sources. This makes it easier to discover the information you need.
  • Cost Efficiency: Obtaining data from a data marketplace is often more cost-effective than collecting it independently.
  • Enhanced Decision-Making: Access to diverse data sets helps in generating more informed decisions, sharpening the accuracy and efficacy of your data-driven insights.
  • Increased Efficiency: Marketplaces offer immediate access to data, helping save time that would be otherwise spent in data collection and preparation. Additionally, the process of finding and acquiring data is streamlined, lowering the time and resources required to collect data.
  • Data Quality and Reliability: Reputable marketplaces often ensure data quality by vetting data providers and their datasets. This includes checks for accuracy, consistency, and timeliness.
  • Innovation and Collaboration: Data marketplaces provide a platform for data consumers to collaborate, share insights, and combine datasets for new findings. Access to diverse datasets can promote innovation across various fields, such as AI and healthcare.
  • Opportunity for Monetization: If your organization has large amounts of data, you can monetize the assets by offering the data in a data marketplace. This encourages the maintenance of high data quality standards and creates an additional revenue stream.
  • Competitive Advantage: Access to high-quality, up-to-date, and relevant data can provide your business with a competitive advantage.

How to Purchase Data in a Marketplace

Data Marketplace: Data Transactional Phases
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The fundamental transactional phases collectively comprising a data marketplace include browsing, comparing, sampling, purchasing, and reviewing.

Browse and Evaluate the Datasets

After identifying your data requirements and selecting an appropriate data marketplace, you can tailor your search based on specific data characteristics for an improved browsing experience.

Consider using the marketplace’s search and filtering tools to narrow your search to relevant data sets. You can look for specific data based on your budget and geography, just like when you enter a price range for products on Amazon or filter results based on location in Airbnb.

Compare the Data

Data marketplaces typically offer purchasers the means to quickly compare providers. While the degree of detail may vary between platforms, all data markets summarize a data provider’s offering.

With data marketplaces being self-service systems for improved decision-making, it’s essential to make it simpler for data purchasers to conduct impartial comparisons among data suppliers. This will increase the buyer’s likelihood of discovering the required data.

Sample the Data

After you narrow your search to one or two data providers, consider requesting a data sample. You must ensure that the external data that grabs your interest works for your use case before proceeding to a purchase.

External data must also be integrated with your organization’s internal systems and software. Analysts or data scientists of the organization can use a data sample and execute tests to check the suitability of the dataset, API, or data service.

Purchase the Data

When you’re satisfied with the compatibility of the data sample with your organization’s software systems and your use case, proceed with the purchase. Depending on the vendor, commercial data may be available in various formats.

Understand the payment terms, whether it’s a one-time data purchase, ongoing data subscription, or data licensing that depends on usage.

Review the Data

Data marketplaces invite purchasers to assess the data products they purchase. Buyer reviews are of significant importance and affect every transaction. Reviews provide transparency in the ecosystem, driving suppliers to give the finest data solutions and services to strive for positive feedback and stand out from the competition.

Consider providing feedback or rating the data to help future buyers.

Associated Use Cases

Data marketplaces have a wide array of uses, such as:

  • Financial Services: Financial institutions use external data sources for customer insights, risk assessment, and fraud detection.
  • BI and Analytics: Companies use marketplace data to analyze market trends, understand the competitive landscape, and identify consumer preferences.
  • Smart Cities: Analyzing data from various sources can help optimize operations, traffic management, and resource allocation.
  • Retail and E-commerce: Using competitor insights, market trends, and consumer behavior data can help with BI and targeted marketing.
  • Healthcare: Pharmaceutical companies use clinical trial data and research from data marketplaces to aid drug development.
  • ML and AI Training: Diverse datasets can help train ML models effectively and improve AI algorithms.

Data Marketplace vs. Data Warehouse vs. Data Lake

Data Marketplace
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Data lakes and warehouses are on-premise data analysis and management systems and are preferred for processing data within the company. These differ from data marketplaces as they are concerned with the storage type. At the same time, a data marketplace is a platform for only buying and selling data.

Users prefer data warehouses due to their strong establishment. However, due to their limited big data capability, data warehouses fail to provide technical information with their business intelligence and can only offer solutions to business-related problems. Therefore, data warehouses are a poor source of external data.

Data Quality and Trust in Data Marketplaces: Best Practices

Ensuring data quality and trust in data marketplaces is essential if you rely on this data for critical decision-making and operations. Bad data can lead to incorrect conclusions and ineffective strategies, among other things. Here are some best practices to ensure data quality and trust in these platforms:

1. Vet the Data Sources

Data marketplaces should provide clear information about the sources of their data. The quality and trustworthiness of the source impact the data’s reliability. Relevant questions include:

  • Who created the data?
  • How was the data collected?
  • Was the data appropriately anonymized and de-identified to protect privacy, if applicable?

2. Ensure Data Accuracy and Consistency

Data providers must implement robust data quality control processes to ensure data accuracy and consistency. Additionally, the data is expected to be regularly updated to keep it accurate and relevant.

Data consumers must evaluate the data quality in terms of accuracy, consistency, completeness, and timeliness.

  • Accuracy: Checking that the data is free from errors and is accurate. Looking into reviews and ratings from previous buyers can provide significant insights.
  • Consistency: Ensuring the data follows a consistent format and standards. It also implies the data doesn’t have any contradictions.
  • Completeness: Checking if the data includes all required elements and isn’t missing any critical information.
  • Timeliness: Ensuring the data is up-to-date; outdated data can result in poor decisions.

3. Ensure Data Governance

Data sold in marketplaces must comply with relevant data protection and privacy laws like GDPR, CCPA, and HIPAA. This requires understanding how the data was collected, whether the appropriate consent was obtained, and whether you can legally use the data.

Data protection implementation involves appropriate security measures like secure storage, controlled access, and encryption.

4. Verify Data Marketplace Reputation

Assess the reputation of data providers. Reputable sources are likely to offer reliable data. Some marketplaces implement their own quality checks, provide buyer ratings and reviews, and facilitate dispute resolution.

5. Verification and Validation

Before fully integrating the data into your systems or using it for decision-making, consider testing it. This may involve performing statistical analyses, cross-checking with other data sources, or conducting a pilot project to assess the relevance and accuracy of the data.

6. Partnership with Providers

Consider establishing strong relationships with data providers to better understand how the data was created, its limitations, and how best to use it. Such partnerships can also ensure you have access to updated and enhanced versions of datasets over time.

Data Marketplace vs. Data Exchange

A data marketplace is an online platform where consumers buy and sell data. In marketplaces, data can be purchased as bundled goods, similar to a product on an e-commerce site like Amazon. In contrast, data exchange is an alternative method for firms, where instead of selling the data, they exchange it with another company. Instead of paying for the data, these firms seek mutual benefit in exchanging it.

The two phrases have become relatively identical as both data marketplace and data exchange have similar technological advances. In some situations, both buying and selling and exchanging the data are possible. Users can prioritize several front-facing environments depending on their requirements.

For example, a public user may see a data product for sale, yet a private user member of a well-established data-sharing network may find the same product accessible for free.

Leading Data Marketplaces

Data marketplaces have become popular platforms for data exchange across diverse industries. Here are some of the prominent data marketplaces that have established themselves as trustworthy:

  • AWS Data Marketplace: Amazon Web Services (AWS) Data Exchange is a AWS marketplace that offers a vast selection of third-party data from various industries integrated with AWS cloud services.

While data providers can securely publish and monetize their data products, data consumers can easily find and use the data they need for various applications or analytics.

  • Microsoft Azure Marketplace: This marketplace for data assets offers a wide range of data products, including datasets, ML models, and APIs. You can discover and access data to integrate into your Azure-based applications and workflows.
  • Snowflake Data Marketplace: The Snowflake Data Marketplace allows you to securely access live and ready-to-query data. You can explore and utilize a diverse array of data without copying or moving it.
  • Google Cloud Public Datasets: A dynamic marketplace within the Google Cloud Platform, Google Cloud Public Datasets offers a wide range of public datasets for analysis. You can execute big data analytics and ML workloads without the complexities of data movement.
  • Datarade: This data exchange marketplace caters to businesses and organizations that require data for analytics, research, and other similar purposes.
  • Kaggle Datasets: Kaggle, the platform for ML and data science competitions, hosts a dataset repository where you can discover and download community-contributed datasets.
  • This public data portal provided by the U.S. Government offers access to a range of open datasets from various federal agencies.
  • Quandl: This data marketplace offers a vast collection of financial, economic, and alternative datasets. The intended audience comprises data analysts, financial professionals, and researchers looking for historical and real-time data.

Data as a Service (DaaS)

Data monetization is increasingly becoming a dependable and scalable revenue stream for forward-thinking businesses and companies, which is how the terms DaaS, or data-as-a-service, developed. Any business can convert to a DaaS business by selling off its assets.

Consider yourself to be the owner of a virtual event planning company. Your company primarily offers to organize webinars, conferences, and social gatherings. An online event planning platform automatically collects data about attendee demographics, venue popularity, catering patterns, and social media involvements. Similar organizations could utilize this data to get marketing insights.

You can monetize this data by catering to the needs of such organizations and selling your data on data marketplaces. Businesses can utilize these data marketplaces to transparently offer proprietary data to third parties.

Summing It Up

A data marketplace is a vital data commercialization platform, providing access to an abundance of data that drives innovation, informed decision-making, and competitive advantage. Whether you’re looking for personal data, IoT data, internal corporate data, or comprehensive B2B data exchanges, these marketplaces cater to varied needs.

While navigating these marketplaces, consider factors such as data quality, source reliability, compliance, and security. By adhering to best practices in purchasing data and utilizing it, you can maximize the benefits. With the increasing demand for high-quality, diverse data, such data marketplaces will play a critical role for data-driven enterprises.

Learn more about Hevo

If you’re looking to integrate data after you’ve gathered the required data from a data marketplace and integrated it into your system, consider using Hevo Data. With the range of readily available connectors, Hevo simplifies the data integration process; it’ll only take a few minutes to set up an integration and get started.

Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand. Also check out the Hevo pricing to choose the best plan for your organization.

Share your views on Data Marketplace in the comments section!

Freelance Technical Content Writer, Hevo Data

Suchitra's profound enthusiasm for data science and passion for writing drives her to produce high-quality content on software architecture, and data integration

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