What is a Data Marketplace?
A data marketplace is a platform or ecosystem where individuals, organizations and data providers can buy, sell or exchange various types of data. Acting as an intermediary between data suppliers and data consumers, a data marketplace is capable of revolutionizing the way companies can access and utilize data for projects, dashboards, reports, and applications. Imagine a user-friendly platform where finding and leveraging the data your organization generates becomes as simple as an online shopping experience. Data marketplaces benefit an organization by enhancing productivity, fostering collaboration and enabling informed decision-making. With a data marketplace, teams can effortlessly discover and acquire the data they need, streamlining workflows and saving valuable time. This user-oriented data exchange hub can provide these benefits in the following ways:
Data Marketplaces Act as the Data Storefront for Data Consumers
The data marketplace is a storefront where enterprise data assets meet the data consumers in one cloud platform. It has the essential ability to promote all the data assets across an enterprise. The data marketplace, therefore, empowers virtually every department and team to discover, share, collaborate on and access data sets, reports, dashboards, APIs, applications and other digital resources to support the business. Much like a global online retailer, an intelligent data marketplace allows companies to promote or “merchandise” their data assets via categories and metadata. These capabilities make it easy to browse for high-quality data that the business requires for actionable insights.
Common features of a data storefront include a marketplace of features such as a search engine, approval workflows, metadata management and usage analytics. For businesses to keep up with the growing volume and complexity, the data marketplace must include capabilities to integrate, cleanse, enrich, define and provide a lineal decent of data across enterprise applications to automatically scale to the data demand. Data sharing and collaboration across departments and teams reduce duplication of effort, keep data assets “evergreen”, enable synergies and improve efficiency and productivity. Overall, a data storefront is a valuable marketplace for organizations that are looking to foster business insights with their greatest asset: data.
Data Marketplaces Help Your Organization to Leverage Your Data as an Asset for Full Business Value
An automated data marketplace solution is key for organizations to promote their data assets to sustain and grow their business. With the advent of the cloud revolution, data and technology leaders alike have taken advantage of the virtually unlimited capacity of data repositories and lakes. This development allows team members to dive into all the data available like never before. However, to prevent business users from drowning in their data, an intelligent and automated data storefront is needed to realize its potential value. Data storefronts can help boost business outcomes by democratizing an enterprise’s data access, which can further support innovation and more precise decision-making.
Priyanka Jain, data science expert and the author of “Behind Every Good Decision: How Anyone Can Use Business Analytics to Turn Data into Profitable Insight,” says that “everybody needs data literacy, because data is everywhere. It’s the new currency, it's the language of the business. We need to be able to speak that.”1 As data volumes continue to grow, so does the complexity of accessing the data for insights. The majority of data consumers lack the technical skill set or capacity to source, cleanse and then utilize the data needed to drive business acumen. Most data consumers commonly reside on the business side of things. For this reason, more time should be applied to leverage all data insights with a good amount of context for further opportunities versus only compiling and validating data.
Data is critical to empower stakeholders and consumers across business processes, such as enterprise analytics, operational efficiency, price optimization, recommendation engines and data science and machine learning. Relevant and trustworthy data must get to the right hands through democratizing across the organization. To foster a data-driven culture, individuals and business groups must leverage data to inform business decisions and spur digital transformation.
Data Marketplaces Make Data Democratization Easy
Data democratization is growing in popularity across industries and technology-related organizations. One of the primary reasons may be that democratizing and sharing data across an enterprise can empower individuals to make data-informed decisions. This helps to encourage innovation and problem-solving and foster a culture of transparency and accountability within organizations.
In a recent CIO article, the importance of democratizing data in an organization, readily achieved through data marketplaces, was stressed: “[T]o get maximum value out of data and analytics, companies need to have a data-driven culture permeating the entire organization, one in which every business unit gets full access to the data it needs in the way it needs it.”2
Data democratization can also promote inclusivity by enabling a broader range of individuals to access and contribute to data-driven initiatives.
The process of making data assets available to a wider range of users within an organization who don’t require specialized technical skills or knowledge, is a significant benefit enabled by a data marketplace. A data marketplace can provide a self-service model to break down the barriers that traditionally exist between data providers and consumers. This self-service model can enable more people to access and use data to inform decision-making. It can also help to foster a culture of data sharing by providing transparency and visibility into the data assets that are available. Users can then collaborate and contribute to the development of new data sets and applications.
Figure 1 – A data marketplace enables many data democratization use cases across the organization.
In addition to the examples mentioned in Figure 1, here are a few business-critical use cases of data democratization across an enterprise, including:
- Customer Experience Enhancement: By democratizing customer data and analytics, organizations can enable customer service representatives, marketing teams and product managers to gain deeper insights into customer behavior and preferences. This allows them to personalize marketing campaigns, improve customer service interactions and develop products that better align with customer needs.
- Enterprise Analytics: By democratizing data access and analytical tools, organizations can empower business analysts and data scientists to explore and analyze data from various sources. This allows them to derive valuable insights, discover patterns and make data-driven recommendations to drive strategic decision-making at an enterprise level.
- Operational Efficiencies: Data democratization can help improve operational efficiencies by providing frontline employees with access to relevant operational data. For example, manufacturing personnel can access real-time production data to monitor performance and identify bottlenecks. They can also optimize processes for increased efficiency and reduced downtime.
- Price Optimization: Democratizing pricing data and analysis tools can enable pricing teams to make more informed decisions. They can analyze market trends, competitor pricing, customer behavior and other factors. This helps to optimize pricing strategies, identify opportunities for price adjustments and improve profitability.
- Supply Chain Optimization: Democratizing supply chain data allows stakeholders across the organization, including procurement, logistics and sales teams, to access and analyze data related to inventory levels, supplier performance, transportation costs and demand forecasts. This facilitates collaborative decision-making to optimize the supply chain, improve inventory management, minimize stockouts and enhance customer satisfaction.
- Risk Management: Data democratization can enhance risk management practices across an organization. By making relevant risk data and analytics available to risk managers, compliance teams and executives, organizations can proactively identify and mitigate risks, ensure regulatory compliance and strengthen overall risk governance.
By enabling more people to access and use data to inform decision-making and drive innovation, organizations can unlock more value from their data assets.
Four Key Requirements for a Robust Data Marketplace
Several key factors or building blocks are necessary for companies to be aware of that are thinking about developing a data marketplace, including:
- Data Governance and Security: When building a cloud data marketplace, businesses need to ensure that they have a strong data governance framework in place to protect sensitive data, comply with regulatory requirements and maintain data quality and accuracy. This involves incorporating the policies, procedures and standards that govern the collection, management and use of data within an organization. Appropriate access controls, encryption and monitoring mechanisms need to be implemented to prevent unauthorized access. This helps organizations ensure that data is only shared with authorized users who have a legitimate business need to access it.
- Data Integration and Data Management: Building a cloud data marketplace requires integrating data from various sources, which can be a complex process. It's important to have a robust data integration and management strategy in place. By doing this, they can ensure that data is cleaned, transformed and stored in a way that makes it easy to use and analyze. This includes developing data pipelines, implementing data quality checks and establishing a centralized data repository that is optimized for querying and analysis.
- User Experience and Accessibility: To encourage adoption and use of the cloud data marketplace, businesses need to ensure that the user experience is intuitive and user-friendly. This includes providing clear navigation, search and filter functions, as well as customizable dashboards and reports that can be easily shared across business and technical teams. It's also important to make sure that the marketplace is accessible to a wide range of users. This would include those with varying levels of technical expertise and abilities.
- Data Quality and Reliability: The quality and reliability of the data within the cloud data marketplace is crucial for making informed business decisions. It's important to have processes in place to ensure that the data is accurate, complete and up to date. Processes can include implementing data validation rules and monitoring data sources for changes and updates. Organizations must also establish data stewardship roles and responsibilities to ensure that the data is properly maintained and managed over time.
Consider a Prebuilt Data Storefront for Your Data Marketplace
A data marketplace democratizes data assets across the enterprise enabling broader access and use and empowering the business to make data-driven decisions. However, the quality of the data must be ensured to maintain the integrity of the results and prevent misleading insights. Therefore, it is essential to establish data governance policies and data quality checks to ensure that the data is fit for use within the data marketplace in order drive adoption and consumption. With these elements in place, a data marketplace can be your storefront of new opportunities for innovation, collaboration and growth across industries and sectors.
Cloud Data Marketplace Resources
Interested in building a successful cloud data marketplace as an efficient way to democratize and build trust in data and drive innovation across your enterprise? Check out our interactive cloud data marketplace demo, or explore our cloud data marketplace webpage to learn more.