We talk a lot about being data-driven. But to become truly data-driven, organizations need to leverage data intelligence. They also need to find a way to balance responsible use of data with the ability to empower data consumers of all skill levels to find, understand, trust and access relevant data for their business priorities.

This means building a self-service platform — a market — that supports data sharing. The market serves as a centralized place where data owners can offer their data and data consumers can browse and shop for data relevant to their topic or domain of interest.

For organizations trying to realize the goals of data sharing and data democratization, a data marketplace offers features and benefits for virtually everyone.

Introduction to Data Marketplaces

Data sharing is about making consistent, trusted data available to data consumers across the organization when and where it’s needed. And that’s what a data marketplace does. It provides a convenient place where data consumers can access trusted data, discover who else has used the information, understand its meaning, request access and have it delivered where and when they need it. Because data consumers “shop” rather than search for data, a data marketplace simplifies the process of accessing data. Data consumers are also no longer hindered by a lack of technical expertise — If they know how to shop online, they can navigate a data marketplace.

In this way, data marketplaces allow information to circulate, creating more opportunities for insights and making life easier for decision-makers. A data marketplace acts as an intermediary between data producers, data owners and data consumers. When set up correctly, a data marketplace can revolutionize how companies access and utilize data for projects, dashboards, reports and applications.

What Is the Value of a Data Marketplace?

Ensuring every person needing reliable data has access to it can be a challenge. Providing self-service access to data is one way to enable that. However, only some people are technologically savvy, so the process needs to be simple and appropriately secure for everyone. Businesses must have a robust data governance framework to protect sensitive data, comply with regulatory requirements and maintain data quality and accuracy. Appropriate access controls, encryption and monitoring mechanisms must be implemented to prevent unauthorized access. This helps organizations ensure that data is only shared with authorized users with a legitimate business need to access it.

Automating data sharing through a data marketplace can help overcome distrust in data, remove barriers to collaboration and eliminate the cost and inefficiency of manually delivering data.

6 Big Benefits of a Data Marketplace

Here are six ways data leaders can increase speed, improve literacy, ensure trust and increase productivity and efficiency by enabling data sharing in a data marketplace.

Benefit 1: Provides Easier, More Universal Access to Data

When it comes to sharing data with your team, there are certain benefits you can always count on, no matter how you prioritize your business objectives. These benefits are related to common business metrics like cost savings, reliability and precision.

One important consideration is how quickly you can share data with your data consumers. Using manual processes can slow things down significantly. Setting up an automated data marketplace can help you meet internal data sharing demands more quickly and consistently.

By removing barriers to data acquisition, eliminating manual delivery processes and enabling automatic data provisioning, you can speed up delivery of accurate data to data consumers. This helps create organizational efficiencies, allowing your team members to focus on more critical tasks and impress your executive leadership team with faster results. Faster data delivery also means your leaders can quickly make more-informed data-driven decisions.

Benefit 2: Increases Data Literacy and Makes Teams Aware of Its Value

A data marketplace offers the opportunity to improve how well your team understands the value of your data, boosting their data literacy. But what exactly is “data literacy?”

One leading data executive recently defined data literacy as the need to have data as a second language throughout your organization. While data dictionaries, business glossaries and documented definitions are a decent beginning, data literacy represents more than that. It comes from a place of understanding, that is, not just understanding “data speak,” but being able to converse with one another about the inputs and outputs of the data landscape.

Examples of success in data literacy include business leaders who can talk to IT leaders about what they need in the world of data, with the IT team able to understand and translate that need into action. Once this data (and likely the accompanying metadata) is delivered back to the business leaders, data literacy goes beyond that initial request for information and into analysis, understanding and strategy.

Simply put, data literacy is a culture change with roots in a better understanding of one another. Perhaps most importantly, data literacy is also the cornerstone of data-driven decision-making throughout your organization. Want a digital transformation? Then it would be best if you started by making sure people can understand what that is — and know how to speak to it.

Like any culture change, true data literacy requires that teams get out of their silos and collaborate to find success. Bringing team members together to form a shared understanding is step one for improving data literacy. Thankfully, establishing a data sharing program through automating a data marketplace ensures that these team members have a gathering ground to collaborate and converse about the data they need.

Once you have team members talking and able to communicate what they need, a data marketplace can help spot the redundancy of similar or identical requests and reduce the number of times that IT and data operations leaders are asked to deliver the same data sets. Too often, such requests surface from different team members who are essentially asking for the same information, but they’re asking for it differently. Perhaps one business leader asks for all customer data originating in digital channels, while another leader is requesting data for any client purchase data information from your website. Delivering the data for this duplicative request takes extra time. A data marketplace can help you get that time back.

Benefit 3: Enhances Trust in Data and Decisions

One of the essential elements of a CDO’s job is raising confidence and trust in data. You’ve heard the “garbage in, garbage out” analogy about data quality? If the office of the CDO can’t provide improved, consistently reliable data, then they won’t be successful.

An automated data marketplace provides this consistency. A marketplace allows your teams to find relevant data assets quickly and easily. And this is data is also governed — meaning that it can be consistently trusted due to its measurable and visible level of quality. A data marketplace gives your team the peace of mind that the proper policies, processes and protection practices have been followed and that data consumers are accessing reliable data sets.

For CDOs, this means that not only is the hard work that your team has already done for data governance wisely used but it’s also made available in the form of an easy-to-use shopping experience for information. What better way to bring together people and accurate data than through an ecommerce-like digital experience?

An automated, intelligent data marketplace should also be collaborative and enabled by crowdsourced reviews. By making data access faster, easier to use, better understood, peer-reviewed and trusted, CDOs can empower their organizations to start delivering real business value. If providing business value is a CDO’s new charter, then a data marketplace brings this charter to life.

Benefit 4: Increases Efficiency and Productivity

Perhaps you are currently sharing data using a manual approach, and it goes something like this:

  1. Business users request a data set.
  2. Data operations professionals take in the request, interpret it and try to verify the request with the business data consumer. This can lead to several back-and-forth messages before the data consumer finally gets what they need.
  3. The data set is searched for, packaged and sent to the consumer. This process is then repeated over and over again.

But what happens if the number of non-technical data consumers grows exponentially? This can lead to a rapidly growing backlog — but how does that scale?

With an automated and intelligent data marketplace, data consumers can easily find and interpret the information they need without IT assistance. The marketplace provides context and delivers the requested data directly to the consumer, turning their initial "wish list" into a seamless and repeatable process. This automation reduces redundancy and the need for additional data personnel. The marketplace also empowers consumers to have confidence in the data and trust their results.

A data marketplace also makes it easier for data consumers to look for the data they need. And if they can’t find the exact data they’re looking for, the data marketplace provides a way to ask for it.

An automated data sharing program such as a data marketplace also helps ensure that today’s data leaders can bring people and data together to drive value creation.

Benefit 5. Enables Seamless Crowdsourcing

Crowdsourcing is the act of gathering information from multiple people. Your organization can benefit from this by offering many opportunities for users to share data and information. A marketplace is easy to use and encourages data users to become data owners by allowing them to publish their reports and data for others to access. Users can collaborate to improve the marketplace experience. They can share their likes and dislikes about the data, provide feedback on its quality and offer their experiences with it in real time.

Benefit 6. Provides Data Owners with a Greater Understanding of What Data Consumers Want

A data marketplace helps owners and stewards keep track of data usage. It shows owners the most requested assets and lets stewards monitor data usage to prevent compliance problems. If most data consumers in a cloud-first organization still ask for on-premises data, the CDO may need to reconsider their approach. By watching what data consumers do, they can learn about data consumers’ needs and behavior. This helps ensure that the most important data is easily accessible and delivered to the right place for the consumer.

7 Important Data Marketplace Features

Although no two data marketplaces are alike, there are some standard features you can expect to find:

  1. A contextual guide. When users hover over an item, they should be able to view more information about the asset. Data consumers and data owners require different details when requesting or approving a new asset.
  2. Browsable data categories that group data with similar content into collections. Like any shopping experience, visitors to your marketplace will find what they’re looking for when you’ve grouped the data assets into logical categories.
  3. Options to help you search. These can be simple representations of data collections showing what they’re for, who owns them, what they contain, how they can be delivered, how they should be used and who else is using them. Data marketplaces are meant to be self-service. The best marketplaces are intuitive and help users quickly find what they need.
  4. Statistics around data consumption. Data consumers can see how many people have ordered and have access to different data collections. Understanding who uses data assets can provide significant insights into what your data consumers want.
  5. A display of the data quality metrics for different data collections. Users prefer to see datasets with high data quality scores first.
  6. A process that allows users to request new types of data assets to be created. Data consumers frequently choose data assets that are already available. If they can’t find what they’re looking for, they can send a request to the data owner and ask them to create a variation of an existing data set or to create something entirely new.
  7. Dedicated chat channels for different types of data assets. These channels allow consumers and owners to learn from the data community — and offer another way to learn more about who uses your data and why they use it.

How Does a Data Marketplace Work?

There are three stages to setting up a thriving data marketplace.

Stage one: create and publish
Stage two: shop and checkout
Stage three: fulfill and track

Stage One: Create and Publish

This stage usually involves four different parts.

  1. Document and Collaborate

    Here’s where data owners answer a lot of critically important questions, such as:

    • What does the data mean?
    • Who owns this data?
    • What is this data suitable for?
    • What policies govern this data?
    • Who will use this data, and how?
  2. When data owners have answered these questions, you can document the policies, processes, business glossary, stakeholders and metadata. Then, the different business data owners (business and IT, marketing and data analytics) can collaborate to establish your definitions and key performance indicators supporting your marketplace.

  3. Discover and Curate the Data
  4. Once you have established your governance framework (and have laid the groundwork for a data-friendly, collaborative organizational culture), it’s time to discover the data.

    Then once you’ve found the data you want to use in your marketplace, it’s essential to curate it properly. This means organizing the data to make it usable and accessible for those who need it. Good curation helps business users determine whether a particular dataset is right for them. It involves labeling the data so users can find it easily, request access and comment on or discuss it.

  5. Cleanse and Master
  6. Cleansing helps ensure that users trust your marketplace's data quality. For data to be trustworthy, it must be of high quality. It must be free of errors so that, once democratized, the results that your users get from analyzing it can likewise be trusted.

    After data cleansing comes mastering, which is all about having a single source of truth. At this step, organizations generally turn to master data management (MDM) tools. This makes it possible to provide data consumers with a single trusted view into whatever dataset — customers, products or operations — they want to analyze.

  7. Protect and Monitor
  8. Here's where you address concerns about privacy and access. Ensuring that sensitive data is reliably protected against even inadvertent misuse is essential before providing access to or sharing the data. This step involves careful management of access rights to data, enforcing appropriate use policies and constant monitoring to ensure continuous protection while minimizing unnecessary risk exposure.

Stage Two: Shop and Checkout

Like a global online retailer, an intelligent data marketplace allows companies to promote or “merchandise” their data assets via categories and metadata. Data consumers browse for high-quality data that the business requires for actionable insights.

Standard features of a data storefront include a marketplace of features such as a search engine, approval workflows, metadata management and usage analytics. Instead of customer reviews, data consumers can reference quality scores and privacy policies associated with that dataset to give them context around the data's quality, trustworthiness, completeness and sensitivity.

Once they’ve identified the datasets they want, they can add them to their shopping cart and proceed to “checkout.” Checkout triggers a workflow — either integrated with existing processes within your organization through service management tools or an automated tool — where the dataset owner is asked to authorize the dataset for that particular user.

Stage Three: Fulfill and Track

Once the data owner has authorized access, you can leverage the metadata you developed in stage one. Because the dataset defines the final data structure, you can automatically generate integration mappings and provision the necessary integration jobs to package up the data and send it to the location of the data user’s choice. An important point: the more automation you can apply to the provisioning step, the more your marketplace will be able to fulfill orders on a self-service basis.

Data Marketplace Resources

Learn what a data marketplace is and how it helps exchange various types of data.

Download your guide to successful data democratization, “Data Sharing Marketplaces for Dummies.

Discover best practices and advice for how to get your data marketplace up and running in this blog, “How-to Primer for Cloud Data Marketplace.”

Learn more about how getting the correct data to the right people at the right time can be critical for the data-driven organization in this blog, “How Different Personas Benefit in the New Data Economy with a Data Marketplace.

Discover how Cloud Data Marketplace is a better way to share data.

Experience Cloud Data Marketplace in action with this interactive demo.