Just as shopping for goods online involves selecting items, adding them to a cart, and choosing delivery and payment options, the process of acquiring data within organizations has evolved in a similar manner. In the age of data products and data mesh, internal data marketplaces enable business users to search for, discover, and access data for their use cases.
In this series of articles, get an excerpt from our Practical Guide to Data Mesh and discover all there is to know about data shopping as well as Zeenea’s Data Shopping experience in its Enterprise Data Marketplace:
- How to shop for data products
- The Zeenea Data Shopping experience
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In our previous article, we discussed the concept of data shopping within an internal data marketplace, addressing elements such as data product delivery and access management. In this article, we will explore the reason behind Zeenea’s decision to extend its data shopping experience beyond internal boundaries, as well as how our interface, Zeenea Studio, enables the analysis of the overall performance of your data products.
Data Product Shopping in Zeenea
In our previous article, we discussed the complexities of access rights management for data products due to the inherent risks of data consumption. In a decentralized data mesh, the data product owner assesses risks, grants access, and enforces policies based on the data’s sensitivity, the requester’s role, location, and purpose. This may involve data transformation or additional formalities, with delivery ranging from read-only access to fine-grained controls.
In a data marketplace, consumers trigger a workflow by submitting access requests, which data owners evaluate and determine access rules for, sometimes with expert input. For Zeenea’s marketplace we have chosen not to integrate this workflow directly into the solution but rather to interface with external solutions.
The idea is to offer a uniform experience for triggering an access request but to accept that the processing of this request may be very different from one environment to another, or even from one domain to another within the same organization – This principle is inherited from classical marketplaces. Most marketplaces offer a unique experience for making a purchase but connect to other systems for the operational implementation of delivery – the modalities of which can vary widely depending on the product and the seller.
This decoupling between the shopping experience and the operational implementation of delivery seems essential to us for several reasons.
The main reason is the extreme variability of the processes involved. Some organizations already have operational workflows, relying on a larger solution (data access requests are integrated into a general access request process, supported, for example, by a ticketing tool such as ServiceNow or Jira). Others have dedicated solutions supporting a high level of automation but whose deployment is not yet widespread. Still, others rely on the capabilities of their data platform, and some even on nothing at all – access is obtained through direct requests to the data owner, who handles them without a formal process. This variability is evident from one organization to another but also within the same organization – structurally, when different domains use different technologies, or temporally when the organization decides to invest in a more efficient or secure system and must gradually migrate access management to this new system.
Decoupling, therefore, allows offering a consistent experience to the consumer while adapting to the variability of operational methods.
For a data marketplace customer, the shopping experience is very simple. Once the data product(s) of interest is identified, they trigger an access request by providing the following information:
- Who they are – this information is already available.
- Which data product they want to access – this information is also already available, along with the metadata needed for decision-making.
- What they intend to use the data for – this is crucial since it drives risk management and compliance requirements.
With Zeenea, once the access request is submitted, it is processed in another system, and its status can be tracked from the marketplace – this is the direct equivalent of order tracking found on e-commerce sites.
From the consumer’s perspective, the data marketplace provides a catalog of data products (and other digital products) and a simple, universal system for gaining access to these products.
For the producer, the marketplace plays a fundamental role in managing their product portfolio.
Enhance Data Product performance with Zeenea Studio
As mentioned earlier, in addition to the e-commerce system, which is intended for consumers, a classical marketplace also offers tools dedicated to sellers, allowing them to supervise their products, respond to buyer inquiries, and monitor the economic performance of their offerings. And other tools, intended for marketplace managers, to analyze the overall performance of products and sellers.
Zeenea’s Enterprise Data Marketplace integrates these capabilities into a dedicated back-office tool, Zeenea Studio. It allows for managing the production, consolidation, and organization of metadata in a private catalog and deciding which objects will be placed in the marketplace – which is a searchable space accessible to the widest audience.
These activities primarily fall under the production process – metadata are produced and organized together with the data products. However, it also allows for monitoring the use of each data product, notably by providing a list of all its consumers and the uses associated with them.
This consumer tracking helps establish the two pillars of data mesh governance:
- Compliance and risk management – by conducting regular reviews, certifications, and impact analyses during data product changes.
- Performance management – the number of consumers, as well as the nature of the uses made of them, are the main indicators of a data product’s value. Indeed, a data product that is not consumed has no value.
As a support tool for domains to control the compliance of their products and their performance, Zeenea’s Enterprise Data Marketplace also offers comprehensive analysis capabilities of the mesh – the lineage of data products, scoring, and evaluation of their performance, control of overall compliance and risks, regulatory reporting elements, etc.
This is the magic of the federated graph, which allows for exploiting information at all scales and provides a comprehensive representation of the entire data landscape.
The Practical Guide to Data Mesh: Setting up and Supervising an enterprise-wide Data Mesh
Written by Guillaume Bodet, co-founder & CPTO at Zeenea, our guide was designed to arm you with practical strategies for implementing data mesh in your organization, helping you:
✅ Start your data mesh journey with a focused pilot project
✅ Discover efficient methods for scaling up your data mesh
✅ Acknowledge the pivotal role an internal marketplace plays in facilitating the effective consumption of data products
✅ Learn how Zeenea emerges as a robust supervision system, orchestrating an enterprise-wide data mesh
