![]() ![]() Making data products mainstream can become closer to a reality when coupled with the idea of a data products catalog. As a result, the usage metrics and metadata-based approach may be the right choice for many. As data products may be used by data consumers not yet identified, it is not always possible to determine security policies. A data products catalog can be a single store for data contracts so that they are applied consistently across all data consumers.įinally, data access control is not a new topic by any stretch, but data products can augment the traditional rule-based and policy-based access control into a richer metadata-based approach that is dynamic and considers attributes, usage and behavior. A data contract is defined by the data producer who may not know who will consume the data product. To avoid siloed metadata products, it’s important that the data marketplace is one capability of the data products catalog.ĭata contracts is another new topic that is gaining traction. Some organizations are already monetizing data products hence, the existence of a data marketplace has become essential. A data products catalog depends upon operational metrics to provide meaningful use to the data consumers.Īs previously mentioned, a data products catalog serves as the marketplace of data products for internal and/or external users. One of the hottest DataOps topics is data observability. Here, a data products catalog becomes a foundation for the data producers and data consumers to coalesce their tasks. DataOps practices are used by developers and maintainers of data products. ![]() Successful deployment of data products are inextricably linked to the adoption of DataOps practices that govern the life cycle of building and operations. Self-service relies on raw data or a semantic layer, while data products take a more business-value centric approach. A data product is an evolution of self-service data access with governance and a published SLA on its reliability, quality and trust. ![]() The idea of data as a product got a huge shot in the arm when Zhamak Dehghani included it in her four principles of data mesh, but its benefits extend far beyond just this. ![]() In fact, it is quite possible that the topics mentioned in this section will get refined or merged. This is not too surprising, given that most new concepts take time to mature and for standards to emerge. Data products catalogs overlap with m etadata management concepts. As mentioned earlier, data products catalogs augment the traditional data catalogs, which are used for business definition/glossary/lineage, curating metadata and discovering data’s occurrence across various sources. Enhance data-driven innovations such as identifying new data products that could deliver new products or services.ĭata producers or data engineers must collaborate with their business stakeholders to compile high value data sets into logical data products, add business context and other metadata like its datasheet, and publish it for discovery.Calculate productivity via “data telemetry” like the frequency of releases, number of data-related goals and objectives met, the level of buy-in and support for the data strategy within the organization.Explore operational metadata for data products, such as security access rights, data creators, version numbers, purpose, user consent, etc.Automations will mark data products stale based on pattern and usage analysis and thus reduce “data debt.” Understand the usage of data products and discover “data tribes.” This serves two purposes-tells the user which data product is appropriate and which unused data products to retire. ![]()
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