Data mesh is a relatively new concept that aims to reduce friction in maximizing the value of data. It distributes data control to different business domains that have experts in the data relevant to them. A catalog of data products contributes to the data owners' efficiency in curating and analyzing their data for business insights.In this episode, Luis Romero, the Product Marketing Director at Collibra, talks in-depth about the four pillars of data mesh and how it can empower businesses. Jay Militscher, the Head of Data & Analytics at Collibra, also shares Collibra’s humble beginnings in executing data mesh and how they hope to improve their already robust system.Tune in to the episode to know about data mesh, its significance, and how to utilize it within your organization.Here are three reasons why you should listen to this episode:Understand the significance and the four pillars of data mesh.Learn how Collibra effectively implements data mesh.Discover how to get started in bringing in data mesh within organizations.ResourcesData Mesh Blog SeriesConnect with Luis on LinkedInConnect with Jay on LinkedIn Episode Highlights[01:50] How Data Mesh Can Help Business DomainsIT and data teams are not the experts on the data coming from the other departments.It’s best to have data in the hands of experts who will manage, curate, and cleanse data. Eventually, they turn the data into a product for its consumers.Analysts and business users waste a lot of time finding the data they need, and sometimes they even find difficulty in trusting the data.Data should be pre-packaged and available in a catalog for anyone who needs it, making it easier to verify and extract the right insights from it.The four pillars of data mesh are data ownership, data as a product, self-service data infrastructure, and federated governance.[05:50] Domain OwnershipMost organizations have multiple business domains such as finance, engineering, marketing, etc.Luis: “We should instead put that data into the hands of the true data stewards right within these domains.”The different business domains are best positioned to manage, curate, and make the data fully and readily available to be consumed by the business.[06:48] Data as a ProductData owners with full knowledge and expertise about the data should treat data like a software product.A software product has a vision, strategy, and life cycle. We should treat data in the exact same way. Treating data as a product means providing all the necessary facts and documentation. So that when it's in a catalog, it's ready to go.[08:25] Self-service Data InfrastructureLuis observed that 99% of their customers complained about their complex data landscape because they have their data across different sources.Having various data sources can overwhelm companies when they retrieve and process data — more so when turning it into a usable product.Luis: “We got to figure out a way to remove the friction from both the data producers and the consumers, and make it easy for them to go and find

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