Share datasets within the organization or with trusted external partners.Use semantic modeling and powerful visualization tools for simpler data analysis.Integrate relational data sources with other unstructured datasets, with the use of big data processing technologies.See more information about Data Management and Data Landing Zones. You can choose to deploy a single data product for centralized environments or multiple data products for distributed environments such as Data Mesh. Establish a data product architecture, which consists of a data warehouse for structured data and a data lake for semi-structured and unstructured data.The solution described in this article combines a range of Azure services that will ingest, store, process, enrich, and serve data and insights from different sources (structured, semi-structured, unstructured, and streaming). This example scenario demonstrates how to use Azure Synapse Analytics with the extensive family of Azure Data Services to build a modern data platform that's capable of handling the most common data challenges in an organization.
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