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Market Research | Industry Analysis
What is Data Mesh? An Overview:
Data Mesh is a concept and architectural approach for managing and scaling data in large organizations. Coined by Zhamak Dehghani, the idea behind Data Mesh is to decentralize data architecture and treat data as a product, applying principles of domain-driven design and decentralized data ownership.
In a traditional centralized data architecture, data is typically managed as a monolithic, centralized resource. In contrast, Data Mesh advocates for a decentralized approach where data is treated as a distributed product with clear ownership assigned to specific domains or business units. This involves breaking down data into smaller, autonomous units called data domains, each with its own responsibility and ownership.
Key principles of Data Mesh include:
Data Mesh aims to address the challenges associated with centralized data architectures, such as scalability issues, data silos, and the bottleneck of a single, monolithic data team. By decentralizing data and applying principles of domain-driven design, organizations can potentially achieve greater agility, scalability, and efficiency in managing their data ecosystems.
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Applications of Data Mesh Market
It's important to note that technology and application landscapes evolve rapidly, and there may be new developments or applications in these areas beyond my last update in January 2022. Always check for the latest information and trends in technology applications.
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Top Market Players in the Data Mesh Market
Amazon Web Services (AWS) | Denodo | Global IDs | 谷歌 | 惠普企业服务 | IBM | 咨科和信 | K2view | 微软 | NetApp | 甲骨文 | Radiant Logic | SAP | Snowflake | Talend | 天睿
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