A data architecture is an overarching framework that defines the structure, components, processes and standards for managing, organizing and integrating data within an organization. It is a key component in a successful data management approach.
Specifically, it describes a structure used in a (modern) data platform. It refers to the way data is organized and structured to meet the needs of the data analytics or data science process. It addresses aspects such as data integration, data storage, data security, data quality, data modeling, data flows and data exchange.
A well-designed data architecture helps reduce data silos, minimizes redundant data, improves data quality, facilitates the creation of data products, and it promotes the exchange of data in a standard way. It is an essential part of a robust and resilient data management framework within organizations.
The goal of data architecture is to create a robust and efficient data environment within which data analysts or data scientists can easily access the data they need to deliver data products.
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