Data architecture is a set of rules, policies, standards and models that govern and define the type of data collected and how it is used, stored, managed and integrated within an organization and its database systems. It provides a formal approach to creating and managing the flow of data and how it is processed across an organization’s IT systems...
Data extraction is where data is analyzed and crawled through to retrieve relevant information from data sources (like a database) in a specific pattern. Further data processing is done, which involves adding metadata and other data integration; another process in the data workflow. The majority of data extraction comes from unstructured data sources and different data formats. This unstructured data can be in any form, such as tables, indexes, and analytics.
Data in a warehouse may come from different sources, a data warehose requires three different methods to utlize the incoming data. These processes are known as Extraction, Transformation, and Loading (ETL).The process of data extraction involves retrieval of data from disheveled data sources. The data extracts are then loaded into the staging area of the relational database. Here extraction logic is used and source system is queried for data using application programming interfaces. Following this process, the data is now ready to go through the transformation phase of the ETL process.
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