A data analyst at an e-commerce company is tasked with creating a unified view of customer activity. The required data is spread across multiple systems: sales orders in an on-premises SQL server, customer support history in a cloud CRM, and web browsing behavior from a third-party analytics tool. The plan is to extract data from each source, standardize key fields like customer IDs and timestamps, and then load the combined data into a central data warehouse for reporting.
Which data integration process is being described?
The correct answer is ETL (Extract, Transform, Load). This is a core data integration process where data is taken from various sources, converted into a consistent format, and then loaded into a target system, such as a data warehouse. The scenario explicitly describes these three phases: extracting from the SQL server, CRM, and analytics tool; transforming the data by standardizing fields; and loading it into a central data warehouse.
Data federation is a different data integration technique that provides a virtual, unified view of data from disparate sources without physically moving it. This is incorrect because the scenario specifies that the data will be loaded into a new, central warehouse.
Master data management (MDM) is a broader discipline focused on creating and maintaining a single, authoritative source of truth for critical data entities (like 'Customer' or 'Product'). While related, it is not the term for the process of moving and transforming the data itself.
Ad-hoc querying refers to writing one-time, spontaneous queries to answer immediate questions, not building a repeatable, automated pipeline to populate a data warehouse.
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CompTIA Data+ DA0-002 (V2)
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