What combination constitutes a Data Warehouse?

What combination constitutes a Data Warehouse?

• A. Integrated decision support database and related software
• B. Social media data and internal reports
• C. Real-time data feeds and cloud storage
• D. Raw data and transactional logs

Answer: (A)

A data warehouse is fundamentally designed to support decision-making and analytical processes by consolidating data from various sources. The correct choice emphasizes that a data warehouse consists of an integrated decision support database along with the relevant software that enables users to query and analyze the data effectively. This integration is key; it allows data from multiple heterogeneous sources to be transformed, cleaned, and organized into a coherent structure that supports reporting and analysis. The associated software typically includes tools for data extraction, transformation, and loading (ETL), as well as analytical applications that provide insight into the data stored within the warehouse. The other options, while they each mention elements that may relate to data or data management, do not fully encapsulate what constitutes a data warehouse. For example, social media data and internal reports may be sources of information that could be integrated into a warehouse, but they do not represent the warehouse itself. Real-time data feeds and cloud storage focus on specific technologies and delivery methods rather than the comprehensive architecture and purpose of a data warehouse. Similarly, raw data and transactional logs refer to data in its initial form rather than the structured and processed information that a data warehouse provides for analytical decision-making. By outlining the integrated nature of the data warehouse and its supportive software, the

A data warehouse is fundamentally designed to support decision-making and analytical processes by consolidating data from various sources. The correct choice emphasizes that a data warehouse consists of an integrated decision support database along with the relevant software that enables users to query and analyze the data effectively.

This integration is key; it allows data from multiple heterogeneous sources to be transformed, cleaned, and organized into a coherent structure that supports reporting and analysis. The associated software typically includes tools for data extraction, transformation, and loading (ETL), as well as analytical applications that provide insight into the data stored within the warehouse.

The other options, while they each mention elements that may relate to data or data management, do not fully encapsulate what constitutes a data warehouse. For example, social media data and internal reports may be sources of information that could be integrated into a warehouse, but they do not represent the warehouse itself. Real-time data feeds and cloud storage focus on specific technologies and delivery methods rather than the comprehensive architecture and purpose of a data warehouse. Similarly, raw data and transactional logs refer to data in its initial form rather than the structured and processed information that a data warehouse provides for analytical decision-making.

By outlining the integrated nature of the data warehouse and its supportive software, the