Which architecture allows users to retrieve specific information from a large volume of data efficiently?

The architecture that allows users to retrieve specific information from a large volume of data efficiently is the data access architecture. This framework is designed to facilitate the extraction and manipulation of data from various sources, promoting efficient querying and data retrieval. Such architectures often employ techniques that optimize the performance of database operations, making it easier for users to access and analyze data without needing to understand the underlying complexities of the data storage systems in place.

In contrast, while data standards contribute to the consistency and interoperability of data, they do not directly address the efficiency of retrieving specific information. A data repository generally refers to a storage location for data rather than a method or system for accessing it. Online Analytical Processing (OLAP) is a specific technology that allows users to perform multidimensional analysis of business data and provides the capability for complex calculations and analytical queries, but it is a component within the broader context of data access architectures rather than an architecture itself.

Thus, data access architecture encompasses tools, processes, and technologies that streamline the retrieval of information from large data sets, making it the most suitable answer to the question.