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1. The process of creating and maintaining copies of data across multiple nodes in a distributed database for increased fault tolerance and availability.
2. A type of database that stores data in a plain-text file without a complex structure.
3. Processed and analyzed data that is meaningful and useful.
4. The transformation of raw data into a meaningful format through various operations and actions.
5. A database system that primarily relies on the main memory (RAM) of a computer for data storage, instead of traditional disk storage.
6. A unit of data in a flat file database that contains all relevant information about a specific entity or object.
7. The act of explaining or making sense of data or information by considering its context and implications.
8. A type of database that provides a non-relational data model, flexible schema, and horizontal scalability, often used for big data and real-time applications.
9. A type of database optimized for storing and retrieving time-stamped or time-series data, such as sensor readings or financial market data.
10. A type of database that stores data across multiple computers or servers, allowing for improved performance, fault tolerance, and scalability.
11. A database that is optimized for storing and querying spatial data, such as points, lines, and polygons.
12. A structured set of data stored electronically.
13. A type of database that organizes data into tables with rows and columns, and establishes relationships between tables.
14. The quality or state of being closely connected or appropriate to a specific purpose or topic.
15. A system that collects, processes, stores, analyzes, and disseminates information for a specific purpose.
16. A technique used in distributed databases to divide the data into smaller subsets or partitions, which are then stored on different nodes in the network.
17. The understanding or awareness acquired through the interpretation and application of information.