These flashcards provide concise definitions and explanations of key concepts related to algorithms and time complexity. Here's a summary of each
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Time Complexity: The amount of time taken by an algorithm to run as a function of the length of the input; commonly expressed using big-O notation.
Big-O Notation: Used to express the time complexity of an algorithm.
O(1) (Constant Time): Describes an algorithm that takes the same amount of time to execute regardless of the size of the input data set.
O(n) (Linear Time): Describes an algorithm whose performance grows linearly with the size of the data set.
O(n^2) (Polynomial Time): Describes an algorithm whose performance is directly proportional to the square of the size of the data set.
O(2^n) (Exponential Time): Describes an algorithm where the time taken to execute doubles with every additional item added to the data set.
O(log n) (Logarithmic Time): Describes an algorithm where the time taken to execute grows very slowly as the size of the data set increases.
Linear Search: A method for finding a target value within a list by sequentially checking each element until a match is found or all elements have been searched. Time complexity: O(n).
Database: A collection of data organized to meet users' needs.
Database Structure: The manner in which data is organized and stored.
Database Management System (DBMS): A group of programs that manipulate the data within a database, providing an interface between the database and users or application programs.
Data Hierarchy: The organization of data in a database into sequential levels of detail.
Database Key: A field in a table used to identify a record.
Record: A collection of fields about a specific entity.
Key: A field in a record used to identify the record.
Primary Key: A field within a database table that uniquely identifies the record.
Relational Database: Organizes data into multiple tables related by common fields.
Database Tools: Software and techniques for analyzing, maintaining, and manipulating data in a database.
Schema: A graphical representation of the structure of a database.
Data Dictionary: Provides a detailed description of each field and table in a database.
Structured Query Language (SQL): A popular data manipulation language used for manipulating data in databases.
Industrial Databases: Large databases that serve as the cornerstone of information systems in businesses and enterprises.
Data Warehouse: A very large database that holds important information from various sources.
Data Mining: The process of extracting information from a data warehouse or data mart.
Distributed Database: Takes data stored in multiple locations and presents it as a single collection.
Data Center: A facility that houses servers storing mission-critical information and services.
Database Administrator (DBA): A skilled professional who directs all activities related to an organization's database, including security. [Show Less]