Active State PDF

Active State: A transaction is currently executing operations. Atomicity: Ensures all operations within a transaction are completed successfully, or none are applied. Classification: A data mining technique that organizes data into predefined categories. Clustering: A data mining technique...

Active State: A transaction is currently executing operations. Atomicity: Ensures all operations within a transaction are completed successfully, or none are applied. Classification: A data mining technique that organizes data into predefined categories. Clustering: A data mining technique that groups data points with similar characteristics. Committed State: The state after a transaction has successfully completed and its changes are permanently applied. Consistency: Ensures that a transaction takes the database from one valid state to another, maintaining all rules. Cube Operator: Generates subtotals for combinations of groupings, useful in data analysis. Concurrency Control with Locking Methods: Manages simultaneous transactions to prevent issues like data inconsistency or deadlocks. Data Mining: The process of discovering patterns, correlations, and trends from large datasets. Data Mining Implementation Process: Includes steps like business understanding, data preparation, modeling, evaluation, and deployment. Data Preparation: The step where data is cleaned, transformed, and made ready for analysis. Deadlock: A situation where two or more transactions wait indefinitely for resources locked by each other. Deployment: The final stage of data mining, where results are implemented and monitored. Durability: Once a transaction is committed, its changes are permanent, even in case of system failure. Evaluation: Assessing a model's performance and checking if it meets business objectives. Failed State: A transaction fails and must be rolled back to maintain data integrity. Isolation: Transactions are executed independently, ensuring they do not interfere with each other’s data. Lock: A mechanism that restricts access to a resource during a transaction. Lost Update: Occurs when two transactions update the same data simultaneously, causing one update to be overwritten. Non-volatile: Refers to data in a data warehouse that remains unchanged after being written. Partially Committed State: The state after a transaction has executed its final operation but before it is committed. Rollup: A method used to aggregate data into higher levels of detail. Subject-Oriented: A characteristic of data warehouses where data is organized around specific business subjects like customers or products.  Terminated: A transaction has either been committed or aborted. Transaction: A logical unit of work that must be either fully completed or fully rolled back to ensure database integrity. Uncommitted: Refers to changes made by a transaction that are not yet permanent. Understanding: The initial stage of data mining that involves identifying business objectives and data requirements.