What is meant by Data manipulation?
The term "data manipulation" refers to all actions aimed at altering data in a database or dataset. This includes inserting new data, updating existing records, deleting data, and retrieving data from a database. Data manipulation is a crucial part of data processing, enabling companies to effectively manage and utilize their databases.
Typical software functions in the area of "data manipulation":
- Inserting Records: Adding new data into an existing database or table.
- Updating Records: Modifying existing data to reflect current information.
- Deleting Records: Removing outdated or irrelevant data from the database.
- Data Querying: Retrieving data based on specific criteria or filters.
- Batch Processing: Performing bulk operations, such as updating or deleting multiple records at once.
- Data Validation: Ensuring that the inserted or modified data meets predefined standards and rules.
- Transaction Management: Ensuring that all data manipulations are performed consistently and securely to maintain data integrity.
- Backup and Recovery: Creating backups before performing data manipulations and enabling recovery in case of errors.
Examples of "data manipulation":
- Adding New Customer Information: A CRM system inserts new customer information into the database.
- Updating Product Prices: Prices for specific products are updated based on new market conditions.
- Deleting Inactive Users: Removing users who have been inactive for over a year to clean up the database.
- Retrieving Sales Data: Querying all sales of a particular product within a specific timeframe.
- Bulk Update: All items in a database are reduced by 10% to reflect a discount promotion.
- Data Validation: Checking that all required fields are correctly filled before inserting new data.
- Transaction Rollback: If an error occurs during a data update, the entire transaction is reversed to restore the database to its original state.