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Data encapsulation, also known as data hiding, is the mechanism whereby the implementation details of a class are kept hidden from the user. The user can only perform a restricted set of operations on the hidden members of the class by executing special functions commonly called methods to prevent attributes of objects from being easily viewed and accessed.
In software systems, encapsulation refers to the bundling of data with the mechanisms or methods that operate on the data. It may also refer to the limiting of direct access to some of that data, such as an object's components. [1] Essentially, encapsulation prevents external code from being concerned with the internal workings of an object.
For example, a relational database is encapsulated in the sense that its only public interface is a query language (such as SQL), which hides all the internal machinery and data structures of the database management system. As such, encapsulation is a core principle of good software architecture, at every level of granularity.
Yes - can create table, alter its definition and data, and add new rows; Some - can only create/alter table definition, not data; Browse table: Yes - can browse table definition and data; Some - can only browse table definition; Multi-server support: Yes - can manage from the same window/session multiple servers
A master data recast is another form of data transformation where the entire database of data values is transformed or recast without extracting the data from the database. All data in a well designed database is directly or indirectly related to a limited set of master database tables by a network of foreign key constraints.
In SQL, the data manipulation language comprises the SQL-data change statements, [3] which modify stored data but not the schema or database objects. Manipulation of persistent database objects, e.g., tables or stored procedures, via the SQL schema statements, [3] rather than the data stored within them, is considered to be part of a separate data definition language (DDL).
In-database processing, sometimes referred to as in-database analytics, refers to the integration of data analytics into data warehousing functionality. Today, many large databases, such as those used for credit card fraud detection and investment bank risk management, use this technology because it provides significant performance improvements over traditional methods.
Record locking is the technique of preventing simultaneous access to data in a database, to prevent inconsistent results. The classic example is demonstrated by two bank clerks attempting to update the same bank account for two different transactions. Clerks 1 and 2 both retrieve (i.e., copy) the account's record. Clerk 1 applies and saves a ...