Database Programming

In a database management system (DBMS), a view is a virtual table derived from one or more base tables. It allows users to query or manipulate data without directly accessing the underlying tables, providing a layer of abstraction and security. Views can simplify complex queries, hide sensitive information, and provide a consistent interface to the data.

New functions in RDBMS often include improved scalability, enhanced query optimization, support for advanced data types (such as JSON and XML), and better integration with cloud services. These features help to handle larger datasets efficiently, simplify complex queries, and enable seamless connectivity with cloud-based resources.

Data handling skills refer to the ability to collect, organize, analyze, and interpret data effectively. This includes tasks such as data entry, data cleaning, data visualization, and data reporting. Strong data handling skills are important for making informed decisions and solving complex problems based on data.

No, a database is a structured collection of data organized in a way that allows for efficient storage, retrieval, and manipulation of information. Data is typically stored in tables with rows and columns, making it easier to search for specific information and perform operations on the data.

Data sharing in a database refers to the ability to allow multiple users or applications to access the same data in a controlled and secure manner. It ensures that data is shared efficiently without conflicts or inconsistencies, enabling collaboration and real-time updates among users. Proper access controls and permissions are essential to protect the integrity and confidentiality of the shared data.

(computer science) A database maintained in physically separated locations and supported by a computer network so that it is possible to access all parts of the database from various points in the network.

The meanings aren't very much different. "Join in" is a more informal phrase usually used to encourage someone to participate in an activity that is already in progress.

For example, the church bulletin may say "To join the choir, come to rehearsal on Thursday." A choir leader who wants everyone to sing might turn towards the congregation and say "Let's all join in with the choir!"

No, records in a database are stored in tables, a field is a specific piece of data within a record. Each record in a table contains multiple fields, each representing a different attribute of the data being stored.

A data dictionary in a DBMS is a centralized repository that stores metadata and information about the database, such as data types, field lengths, relationships, and constraints. It helps in maintaining consistency and integrity of the database by providing a reference for developers, administrators, and users to understand the structure and content of the database. Additionally, it assists in data quality management, helps in data governance, and supports database documentation and maintenance tasks.

The SQL statement used to update data in a database is the UPDATE statement. It allows you to modify existing records in a table by specifying the columns and values to be updated based on certain conditions.

It seems like there might be a typo in your question. Did you mean "data processing"? If so, data processing refers to the collection, manipulation, and analysis of data to extract meaningful information and support decision-making processes. This can involve activities such as sorting, filtering, aggregating, and summarizing data.

A bridge table stores the many-to-many relationship between two entities in a database. It typically contains two foreign keys that reference the primary keys of the related tables, establishing the connections between them. Bridge tables facilitate querying and managing complex relationships in a relational database.

Business Data Processing (BDP): Data processing in accounting or business management

Scientific Data Processing (SDP): Data processing in experiments, or computations using data collected from such activities.

Learned dependency refers to a psychological concept where individuals become overly reliant on others for decision-making and problem-solving, to the extent that they struggle to act independently. This pattern often develops from experiences of being constantly directed or controlled by others, leading to a lack of self-confidence and autonomy. Encouraging individuals to develop their decision-making skills and assertiveness can help them overcome learned dependency.

Primary key uniquely identifies each record in a database table and must have a unique value for each record. Secondary key is a field that can be used to uniquely identify a record, but it is not the primary key. Foreign key is a field in a table that links to the primary key of another table, establishing a relationship between the two tables.

Redundancy - Repetative storage of data leading to possible multiple versions and/or ill utilisation of data storage capacity.

Inconsistency - Failure to adhere to standardised storage of data; usage of varying formats, non-confirmation to standardised/defined methods to store similar/related data.

Discrete data refers to data that can only take on specific values and cannot be measured along a continuous scale. Examples include the number of pets owned by a family or the outcome of rolling a dice. Discrete data is distinct and separate, rather than being part of a continuous range.

SQL (Structured Query Language) is a standard language used to interact with databases for tasks like querying, updating, and managing data. iSQL*Plus is an Oracle tool that allows users to run SQL commands and scripts interactively through a web browser. It provides a user-friendly interface for executing SQL queries and managing Oracle databases.

1) complexity is more compared to centralized DBMS

2) It is much more expensive to setup and maintain a DDBMS. More hardware is required the network maintenance is increased the communication costs increase and there will be additional labour costs.

3) It is much more difficult to maintain a secure network system across multiple locations. The network needs to be made secure and access to replicated data needs to be maintained across multiple sites.

4)Integrity control is more difficult

5)Lack of standard

6)lack of experience

7)more complex database design

Metadata provides information about a piece of data, such as its size, format, or author. Attributes, on the other hand, are characteristics or properties of an entity, object, or file that define its features or behavior. In essence, metadata describes the data itself, while attributes describe specific qualities or traits of an entity.

A file management system can typically access records from various storage devices such as hard drives, SSDs, network drives, and cloud storage. These systems are designed to efficiently organize and retrieve files stored in these locations.

No, a record can contain multiple pieces of data about a person or thing. It typically includes information such as name, address, contact details, and any other relevant details associated with the entity being recorded.

Data duplication happens all the time. It is an inevitable phenomenon as millions of data are gathered at very short intervals. A data warehouse is basically a database and having unintentional duplication of records created from the millions of data from other sources can hardly be avoided. In the data warehousing community, the task of finding duplicated records within large databases has long been a persistent problem and has become an area of active research. There have been many research undertakings to address the problems of data duplication caused by duplicate contamination of data. Several approaches have been implemented to counter the problem of data duplication. One approach is manually coding rules so that data can be filtered to avoid duplication. Other approaches include having applications of the latest machine learning techniques or more advance business intelligence applications. The accuracy of the different methods for countering data duplication varies. For very large data collection implementing some of the methods may be too complex and also expensive to be deployed in their full capacity.