Managing Data in an Organization
A database is a structured collection of data that allows for the efficient storage, retrieval, and management of information. Tables are central to this structure and consist of rows and columns.
Tables
The architecture of a database table is critical in shaping how data are organized, stored, and interconnected within the database system.
The structure of a database table includes the following:
Columns, also known as fields, define the data type for a specific attribute, such as text, date, or number. For example, an employee table for employees might include columns for employee ID, name, position, and salary. Rows, alternatively known as records or tuples, represent individual data entries. In the context of an employee table, a row would correspond to a unique employee. The primary key is a designated column or combination of columns that uniquely identifies each row in a table. In an employee table, the employee ID could serve as the primary key. The foreign key is a specific field that forms a connection between data in two tables, creating a relationship. This key matches a primary key in another table. For example, in an employee table, a column named "DepartmentID" could serve as a foreign key that links to a primary key in a separate department table. Database Table Management
Managing database tables is a nuanced process that requires attention to various tasks and factors.
Table Creation: Design and create a table with the appropriate columns, data types, and constraints. This includes defining primary and foreign keys. Data Insertion: Add new records to the table. This can be done through SQL commands or through various applications that interact with the database. Data Modification: Update existing records as needed. This can involve changing the value in a specific field, deleting a record, or updating multiple records based on specific criteria. Data Retrieval: Query the table to retrieve specific information. This can include simple queries to get specific records or more complex queries that join multiple tables and apply various filters. Indexing: Create indexes on specific columns to make data retrieval more efficient. Indexing is a way to optimize the performance of queries by allowing the database system to find the data more quickly. Data Integrity Management: Ensure the data follows defined rules and constraints. This can include unique constraints, as well as constraints on permissible values for specific fields. Backup and Recovery: Regularly back up the table data and have recovery procedures in place to restore data if something goes wrong. Security Management: Implement appropriate security measures to control who can access the table and what they can do with the data. This might include various permissions for reading, writing, updating, and deleting data. Normalization: Design the table structure in a way that reduces redundancy and dependency by dividing the data into related tables. This is a key concept in relational database design. Monitoring and Optimization: Regularly monitor the performance of the table and optimize as needed. This might include restructuring the table, re-indexing, or other performance enhancements. A Data Quality Audit: Will survey the accuracy and level of completeness in all the firm's major databases, then, initiate a program for data cleansing to correct data that is incomplete, improperly formatted, redundant, or just plain wrong. An Information Policy establishes rules and specifies the organization's rules for sharing, disseminating, acquiring, standardizing, classifying, and inventorying information.
Section 2: Managing Databases
