Traditional file-based system.
A collection of application programs that preform services for the end user, each programe defines and manages its own data.
Limitations
- Separation and isolation of data: user of set program may be unaware of the existence of other useful programs and data because each program defines and manages its own data.
- Data duplication: data may be duplicated in several programs. results in wasted space and inconsistent data(different values/formats for the same data).
- Data dependency: file structure is defined in the program code, so if the program is changed, the file structure must be changed too.
- Incompatible file formats: written in different languages, so they cant easily share data.
- Fixed queries: written to satisfy specific functions, so any new queries must be added to the program.
Database approach.
Database
A collection of logically related data(with description of that data), stored in a manner that allows access, retrieval, and use of that data.
The system catalog, also known as metadata, is a database that contains information about the structure and relationships of data stored in a system. This information includes descriptions of tables, columns, indexes, constraints, and other data elements. The purpose of the system catalog is to provide program-data independence, meaning that the structure of the data can be changed without affecting the programs that use it. This is because the programs use the information in the system catalog to access the data, rather than hard-coding the data’s structure into the programs themselves. This allows for more flexible and maintainable software systems, as changes to the data structure can be made without having to make corresponding changes to every program that uses the data.
logically related data refers to the entities, attributes, and relationships that make up the information of an organization. An entity is a real-world object or concept that is being modeled in the data, such as a customer or an order. Attributes are the characteristics or properties of an entity, such as a customer’s name or an order’s date. Relationships describe how entities are connected to one another, such as a customer having multiple orders or an order belonging to a single customer. By organizing data into entities, attributes, and relationships, it becomes possible to create a logical model of an organization’s information that accurately represents the real-world relationships between the data. This model can then be used to support the storage and retrieval of data in a manner that is both efficient and easy to understand.
Why use database approach?
- Allow the storage of data in one place and eliminate duplications.
- Allow the sharing of data.
- Data is stored in tables, which have rows and columns like a spreadsheet. A database may have multiple tables, where each table stores data about a different thing.
- Each row in a table stores data about an occurrence or instance of the thing of interest.
- A database stores data and relationships.
Components of database system.
- Database Applications are the computer programs that users work with. A computer program that interacts with database by issuing an appropriate request (SQL statement) to the DBMS.
- The Database Management System (DBMS) creates, processes, and administers databases.
- Structured Query Language (SQL) is an internationally recognized standard database language that is used by all commercial DBMSs.
Database Applications.
- Create and process Forms.
- Process queries.
- Create and process reports.
- Execute app logic.
- control application.
Database Management System (DBMS) and its functions.
- Create database
- Create tables
- Create supporting structures (e.g indexes)
- Read database data
- Modify (insert, update or delete)
- database data
- Maintain database structures
- Enforce rules
- Control concurrency
- Provide security
- Perform backup and recovery
| Advantages | Disadvantages |
|---|---|
| Control of data redundancy | Complexity |
| Data consistency | Size |
| More information from the same amount of data | Cost of DBMS |
| Sharing of data | Additional hardware costs |
| Improved data integrity and security | Cost of conversion |
| Enforcement of standards | Performance |
| Improved data accessibility and responsiveness | Higher impact of a failure |
| Increased productivity | |
| Improved maintenance through data independence | |
| Increased concurrency (enables multiple users and access) | |
| Improved backup and recovery services |
Structured Query Language (SQL).
as described above.
Includes DDL and DML.
- DDL: Data Definition Language
- used to define the structure and organization of a database, including the creation, modification, and deletion of database objects such as tables, indexes, and views.
CREATE TABLE: used to create a new table in the database ALTER TABLE: used to modify the structure of an existing table in the database DROP TABLE: used to delete a table from the database
- DML: Data Manipulation Language
- used to manipulate the data stored in a database, including the insertion, retrieval, update, and deletion of data. Examples of DML statements include:
SELECT: used to retrieve data from the database INSERT: used to insert new data into the database UPDATE: used to modify existing data in the database DELETE: used to delete data from the database
In summary, DDL is used to define the structure of the database, while DML is used to manipulate the data stored in the database. Both DDL and DML are essential components of SQL and are used together to manage the data stored in a database.
History of database processing.
Relational Database Modle:
- all current major DBMSs are based on the relational model.
- created by IBM engineer Edgar F. Codd in 1970.
- based on on mathametics called relational algebra.
Database future trends.
- Big Data
- Data sets that are so large or complex generated by web apps.
- analized to reveal patterns, trends, and associations, especially relating to human behavior and interactions.
- used to train machine learning algorithms.
- Data Warehouses
- A data warehouse is a database that is designed for reporting and data analysis, rather than for transaction processing.
- Data warehouses are used to store historical data that is used for analysis and reporting.
- Data warehouses are often used to support business intelligence systems.
- Business Intelligence Systems(BI)
- A business intelligence system is a computer-based system that is used to analyze raw data and provide business users with reports that can be used to make business decisions.
- Business intelligence systems are often used to support data warehouses.
In summary,
- Big Data refers to the large and complex data sets that require specialized tools and techniques for processing and analysis.
- Data Warehouses are centralized databases designed for reporting and analysis.
- Business Intelligence Systems are computer-based systems used to analyze data and provide insights for business decision-making.