The file processing system method of organizing and managing data was a definite improvement over the manual system. The traditional file processing system well in data management for a long time.
However, there exist different disadvantages of file system data management.
The different problems with the File System Data management Processing are as follows.
1. Problems with file based system: Lengthy Development Times
The first and most important problem with the file based system approach is that even the simplest data-retrieval task requires extensive programming.
With the traditional file environment, programmers had to specify what must be done and how it was to be done. But modern databases use a nonprocedural data manipulation language that allows the user to specify what must be done without specifying how it must be done.
2. Problems with file based data management system: Difficulty of getting quick answers
The another important problem in traditional file environment system is difficulty of getting quick answers because it needs more adhoc queries and more programming for new reports. So, we can’t take the decision very fast.
3. Problems with file based system: Complex system administration
In the old traditional file based system, system administration becomes more difficult as the number of files increases. Even a simple file system with a few files requires creating and maintaining several file management programs because each file must have its own file management programs that allow the user to add, modify, and delete records.
To list the file contents and to generate reports, it needs more reporting programs. This problem is doubled if each department in the organization maintains its data by creating its own files.
4. Problems with file based system: Lack of security and Limited Data Sharing
Another fault of a file based system is a lack of security and limited data sharing.
Data sharing and security are closely related. Sharing data among multiple geographically dispersed users introduces a lot of security risks. In terms of spreadsheet data, while many spreadsheet programs provide basic security options, they are not always used, and even when they are used, they are insufficient for robust data sharing among users.
In terms of the creation of data management and reporting programs, security and data-sharing features are difficult to program so they are normally omitted in a file system environment. Such features include effective password protection, the ability to lock out parts of files or parts of the system itself, and other measures designed to safeguard data confidentiality. Even when an attempt is made to improve system and data security, the security devices tend to be limited in scope and effectiveness.
5. Problems with file based system: Extensive programming
Making changes to an existing file structure in a file based system environment, it needs extensive programming. For example, changing just one field in the original CUSTOMER file would require a program that:
1. Reads a record from the original file.
2. Transforms the original data to conform to the new structure’s storage requirements.
3. Writes the transformed data into the new file structure.
4. Repeats steps 2 to 4 for each record in the original file.
Any small change to a file structure forces modifications in all of the programs that use the data in that file. Modifications are likely to produce errors (bugs), and additional time is spent using a debugging process to find those errors.
6. Problems with file based system: Structural dependence
A file based system exhibits structural dependence, which means that access to a file is dependent on its structure.
For example, adding a customer date-of-birth field to the CUSTOMER, given this change, none of the previous programs will work with the new CUSTOMER file structure. Therefore, all of the file system programs must be modified to conform to the new file structure.
So the file based system application programs are affected by file structure modification, they exhibit structural dependence. If structural independence exists then it is possible to make changes in the file structure without affecting the application program’s ability to access the data.
7. Problems with file based system: Data dependence
Another problem with traditional file based system is, modifications in the characteristics of data, such as changing a field from integer to decimal, require changes in all the programs that access the file.
Because all data access programs are subject to change when any of the file’s data storage characteristics change (that is, changing the data type), the file system is said to exhibit data dependence.
So, If data independence exists then it is possible to make changes in the data storage characteristics without affecting the application program’s ability to access the data.
8. Problems with file based system: Data redundancy
Data redundancy is another important problem in the traditional file processing system.
Data redundancy exists when the same data are stored at different places. The file system’s structure makes it difficult to combine data from multiple sources, and its lack of security renders the file system vulnerable to security breaches. The organizational structure promotes the storage of the same basic data in different locations. The different problems with data redundancy are:
i. Poor data security: Having multiple copies of data increases the chances for a copy of the data to be susceptible to unauthorized access.
ii. Data inconsistency: Data inconsistency exists when different and conflicting versions of the same data appear in different places.
For example, suppose you change an agent’s phone number or address in the AGENT file. If you forget to make Corresponding changes in the CUSTOMER file, the files contain different data for the same agent. Reports will yield inconsistent results that depend on which version of the data is used.
iii. Data anomalies: The dictionary defines anomaly as “an abnormality.” Ideally, a field value change should be made in only a single place. Data redundancy, however, fosters an abnormal condition by forcing field value changes in many different locations. A data anomaly develops when not all of the required changes in the redundant data are made successfully.
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