Post 1:- Insertion anomalies: This occurs when insertion of important data is not possible when it is inserted into the database, because there is no other data present inside it occurrence of such issue is called Insertion anomalies. Let us consider an example of a network is constructed to keep the records of the customer before the file sales. But they cannot expand the buyers until they fetch the new edition of anything (Chen et al., 2021)

Deletion anomalies: This happens when the unwanted matter is to be deleted and without realizing, the useful matter also is deleted this situation is called Deletion anomalies (Chen et al., 2021) Let us take an example of a single database which contains information of company workers for suppose if some employees leave the company their particular data should be deleted but the data of the workers who are presently working also will be deleted along with them.

Modification anomalies: where a specific person is employed to maintain the current records with accuracy and he has to submit it whenever it is required (Mukherjee et al., 2021). For example, in a company there will be many promotions when a employee title must be changed because he or she is promoted if all the data is stored in the same table them there will be some confusion and a single person will have many titles, so the person who is employed in doing this work might not know which is the correct title associated to that employee

These anomalies are considered bad because, they are risky to maintain density in the database, it can result in useless updates of data, the storage will be consumed due to useless data (Mukherjee et al., 2021).

Post 2:-Database anomalies can be defined as the problems caused by the redundancy in the relations. The anomalies have a significant impact on inserting, deleting, and modifying data in the relations. The vital data can easily be lost if an elation is restructured that contains the database anomalies. It is essential to eliminate the anomalies to perform diverse processing without any issue with the relations. Different forms of database anomalies include modification, insertion, and deletion (Jurdak et al., 2011). The three forms of database anomalies are considered harmful because it is challenging to maintain the reliability of the data in the database. The other reason is that they lead to redundant data and cause unnecessary updates of information.

Modification anomalies can be described as data irregularities due to data redundancy or incomplete updates. If a change is not performed of the related rows, the database becomes unreliable, causing an update anomaly. Insertion anomalies are the problems that occur when initially inserting data into the database (Jurdak et al., 2011). Correct details should be inserted in the table to make them reliable with the other values. In this case, missing or inaccurately formatted entries are the main insertion errors. Most inventors admit that this will occur by building in the error codes that illustrate what happened.

On the other hand, deletion anomalies are the problems of the information being erased. For instance, when a row is deleted from a table representing the last part of the data, the details are also lost, making the users unable to proceed (Mercaldo et al., 2013). Since various deletion mistakes are not easily noticed for a long time, it can be challenging to recover them. Everyone experiences database anomalies in one way or another in life. Individuals and organizations should consider the backups of the data, storing offsite, and checking the data consistency to avoid losing the data.

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