In today's world where information-based big data is shared, protecting, storing and accessing data is of critical importance. Protected data should be accessible when needed. Digitization and digital transformation cause great changes in data storage and storage technologies. While the size of data backup tools is getting smaller, their capacity is increasing, and they are moving towards more cost-effective and faster reliable technologies. Despite all these positive developments, there are problems of corruption on the devices and systems where the data is stored. As a result, data access problems occur. This problem means that business processes stop in an institution where data-based transactions take place. The damage to the drying of each time spent in the study is quite large. On the other hand, in sectors such as banking, education, defense, health, insurance, agriculture, telecommunications, data is usually kept on one or more of the relational databases such as Microsoft SQL, My SQL, Postgre SQL and Oracle. There is a need for new research on how to recover data with which techniques, processes and methods in the face of a corruption event that may occur on these databases or servers. This issue has a critical importance in terms of ensuring the continuity of digital data infrastructures. If a quick solution cannot be produced in the face of a sudden interruption in database access, it will cause serious problems in business continuity. The causes of corruption in the use of Microsoft database, the measures that can be taken against them, consistency checks and database recovery methods are investigated. Techniques and methods based on database recovery scenarios in Microsoft SQL server used in large data centers are examined. Methods of overcoming a corruption problem in the database with the least damage in the shortest time are explained, and application practices are studied through VT recovery scenarios. This study also serves as a guide for students, researchers and technical staff.