How To Prepare The Testing Data For Database Testing


2 m read


Testing Methodolo­gies

One of the most important stages of database testing is preparing of the testing data, because a clear test data selection is very important in this process. So it’s time to discuss some techniques of preparing test data. Actually, there are only two of them.

techniques of preparing test data

1. Inserting new data

You have to clean the database and then insert all the data as it specified in your test cases. When all the required data has been inserted, you have to start executing the test cases filling “Pass/Fail” columns after comparing expected output with the actual one. It could really sound simple, but it’s not.There are some critical concerns that you have to follow.

  • Database empty instance may not be available.
  • You may find out that inserted test data is insufficient for testing soma cases such as load testing and performance.
  • Data insertion may become a difficult task due to database table dependencies.
  • When you insert limited test data, it may hide some issues, but they could be found by big data set.
  • When inserting data, complex procedures and queries may be required.

The issues, mentioned above are the most important for testing data preparation. But there are some advantages of this method as well:

  • Test cases execution becomes more efficient.
  • Bugs isolation doesn’t require any time as the DB is filled only with data specified in the test cases.
  • Testing and results comparison requires less time.
  • The test process is clutter-free.

2. Sample data subset is chosen from the actual DB data.

This is more feasible and practical method for preparation of the test data. However this technique is not for dummies: here you must have some sound technical skills and knowledge in SQL and DB Schema.
So here you have to copy and then use production data replacing some field values by other dummy values. This is definitely the best data subset for your test data because it is representing the production data. But this method is not feasible all the time because of the data security and some privacy issues.

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