Skip to content

Commit 699b8c3

Browse files
committed
Updated Data Mocks using AI page
Signed-off-by: Swapnoneel Saha <[email protected]>
1 parent a60e7a8 commit 699b8c3

File tree

1 file changed

+2
-2
lines changed
  • versioned_docs/version-2.0.0/concepts/reference/glossary

1 file changed

+2
-2
lines changed

versioned_docs/version-2.0.0/concepts/reference/glossary/mocks.md

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -12,14 +12,14 @@ keywords:
1212

1313
## What are data mocks?
1414

15-
Mocks or Data mocks are fake data that is used to simulate real data in a controlled environment. They are often used in software development to test code that interacts with data, such as APIs and databases. Data mocking can be used to:
15+
Data mocking with AI involves generating synthetic data that mimics real-world datasets, which is useful for testing, training machine learning models, and simulating data flows without relying on actual production data. They are fake data that is used to simulate real data in a controlled environment. Data mocks are often used in Software Development to test code that interacts with data, such as APIs and databases. Data mocking can be used to:
1616

1717
- Test code that is not yet connected to a real data source.
1818
- Test code that is expected to handle errors or unexpected data.
1919
- Test code that is expected to work with different types of data.
2020
- Speed up the testing process by avoiding the need to wait for real data to be loaded.
2121

22-
## Here are some of the benefits of data mocking:
22+
## What are the benefits of data mocking?
2323

2424
- **Increased test coverage**: Data mocks can be used to test code that is not yet connected to a real data source. This can help to increase the test coverage of the code, and it can help to identify bugs that would not be found if the code was only tested with real data.
2525
- **Improved testing speed**: Data mocking can be used to speed up the testing process by avoiding the need to wait for real data to be loaded. This can be especially beneficial for large data sets or for tests that need to be run repeatedly.

0 commit comments

Comments
 (0)