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Description

As enterprise data explodes and is scattered across multiple systems, the oversight of privacy, data security and governance has become a very difficult task. Businesses are exposed to significant risks, including data breaches, privacy suits, and penalties. It takes months to find data privacy risks within an organization. A team of data engineers is involved in the effort. Data breaches and privacy legislation are forcing companies to better understand who has access to data and how it is used. Enterprise data is complex. Even if a team works for months to isolate data privacy risks, they may not be able to quickly find ways to reduce them.

Description

It can quickly generate data based on table names, column specifications, field sizes, data types, and other predefined constraints. These generators can easily be tailored to suit your specific needs. You can produce substantial amounts of data within just a few clicks in SQL Server Management Studio. The system allows for column-aware data generation, enabling the creation of data in one column that depends on the values in another. Users benefit from enhanced flexibility and manual oversight when crafting foreign key data. Custom generators that can be shared with your team are also available, allowing you to save regular expressions and SQL statement generators for collaborative use. Furthermore, you can write your own generators in Python, giving you the ability to create any additional data required. With seeded random data generation, you can ensure that the same dataset is produced consistently each time. Moreover, foreign key support helps maintain data consistency across various tables, making the process even more efficient and reliable. This versatility in data generation significantly streamlines workflows and enhances productivity for database management tasks.