DataTerrain, a leader in Business Intelligence solutions, announced the launch of its Data masking tool for customers who are looking to protect their sensitive data. Using DataTerrain’s data masking tool, customers can mask sensitive data with ease and become compliant with various privacy laws.
Data Terrain’s data masking tool masks sensitive data in Non-Production environment by an automated process and it reduces the risk of a data breach in Non- Production environments where data is more vulnerable. This masking activity is one-way and irreversible.
Data Terrain’s data masking tool first discovers the sensitive columns available in the database by scanning the data dictionary to find where all sensitive data is located. Sensitive columns will be discovered based on the pre-defined entries in the config file. The tool also retains referential integrity, check constraints and unique constraints and uniqueness(if a unique index exists).
DataTerrain is committed to being ahead of customer BI and data needs, delivering state-of-the-art solutions to increase business productivity while reducing costs. DataTerrin’s Datamasking tool is one of the products which will achieve these goals. Customers using Datamasking tool will typically benefit from 80% reduction in effort in masking and protecting their data.
Please contact connect@dataterrain.com for a demo to have direct real-time experience.
About DataTerrain
DataTerrain is a Silicon Valley-based company and is focused on automated Business Intelligence reports/metadata migration solutions and Oracle HCM reporting solutions. DataTerrain’s proprietary automated conversion solution helps customers in converting reports across multiple BI technologies, preserving years of effort in designing the original reports. DataTerrain automated conversion service has been used by hundreds of customers across the globe. For more information visit www.dataterrain.com
Masking based on transformation type specified by user masking will be done as given below.
Transformation Type | Masking Format |
---|---|
SSN | 00-000-0000, 00 000 0000 & 000000000 |
Credit Card Numbe | 0000-0000-0000-0000, 0000 0000 0000 0000 & 0000000000000000 |
IP Address | 00.00.00.00 & 000.000.000.000 URL will be replaced with dummy URLs. |
URL | Example: - https://www.<5 Char Random String>.com/<Seq. Number> |
EMAIL ID | The email will be replaced with dummy email ids. Example: - Test User<Seq. Number>@gmail.com |
Mobile # | Replaced with dummy 10-digit sequence numbers. |
Age | Random Number between 18-90 |
Salary | Random Number between 1000-10000 |
Address | Random String |
If transformation type is not specified then masking will be done based on the datatype as given below.
Transformation Type | Masking Format |
---|---|
SSN | 00-000-0000, 00 000 0000 & 000000000 |
Credit Card Numbe | 0000-0000-0000-0000, 0000 0000 0000 0000 & 0000000000000000 |
IP Address | 00.00.00.00 & 000.000.000.000 URL will be replaced with dummy URLs. |
URL | Example: - https://www.<5 Char Random String>.com/<Seq. Number> |
EMAIL ID | The email will be replaced with dummy email ids. Example: - Test User<Seq. Number>@gmail.com |
Mobile # | Replaced with dummy 10-digit sequence numbers. |
Age | Random Number between 18-90 |
Salary | Random Number between 1000-10000 |
Address | Random String |
Data Type Masking Format
CHARACTER /VARCHAR Random String
NUMERIC Sequence Number
DATE Random Date [By adding or subtracting a random number]
TIMESTAMP
TIMESTAMP With Time Zone Random Date [By adding or subtracting a random number]
BLOB Empty BLOB
DB Housekeeping Features
OS [Linux] Housekeeping Features