Our Data Discovery and Data Masking in Action
The demo is based on a beta version of our brand new NLP engine. We are continuously testing and improving its performance and accuracy. You can perform sensitive data discovery and masking for upto 13 different data classifications in this demo. Find more about the types of data classifications supported here.
This demo uses a beta version of our brand new Natural Language Processing (NLP) engine. We are continuously evolving our NLP models, to improve accuracy and performance. On deployment, the discovery configuration and models will be adjusted to your dataset to generate accurate results.
For purposes of this demo, only the following data classifications have been configured:
US Social Security Number, Credit Card Information, Address, Phone, Email Addresses, Nationality, Religion, Country, City, Name, Company Name, Date, and URL.
Mage Discovery uses our patented pathway approach to find sensitive data in your data sources. Mage Pathways are a configurable sequence of techniques used to discover sensitive data, including data dictionary matching, pattern matching, pattern validations, data matching, and natural language processing. On the basis of the Pathway analysis, each potentially sensitive data location is assigned a Total Score that defines the degree of confidence of the finding. If the Total Score is greater than or equal to a pre-defined Threshold Score, then the data is deemed as “Sensitive”.
You are free to enter the data of your choice. Simply delete the existing pre-populated text, and enter your own custom data of maximum of 250 characters.
NOTE: The data that you enter is being stored in our engine. Please do not enter any actual data. Mage is not responsible for any sensitive data leakage arising due to this.
You can book a demo here. We will get in touch with you as soon as possible to provide a customized demo based on your requirements and use cases.
Overall Capablity Score
“iMask has met all of our expectations”
IT Domain Manager, Security & Risk Management
Firm Size: 30B+ USD
“I like this tool because with its secure anonymization technologies the performance and efficiency is not compromised. I like to use it because it works fast, takes a short time to run, and doesn’t use a lot of system resources. It cleans copies of our production data for testing, development, and other activities and fully eliminates unnecessary data. Our main motivation for using this solution was to achieve dynamic data masking and data protection and it never disappointed us and we are convinced that we made the right decision. iMask has perfectly met all of our expectations thus far that other tools are unable to do, we also look at a few different options, but iMask is the best.”
“Artificial intelligence to uncover data in the most complex of locations”
Project Manager, Product Management
Firm Size: 10B-30B USD
“Mentis helps the organization to uncover the hidden sensitive data locations within the organization with Sensitive Data Discovery module. This type of discovery is unique to the application. It uses the artificial intelligence to uncover data in the most complex of locations. It also has all compliance with popular data classifications by global privacy regulations includes the GDPR, CCPA, HIPAA. An overall recommended data masking application for the company.”
“Really helpful in protecting most sensitive data elements”
Decision Analyst, Data and Analytics
Firm Size: 1B-3B USD
“iScramble is a great data masking technique that provides flexibility to encrypt data to protect it from attacks and threats. It has various anonymization techniques that help to safeguard data in non-production environments. It can source data from various applications and third party like Big Data, Hive, Oracle. It helps protect data at enterprise and database layers and help secure data on any cloud platform. This provides a complete security solution with proper masking techniques to protect data from outside attacks. Overall, it is really helpful in protecting most sensitive data elements.”