Data discovery is the collection and analysis of data from various sources to gain insight from hidden patterns and trends. It is the first step in fully harnessing an organization's data to inform critical business decisions.
It is a business user oriented process for detecting patterns and outliers by visually navigating data or applying guided advanced analytics. Discovery is an iterative process that does not require extensive upfront model creation.
Data masking represents a simple concept, but it is technically challenging to execute.
Data masking (also known as data scrambling and data anonymization) is the process of replacing sensitive information copied from production databases to test non-production databases with realistic, but scrubbed, data based on masking rules.
Helps customers improve security, accelerate compliance, and reduce IT costs by making copies of production data for non-production environments and by easily discarding unnecessary data.
Changing data in a production environment is not feasible and almost impossible, so we need to mask served data to clients on-the-fly, dynamically.
Our solution serves data in a secure way dynamicly and it can notify or block unauthorized access with minimum overhead and without an agent installation required to either side.
Discover hidden instances of private data so they can be fully protected.
Leverage masking services to mask data on demand, anywhere at any time.
Agile and flexible, so users can find answers to their questions ad hoc without relying on the help of IT to set up a complex environment prior working with the data.
Allows easy handling of a high volume and variety of data as the large amount and increasing variety of data require more efficient and user-oriented methods of presentation to make sense of them.
