Bringing the power of NextLabs DAE’s policy-based data segregation and data privacy to big data applications
NextLabs announced the expansion of its Data Access Enforcer (DAE) product line to cover a broader range of application and database, addressing the growing need to protect and safeguard business critical information in big data applications. DAE helps NextLabs customers control access to data through flexible policies that are dynamically enforced at runtime, allowing those policies to be enforced regardless of how the data is being accessed.
All organizations face challenges such as compliance with data protection regulations, and the cost of detecting and preventing violations of data access policies. NextLabs helps overcome these challenges with DAE, which uses centrally managed policies to determine in real-time who, what, when, where, and why, and how criteria to mask and filter data based on dynamic attributes. DAE prevents unauthorized access to sensitive data through fine-grained data-level security controls, protecting data and addressing compliance requirements all at once. Furthermore, DAE can track, report, and alert on risky access activity critical fields and records through its centralized dashboards, reports, and automated monitoring facilities. Data access requests, whether allowed or blocked, across the application are tracked and logged centrally, simplifying compliance management and audits.
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Building on NextLabs’ expertise in application integration, DAE has been certified to support the following big data applications out-of-the-box:
- DAE for Database: SAP HANA, Oracle, SQL Server, DB2, PostgreSQL, MySQL & MariaDB
- DAE for Cloud DB: Azure SQL, AWS RDS, AWS Aurora, AWS Redshift, Google Cloud SQL, Google BigQuery
- DAE for BI: PowerBI, Azure Data Studio, SQL Server Management Studio (SSMS), HANA Studio, Crystal Reports, Tableau, Oracle SQL
- DAE for Windows: Windows-based application
- DAE for ODBC and JDBC: ODBC and JDBC based application
Some of the notable capabilities of DAE are field-level data masking and record level data filtering. Both features ensure only those with authorization can view the fields and/or records they have been granted access to. This is powered by attribute-based security, which allows access to data based on policies that examine attributes of the data being accessed, the context of the request, and user identity. DAE performs policy check in real-time to partition data and ensure data privacy based on fine-grained conditions specified in the policies. These policies are centrally managed with activity logs that can be audited across all organization’s applications to simplify administration. Additionally, DAE supports policies to control Data Manipulation Language (DML) actions, such as create, update, insert, delete, and execute.
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Advantages of NextLabs DAE include:
- Support any database and any applications to offer a wide range of application coverage – earning DAE the quickest to deploy and easiest to use data protection and data privacy solution
- Support field-level dynamic data masking and encryption, record-level filtering and segregation, and attribute-based access control of database operations all within a single product.
- Powered by industry leading dynamic authorization and attribute-based Policy engine to enforce policies in real-time without code – ease of management, significantly lower cost of change management, and rapid time to value to offer enterprises ability to keep up with the rapidly evolving data security needs.
- DAE tracks and stores user activities and data access across applications in a central audit server simplifying compliance management. Analytics for user behavior and access patterns are provided via dashboards, reports, and automated monitoring facilities.
“Our mission for DAE is to be the easiest to deployment and fastest time to value product in the market, we are one step closer with this new release;” said Keng Lim, CEO and Founder of NextLabs. “This latest release of DAE allows our customers to easily apply and maintain consistent data security policies to safeguard data across all of their big data applications within days.”
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