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Financial Data Management Solutions
Ensure sensitive data remains protected against the largest security threat: internal resources. Financial services data management allows financial services companies to identify data that meets specific data security and retention requirements and automate how data is protected and managed throughout its entire lifecycle.
Retailers are taking measures to improve retail data security around consumer data, but more can be done. When retailer IT data centers make copies of their production database systems, the copies contain the same customer sensitive information as the production environment. Audit controls and data security policies need to be extended to the non-production systems to ensure customer data is safe at all stages of the application development lifecycle.
Data masking is a proven strategy to obscure specific fields that identify an individual, potentially exposing customers or employees to identity theft or other forms of privacy invasion. Utilizing oracle data masking to scramble, encrypt, shuffle or otherwise mask names, addresses, credit card numbers, salaries, or social security numbers; privacy is ensured and relational integrity is maintained.
Manage test data is a strategy for organizations to manage their test and development processes to meet application development and testing requirements, streamline cloning processes and secure data so organizations are equipped to deliver the clones needed to meet upgrade and patch cycles and maintain data security.
Health data management solutions enable centralized management of data classification and security policies. At the core of the EDMS is the Enterprise Metadata Manager, which manages multiple applications and data types across all hardware platforms through a unified policy manager.
Organizations can create and deploy consistent policies for managing, securing and storing data from a single console with the help of application archiving. The result is improved application performance and availability through smaller production database sizes, shorter backup and recovery times, reduced labor costs to maintain the production system and lower storage costs.
Preserve the essential metadata for future executions
With the JD Edwards database solution, organizations can create and deploy effective and consistent policies for managing, securing and storing data from a single console. The result is improved application performance and availability through smaller production database sizes, shorter backup and recovery times, reduced labor costs to maintain the production system and lower storage costs.
Application archiving allows companies to securely manage their archiving processes. There is no need for multiple installations of database tools or application metadata for each server environment. It helps organizations to Increase productivity among application and database users and reduce IT maintenance associated with large data sets.
Oracle archiving is the most widely deployed RDBMS system in the world supporting more than 300,000 installations. In addition to the growing number of implementations, current installed Oracle databases are experiencing incredible growth due to the amount of data enterprises are keeping online. Enterprise data management is a proven strategy to manage growth in custom and packaged applications running on Oracle databases by archiving data out of production infrastructure systems onto secondary, lower cost infrastructure while maintaining seamless data access through the native application or BI layer.
With health data management solutions organizations can create and deploy effective and consistent policies for managing, securing and storing data from a single console. The result is improved application performance and availability through smaller production database sizes, shorter backup and recovery times, reduced labor costs to maintain the production system and lower storage costs.
Enterprise class business applications require multiple copies be made to support test data management processes such as patch, test, QA, and training. Most companies make 6-8 full size clones for every production application, not only wasting storage and time in cloning but potentially exposing sensitive application data to the test environment. Data masking provides companies with a centralized solution to manage the test data management process for clone creation, productivity and data security.
