MySQL archive technology is used by some of the world’s largest and fastest-growing organizations to save time and money powering their high-volume Web sites, business-critical systems and commercial software. Enterprise data management is a proven strategy to manage growth in application and custom databases by reallocating data out of production systems into secondary, lower cost storage systems while maintaining seamless data access through the native application or BI layer.

Enterprise customers running Oracle E-Business Suite, JD Edwards, PeopleSoft, Siebel, Baan and custom applications depend on enterprise applications to run their businesses. Coupled with support for custom applications running on Oracle, IBM DB2, IBM Informix, Microsoft SQL, MySQL or other RDMS with JDBC driver support, data masking is the complete solution for all test data management needs.

With Secure Test and Development IT can automate the copying and securing of consumer and retail data security applications eliminating the risk of insider theft of consumer data. Oracle archiving helps organizations can create and deploy effective and consistent policies for managing, securing and storing data from a single policy console. The result is improved application performance and availability through smaller production database sizes, shorter backup and recovery times, reduced labor costs associated with production and test system maintenance and lower storage and infrastructure requirements and costs.

Organizations can mitigate the impact of data growth by running batch reports during downtimes, purchasing faster hardware or purge data from the application. None of these strategies fully address the reality of application growth coupled with the need for long term data retention. To maintain performance of JD Edwards database applications, while ensuring compliance, organizations must preserve the essential metadata for future executions.

Enterprise data management Suite’s modular and centralized architecture 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. JD Edwards database increases productivity among application users and application administrators.

Data masking is part of the Enterprise Data Management Suite that enables centralized management of data classification and security policies. At the core of the EDMS is the Enterprise Metadata Manager, which manages multiple applications metadata for all data types independent of the hardware platforms through a unified policy manager.

With oracle archiving, organizations can create and deploy effective and consistent policies for managing, securing and storing data from a single policy console. The result is improved application performance and availability through smaller production database sizes, shorter backup and recovery times, reduced labor costs associated with production and test system maintenance and lower storage and infrastructure requirements and costs.

Organizations can mitigate the impact of data growth by running batch reports during downtime, purchasing faster hardware or utilizing the purge functionality. None of these techniques fully address the reality of database growth and the need for long term data retention. To maintain performance of MySQL archive based applications while ensuring compliance, organizations must develop classification strategies for primary and secondary data sets.

Organizations can mitigate the impact of data growth by running batch reports during downtimes, purchasing faster hardware or purge data from the application. None of these strategies fully address the reality of application growth coupled with the need for long term data retention. To maintain performance of JD Edwards’s database applications, while ensuring compliance, organizations must automate the process of space reclamation in the production instance after archive & purge.

Organizations can minimize the impact of large data volumes by upgrading the server and storage environments or deleting data from the system. However, wholesale deletion of data from production does not comply with legal and regulatory requirements for long term data retention. To maintain performance of PeopleSoft archiving applications while ensuring compliance, organizations must ensure that data referential integrity is maintained.

Retailers are taking measures to improve 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 retail 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.

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.

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 Data Privacy Pack for Oracle E-Business Suite 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.

With application archiving organizations can create and deploy 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.

Data in production systems use highly available redundant Tier 1 storage systems. Enterprise data archiving is a proven strategy to relocate data to less expensive Tier 2 storage, reducing the need to continuously add to storage to production systems. Most experts conclude up to 80% of production data is no longer mission critical, using data archiving solutions reduces overall storage costs while maintaining access through the native application.

Information Lifecycle Management solutions are designed to help enterprises manage data growth by providing the tools classify, archive and migrate data to improve application performance and reduce administrative overhead and infrastructure costs.

Organizations can mitigate the impact of data growth by running batch reports during downtimes, creating additional partitions, purchasing faster hardware or utilizing purge routines within the application stack. But none of these techniques fully address the reality of application growth coupled with the need for long term data retention. To maintain performance of baan database while ensuring compliance, organizations must implementing an enterprise database management strategy to optimize infrastructure investments based on data classes.

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. With health data management solutions, organizations can create and deploy effective and consistent policies for managing, securing and storing data from a single console.

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.

With the sql server archiving, 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.

Financial services data management centralized metadata management approach allows organizations to install a single solution that leverages metadata from different applications. With integrated enterprise search, IT and end users can access and retrieve customer information that is either in the production system or is archived – whether it’s in a transactional system, email, ERP Report or in a Profitability Analysis of a BI system. But in conformance to privacy regulations, non-production data is secured, access controls are enforced and all activity is logged and audited.

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.

With the help of 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.

Organizations can mitigate the impact of data growth by running batch reports during downtimes, creating additional partitions, purchasing faster hardware or utilizing purge routines within the application stack. But none of these techniques fully address the reality of application growth coupled with the need for long term data retention. To maintain performance of baan database applications while ensuring compliance, organizations must understand the impact of growing application databases on productivity and resource costs.

Private and confidential customer and company data is often locked in production systems; credit card data, social security numbers, financial, HR data and customer lists are just a few of the fields that need to be stored securely. The Gramm-Leach-Bliley Act and HIPAA are just the latest in a long line of privacy regulations that will directly impact organizations that fail to secure their corporate data. Data masking enacts policy based archiving schemes where specific, sensitive data is masked according to pre-set algorithms before the database is released to the test environment.

In a 2005 survey conducted by retail data security, “Retail Data Security 2005 Benchmark Study,”it was found that retailers collecting and retaining customer specific purchase information are using this information for more than consumer-specific or one-to-one marketing.  Recent breaches of retailer database systems show that in many cases this personal information, such as POS and customer personal data, is not being used as intended and has become a target for theft.

Organizations can mitigate the impact of data growth by running batch reports during downtime, purchasing faster hardware or utilizing the purge functionality. None of these strategies fully address the reality of database growth and the need for long term data retention. To maintain performance of Microsoft SQL Server archiving based applications while ensuring compliance, organizations must understand the impact of growing application databases to productivity and resource costs.

As one of the original ERPs, there are thousands of customers’ worldwide running Baan modules for manufacturing, financial, project estimating and management and distribution. Over time, the load from millions of transactions added daily to the system weighs heavily on application servers impacting performance and report response rates. Further limitations on database table size make enterprise data management an important data management strategy for Baan database customers.

The solution for manage test data allows companies to securely manage test data and development processes with a single tool.  There is no need for multiple installations of database tools for each server environment. Test data management helps organizations to achieve faster cloning times through rapid application and database migration processes.

Complying with Legal and Regulatory Discovery is a growing imperative for all enterprises. With new amendments to the Federal Rules of Civil Procedure covering electronic documents, ignorance of the data is no longer a defensible strategy for not producing requested documents. Increasingly, organizations are looking to eDiscovery compliance solutions to save them from sanctions for non-compliance.

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.

With SQL server archiving 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.

With the 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.

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.

Enterprise data auditing ensures that you are alerted when unusual activity is occurring and keeping a secure and searchable audit log of database changes is critical to maintaining compliance with regulatory requirements as well as ensuring adherence to corporate information governance policies.

Information Lifecycle Management solutions are designed to help enterprises manage data growth by providing the tools classify, archive and migrate data to improve application performance and reduce administrative overhead and infrastructure costs.

Enterprise database archiving for PeopleSoft, organizations can implement policy based schemes for automatically migrating out of Tier 1 production stores into lower cost Tier 2 storage, ensuring application performance, faster back-up and recovery and lower total cost of storage. Test data management helps organizations to achieve faster cloning times through rapid application and database cloning processes.

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.

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.

It is a common fact that most database applications store company’s confidential details such as employee information, client information, company’s financial details etc. Most often these details need to be shared with developers and others while providing production support for upgrades, training, outsourcing etc. As a result there is a great risk of this data being used for unlawful activities. Data Masking helps in protecting data in less secure environments.

Data migration is a metadata based tool that allows companies to map metadata between applications and create conversion rules for faster and seamless data migration. It acts as an efficient project accelerator for migrations of any nature. Data management solutions provide organizations with the tools to mitigate risk, reduce storage costs, enforce consistent security policies, data auditing, and to retire legacy applications.

Information lifecycle management solutions are designed to help enterprises manage data growth by providing the tools to classify, archive and migrate data to improve application performance and reduce administrative overhead and infrastructure costs. Users of Oracle E-Business Suite, Baan, Oracle JD Edwards, Oracle PeopleSoft, Siebel and more are benefit a great deal by data archiving.

Database cloning creates a database template and restores or inserts only the transactions or modules needed. The Insert Method for database cloning allows IT organizations to create subsets much faster as only the data needed for the test is cloned, resulting in a faster cloning process and reduced storage requirement. Whichever subset method is used, referential integrity is maintained.

It is a common fact that most database applications store company’s confidential details such as employee information, client information, company’s financial details etc. Most often these details need to be shared with developers and others while providing production support for upgrades, training, outsourcing etc. As a result there is a great risk of this data being used for unlawful activities. Data Masking helps in protecting data in less secure environments.

Many organizations have tried alternative approaches to archiving, such as running batch reports during downtime, purchasing faster hardware or purging data by completely removing data from access. None of these strategies fully address the challenges of database growth and the need for long term data retention. Data archiving is an efficient solution to enhance application performance through smaller production database sizes, shorter backup and recovery times, reduced labor costs to maintain the production system and lower storage costs.

Every kind of storage is bound to overflow sometime or the other. It applies very much to software industries. Companies that have large storage data, which would also be needed for future trend analysis, reduce retrieval speed. Such companies can opt for data archiving solutions. Data archiving is built on the concept of preserving data through classification and storage, helps in improving throughput.

Data auditing provides enterprises with the tools to classify data based on its sensitivity, define policies at the database level that determine how that data should be managed, and automatically monitors and logs any changes to application data.

Information Lifecycle Management solutions are designed to help enterprises manage data growth by providing the tools classify, archive and migrate data to improve application performance and reduce administrative overhead and infrastructure costs. Enterprise data management offer streamline information management, security and automate data storage and retrieval to enable compliance and e-Discovery through long term data retention, data masking, database audit and enterprise search.

Data masking provides companies with a centralized solution to manage the test data management process for clone creation, productivity and data security. As a result, there is a great risk of this data being used for unlawful activities. Data masking helps in protecting data in less secure environments.

Data management solutions provide organizations with the tools to mitigate risk, reduce storage costs, enforce consistent security policies, data auditing, and to retire legacy applications. They also help in data archiving so as to support eDiscovery by creating a secure, controlled, and searchable archive for all data – application, email, documents and other files

Database cloning is a practical solution for the problem of protecting sensitive information that is shared while providing production support for upgrades, patching, testing etc. It has several options for reducing security risk. One such is that it creates clones of databases which would be smaller than the actual one by copying only the required data. It also has an option of creating a template that contains only the required information.

Archiving in peoplesoft enables management solutions for performance, security and information access. 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 retirement is a growing necessity for many organizations as they grow, merge or consolidate operations. The number of enterprise systems that IT departments support continues to grow. Strategic moves away from proprietary mainframe and applications systems coupled with efforts to reduce IT spending on existing infrastructure are bringing focus on application retirement as a way to fund new projects or make the existing IT budget go farther.

Creating data masking is a labor intensive and manual process where servers, applications and storage devices are configured for each new clone, an inefficient process for a routine data center activity. By automating the cloning and post-cloning processes, clones are created and configured faster and with fewer errors.

Most enterprise class business applications require multiple copies be made to support test data management processes such as patch, test, QA, etc. Hence 6-8 full size clones are prepared, thereby potentially exposing sensitive application data. To ensure sensitive data remains protected against the largest source of vulnerability, the internal threat; data management suites allow telecom operators to identify data that meets specific security and retention requirements and automate how the data is protected and managed throughout its entire lifecycle.

Data migration is a metadata based tool that allows companies to map metadata between applications and create conversion rules for faster and seamless data migration. It acts as an efficient project accelerator for migrations of any nature.

Data management solutions provide organizations with the tools to mitigate risk, reduce storage costs, enforce consistent security policies, data auditing, and to retire legacy applications. They also help in database archiving so as to support eDiscovery by creating a secure, controlled, and searchable archive for all data – application, email, documents and other files.

It is a common fact that most database applications store company’s confidential details such as employee information, client information, company’s financial details etc. Most often these details need to be shared with developers and others while providing production support for upgrades, training, outsourcing etc. As a result there is a great risk of this data being used for unlawful activities. Data masking helps in protecting data in less secure environments.

Often many applications, which were yielding good results for the companies, become outmoded when organizations grow, merge or strengthen their operations; since not much attention is paid to maintain these applications. Application retirement is the best solution for doing away with disused applications as they expend a lot of resources, storage etc while benefiting the organization very little.

Data migration is a metadata based tool that allows companies to map metadata between applications and create conversion rules for faster and seamless data migration. It acts as an efficient project accelerator for migrations of any nature.

Data subsettting decreases storage requirements and increases IT productivity by reducing the overall size of the final database clone. Database Administrators and Developers can select sets of transactions or application modules and remove the data through deletion or truncation, or use the more efficient Insert Method for database cloning.

Archiving in peoplesoft enables management solutions for performance, security and information access. 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.

Data masking provides companies with a centralized solution to manage the test data management process for clone creation, productivity and data security. As a result, there is a great risk of this data being used for unlawful activities. Data masking helps in protecting data in less secure environments.

Data management solutions provide organizations with the tools to mitigate risk, reduce storage costs, enforce consistent security policies, data auditing, and to retire legacy applications. They also help in data archiving so as to support eDiscovery by creating a secure, controlled, and searchable archive for all data – application, email, documents and other files.

Information Lifecycle Management solutions are designed to help enterprises manage data growth by providing the tools classify, archive and migrate data to improve application performance and reduce administrative overhead and infrastructure costs.

Database cloning creates a database template and restores or inserts only the transactions or modules needed. The Insert Method for database cloning allows IT organizations to create subsets much faster as only the data needed for the test is cloned, resulting in a faster cloning process and reduced storage requirement. Whichever subset method is used, referential integrity is maintained. Database cloning is therefore very helpful in protecting data in less secure environments.

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.

Data management solutions provide organizations with the tools to mitigate risk, reduce storage costs, enforce consistent security policies, database auditing, and to retire legacy applications. They also help in data archiving so as to support eDiscovery by creating a secure, controlled, and searchable archive for all data – application, email, documents and other files.

With archiving in peoplesoft, organizations can implement policy based schemes for automatically migrating out of Tier 1 production stores into lower cost Tier 2 storage, ensuring application performance, faster back-up and recovery and lower total cost of storage.

Database cloning creates a database template and restores or inserts only the transactions or modules needed. The Insert Method for database cloning allows IT organizations to create subsets much faster as only the data needed for the test is cloned, resulting in a faster cloning process and reduced storage requirement. Whichever subset method is used, referential integrity is maintained.

Application retirement is a viable strategy for eliminating redundant legacy applications, thereby improving operational efficiency and reducing costs. By reducing the number of applications within the IT infrastructure, DBAs can concentrate on maintaining critical business applications with the highest value to the organization, instead of compiling data from disparate sources. Enterprise data management application provides companies with a centralized solution to manage the test data management process for clone creation, productivity and data security.

Database cloning creates a database template and restores or inserts only the transactions or modules needed. The Insert Method for database cloning allows IT organizations to create subsets much faster as only the data needed for the test is cloned, resulting in a faster cloning process and reduced storage requirement. Whichever subset method is used, referential integrity is maintained. Database cloning is therefore very helpful in protecting data in less secure environments.

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.

Most enterprise class business applications require multiple copies be made to support test data management processes such as patch, test, QA, etc. Hence 6-8 full size clones are prepared, thereby potentially exposing sensitive application data. To ensure sensitive data remains protected against the largest source of vulnerability, the internal threat; data management suites allow telecom operators to identify data that meets specific security and retention requirements and automate how the data is protected and managed throughout its entire lifecycle.

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.

Data management solutions provide organizations with the tools to mitigate risk, reduce storage costs, enforce consistent security policies, data auditing, and to retire legacy applications. They also help in data archiving so as to support eDiscovery by creating a secure, controlled, and searchable archive for all data – application, email, documents and other files

Data that has been relocated after classification is protected from redundant searches or data addition. This helps in maintaining integrity and reduces the strain on database servers. When a quarterly or yearly trend analysis is performed it allows for convenient data purging also. Automation of archiving and purging is available as data archiving solutions. They can be used by multiple projects at the same time and data retrieval is very convenient.

Too much data can slow application and reporting performance and tax IT resources. Utilizing data management tools to actively manage the growth of application data is the key to managing data for its value to the organization. Enterprise Data Archiving solution is part of the Enterprise data management Suite that enables centralized management of data classification and security policies.

Data masking provides companies with a centralized solution to manage the test data management process for clone creation, productivity and data security. As a result, there is a great risk of this data being used for unlawful activities. Data masking helps in protecting data in less secure environments.

Data archiving solutions helps in reinstating the application’s performance to 50% by archiving inactive data. It enables in improving and reducing storage and IT costs. Users of Oracle E-Business Suite, Baan, Oracle JD Edwards, Oracle PeopleSoft, Siebel and more benefit a great deal by data archiving solutions.

Data auditing provides enterprises with the tools to classify data based on its sensitivity, define policies at the database level that determine how that data should be managed, and automatically monitors and logs any changes to application data.

Every kind of storage is bound to overflow sometime or the other; it also applies to software industries. Companies that have large storage data, which would also be needed for future trend analysis, reduce retrieval speed. Such companies can opt for data archiving solutions. Data archiving is built on the concept of preserving data through classification and storage, helps in improving throughput.

Securing sensitive data in database environments is only one piece of the compliance puzzle. Ensuring that you are alerted when unusual activity is occurring and keeping a secure and searchable data auditing log of database changes is critical to maintaining compliance with regulatory requirements as well as ensuring adherence to corporate information governance policies

Enterprise data management provides the data management framework for all enterprise applications and databases including database cloning, subsetting and data masking to allow organizations to protect data in non-production environments while reducing infrastructure costs and improving development cycles.

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. Database masking provides companies with a centralized solution to manage the test data management process for clone creation, productivity and data security.

Data auditing provides enterprises with the tools to classify data based on its sensitivity, define policies at the database level that determine how that data should be managed, and automatically monitors and logs any changes to application data.

Application retirement is a viable strategy for eliminating redundant legacy applications, thereby improving operational efficiency and reducing costs. By reducing the number of applications within the IT infrastructure, DBAs can concentrate on maintaining critical business applications with the highest value to the organization, instead of compiling data from disparate sources. Enterprise data management application provides companies with a centralized solution to manage the test data management process for clone creation, productivity and data security.