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.

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.

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.

Application retirement helps organizations to reduce cost while maintaining access to the data either through the creation of a common data store or by data migration into an existing enterprise application. This helps in operational efficiency and reducing cost.

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.

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.

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.

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.

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 archiving solutions enables in improving and reducing storage and IT costs. Enterprise database archiving restores application performance by up to 50% by relocating inactive data from the production database to a secure online data archive.

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 archiving in PeopleSoft while ensuring compliance, organizations must assess data volume for each given modules or the sum total of the PeopleSoft Application database.

Test data management 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.

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.

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.

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.

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. It helps in helps in providing retirement to applications that are on the verge of it. It reduces the number of applications within the organ data auditing.

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.

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.

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.

Database archiving solutions automates the archive and purge process by offloading underutilized data from the production environment, ensuring good operational performance during heavy load times such as quarter end. By deploying Enterprise Data Archiving, organizations maintain performance and can reduce the IT burden of large data sets.

Application Sunsetting and Migration solution is a metadata based tool that allows companies to map metadata between applications and create conversion rules for faster and seamless data migration .

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.

Data archiving restores application performance up to 50% by relocating inactive data from your production database to a secure online data archive. Database Archiving automates the archive and purge process by offloading underutilized data from the production

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.

Application retirement allows organizations to implement data migration projects across applications: Legacy, Mainframe, BaaN, JDE, PeopleSoft, Siebel Oracle, SAP, etc. while allowing changes to chart of accounts, organization structure, costing methods, etc.

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.

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.

Private and confidential 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 secured. 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.

Too much data can slow down application performance and 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 sute that enables centralized management of data classification and security policies.

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.