High Technology

Organizations can mitigate the impact of data growth by running batch reports during downtimes, creating additional partitions, purchasing faster hardware or utilizing the purge functionality within the application stack. None of these techniques fully address the reality of application growth coupled with the need for long term data retention. It’s important to maintain performance of Oracle Applications while ensuring compliance.

With E-Business Suite 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.

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.

Enterprise Data Management Suite's modular and centralized architecture allows companies to securely manage their data management processes. Enterprise data management solutions are the binding layer for the organization that provides consistent interpretation of the business data and help create & maintain the data. This helps organizations to increase productivity among application users, reduce IT maintenance associated with large data volumes, reduce high cost infrastructure in production systems and also implement a comprehensive data management strategy.

Enterprise data management provides the solution for managing your data holistically accounting for compliance, cost and security. With quantifiable improvement across the enterprise, gain risk reduction, improved performance, lower costs and improved operational efficiencies.

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.

With the Data Archiving solution for Oracle, 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.

Most experts conclude up to 80% of production data is no longer mission critical, using database archiving reduces overall storage costs while maintaining access through the native application. The result is a highly stable production environment and streamlined performance that leads to higher productivity and a positive impact to your organization's bottom line.

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 helps organizations to reduce cost while maintaining access to the data either through the creation of a common data store or by migrating data into an existing enterprise application. By utilizing Application retirement organizations can improve operational efficiency, reduce costs and ensure that data retention requirements are met.

Application retirement reduces 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.

Relational databases handle mission-critical data in industries. These databases are known to grow at the rate of 125% annually. To overcome this challenge, data is alternatively stored in different data management systems. Response time for live transactions are the worst affected due to such high accumulation of data. Processing threads start overlapping when the user tries to refresh the screen constantly.

Database archiving is a proven strategy that will archive rarely used data and provide easy access to data on demand. Basically, data is most valuable when it is created. As data ages, its relative value comes down. Such data can be archived to improve real time transactions. Archived data, business context data and metadata are grouped into one archive file and stored on convenient and cost-effective storage mediums. Archived data can be easily accessed, researched and restored whenever needed.

Large amount of real time transactions and increased access rates have resulted in storage overflows occurring often. The risk of allowing a database to overflow will create havoc on live systems that are dependent on it. The database becomes vulnerable to power surges that can ruin vital data. The time taken for backup and restore will also increase multifold if databases are not archived properly.

Database archiving is an area that has always been of prime importance to administrators. Most database administrators will agree that archiving solutions have improved throughput time and also left them with a lot of free space. The decision to archive depends on how fast live data gets accumulated and also when we will need the archived data again for analysis.

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 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. Data masking helps in protecting data in less secure environments.

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 provides companies with a centralized solution to manage the test data management process for clone creation, productivity and data security. Data masking helps in protecting data in less secure environments. Secure test and development provides companies with a centralized solution to manage the test data management process for data masking.

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.

Test data management processes are critical to maintain applications and databases, but creating the necessary clones is a labor intensive activity for any IT department. Multiple clones must be configured and managed across applications, databases, servers, and storage devices, all the while exposing sensitive customer data to potential leaks. With identity theft being a growing concern among consumers, regulators and law makers; a strategic approach to test data management is needed.

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.

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.