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Archive for the ‘database management’ Category

Actively manage transactional data stores to optimize application performance

Posted by davidstech on November 27, 2009

Oracle 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.

All sectors of financial services data management are globalizing. This is particularly true for developing countries. A bank not only has to conform to local regulations of its home country, but also of the other countries in which it has its operations. And to compound it all, there are even international guidelines like Basel II – an accord for capital adequacy that banks must maintain across different countries for international lending.

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.

Information Lifecycle Management (ILM) ensures that under-utilized data is moved out of expensive Tier 1 storage technologies into less expensive Tier 2 or Tier 3 solutions, freeing up IT resources from creating unnecessary back-ups and clones for test and development while ensuring data access is maintained in the original application context.

Archive MySQL 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.

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Monitor and track access to Consumer Sensitive Data

Posted by davidstech on November 27, 2009

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.

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Implements a comprehensive data management strategy to improve operational efficiencies

Posted by davidstech on November 24, 2009

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 database archiving reduces overall storage costs while maintaining access through the native application.

Test data management 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 cloning processes.

Data management suite helps organizations to create and deploy consistent policies for classifying, tiering and managing archive data from a single archive policy console. The result is improved application performance and availability through smaller production database sizes, shorter backup and recovery windows, reduced labor costs and lower infrastructure requirements.

To maintain performance of archiving MySQL based applications while ensuring compliance, organizations must actively manage transactional data stores to optimize application performance and understand the impact of growing application databases to productivity and resource costs. Information Lifecycle Management (ILM) is a data management practice that manages data from inception to storage to eventual disposal for its cost, use and value to the organization.

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Increase productivity among application and database users

Posted by davidstech on November 24, 2009

Organizations can minimize the impact of large data volumes by upgrading the server and storage environments or deleting data from the system. With the help of peoplesoft archiving 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.

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 archiving solution restores application performance up to 50% by relocating inactive data from your production database to a secure online data archive. JD Edwards database offers organizations the ability to Simultaneously access archive data along with current activity using the JD Edwards application to respond to inquiries, run reports and make decisions.

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. Oracle archiving 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.

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EDMS for Compliance and eDiscovery

Posted by davidstech on November 13, 2009

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.

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Data management solutions for challenges in financial services

Posted by davidstech on November 13, 2009

All sectors of financial services are globalizing. This is particularly true for developing countries. A bank not only has to conform to local regulations of its home country, but also of the other countries in which it has its operations. Financial services data management allows 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. Enterprise Data Management is a best practice that can be implemented in a retailer’s data center to mitigate risk associated with managing consumer sensitive data.

Oracle 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. 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.

Baan database 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.

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Develop classification strategies for primary and secondary data sets

Posted by davidstech on November 9, 2009

Enterprise Applications and Databases are designed and architected to efficiently record and store the transactional history of the organization. By using application archiving organizations can improve 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 is the life blood of any organization, but too much data can slow application and reporting performance and tax IT resources. Utilizing database archiving to actively manage the growth of application data is key to managing data for its value to the organization.

Enterprise data management supports all JD Edwards modules. It can be integrated with any module in JD Edwards database through EDMS objects that define the most common JD Edwards business logic.

Enterprise Data Management Suite’s modular and centralized architecture allows companies to securely manage their data management processes. This helps organizations to Increase productivity among application users and reduce IT maintenance associated with large data volumes.

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. To maintain performance of oracle archiving based applications while complying with data retention needs, organizations must develop classification strategies for primary and secondary data sets.

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Reduce storage footprint of Test and Development

Posted by davidstech on November 9, 2009

Securing sensitive data in database environments is only one piece of the compliance puzzle. Data Auditor 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.

With peoplesoft archiving, 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. Most experts conclude up to 80% of production data is no longer mission critical, using enterprise data archiving reduces overall storage costs while maintaining access through the native application.

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.

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 a growing concern among consumers, regulators and law makers, a strategic approach to manage test data is needed.

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 archive MySQL based applications while ensuring compliance, organizations must Develop classification strategies for primary and secondary data sets.

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Implement a comprehensive data management strategy

Posted by davidstech on November 3, 2009

Data 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. Application archiving helps organizations to implement a comprehensive data management strategy. Implementing information lifecycle management is the best practices with EDMS, organizations can Secure data throughout the entire data lifecycle.

Data Management Suite’s modular and centralized architecture allows companies to securely manage their data management processes. This helps organizations reduce high cost infrastructure in production systems.

With the help of baan database 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.

EDMS supports all JD Edwards modules. It can be integrated with any module in JD Edwards through EDMS objects that define the most common JD Edwards business logic.

In the US, Data Centers release 44 million metric tons of CO2 into the air annually, consuming 61 billion kwH and costing $4.5 billion. Going green in the data center is about reducing power, reducing CO2 and driving energy cost out of the IT infrastructure. A smart data management policy is critical to reducing the cost in power and cooling while fulfilling the needs of data retention.

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Retail Data Management Solutions

Posted by davidstech on November 3, 2009

By implementing retail data security helps in improving Customer Satisfaction and Sales. Online transaction processing is faster and availability to promise queries are quicker resulting in higher customer satisfaction and higher purchase probability. Enterprise Data Management is a best practice that can be implemented in a retailer’s data center to mitigate risk associated with managing consumer sensitive data.

Database Archiving for health data management solutions 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 and data types across all hardware platforms through a unified policy manager.

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. This solution allow enterprises to deploy tiered storage with enterprise data archiving, and significantly reduce the size of the entire application environment with the data masking solution while ensuring sensitive data remains secure.

Test data management 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.

Organizations face a critical challenge; they don’t know what data they have, how many copies of data exist, what data is in production databases and which are in non-production such as Test and Development, QA, etc. With ediscovery compliance, companies can understand all their Enterprise Data (Applications, Email & Documents) for eDisovery.

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