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Implement IBM Optim Data Growth Solution to Control Data Growth
Organizations are today increasingly depending on technology for their day to day functioning. This has led to
manifold increase in data that in turn is threatening application performance and stretching the IT budgets.
Mismanaged data growth can impact the application performance and strain financial and technical resources.
Apart from that it can also impact the completion of business-critical processes on time.
According to a new survey by research firm Gartner Inc., data growth is the biggest data center hardware
infrastructure challenge for large enterprises. Compliance, data retention requirements, and the rising cost of
hardware infrastructure are forcing businesses to explore alternatives to traditional storage.
To effectively meet these challenges organization need to manage data growth, by proactively managing the
enterprise application data while increasing its value. Some of the latest storage methodologies focused on the
efficient management and effective utilization of data include, data de-duplication, automatic tiering of storage,
big data analytics and cloud storage.
Implementing IBM Optim Data Growth Solution can help control the unmanaged data growth at the source, by
proactively managing the enterprise application data while ensuring application integrity. The solution lessens the
impact of data growth by archiving historical databases or compressed files and save them on a hardware device.
IBM Optim provides pre-defined built-in templates that define the most common business objects within leading
ERP and CRM application products, including Oracle JDE EnterpriseOne, Oracle E-Business Suite, Oracle PeopleSoft,
SAP, and Siebel that can be customized as per the clients requirements.
Thus by archiving historical data, only the current data is available in the production environment, therefore
application performance improves dramatically. Being scalable and consistent Optim Data Growth solutions
include comprehensive capabilities for managing enterprise application data across applications, databases,
operating systems, and hardware platforms.
IBM Optim Data Growth Solution helps:
 Archiving historical data from applications and systems freeing valuable resources, thereby reducing
hardware, storage and maintenance costs.
 Maintain optimal application performance levels.
 Archive, manage and retain application data according to the business and compliance policies.
 Respond quickly to audit and discovery requests.
 Centrally manage and control archiving across applications, databases, operating systems and platforms.
 Streamline the production database to reduce processing overhead.
 Lower IT costs, and support data-retention compliance programs.
 Provide universal access to archived information.
Thus implementing a proven IBM Optim data growth solution can help enterprises take control of their mission-
critical data throughout its entire lifecycle while providing universal access to current and archived data.

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Implement IBM Optim Data Growth Solution to Control Data Growth

  • 1. Implement IBM Optim Data Growth Solution to Control Data Growth Organizations are today increasingly depending on technology for their day to day functioning. This has led to manifold increase in data that in turn is threatening application performance and stretching the IT budgets. Mismanaged data growth can impact the application performance and strain financial and technical resources. Apart from that it can also impact the completion of business-critical processes on time. According to a new survey by research firm Gartner Inc., data growth is the biggest data center hardware infrastructure challenge for large enterprises. Compliance, data retention requirements, and the rising cost of hardware infrastructure are forcing businesses to explore alternatives to traditional storage. To effectively meet these challenges organization need to manage data growth, by proactively managing the enterprise application data while increasing its value. Some of the latest storage methodologies focused on the efficient management and effective utilization of data include, data de-duplication, automatic tiering of storage, big data analytics and cloud storage. Implementing IBM Optim Data Growth Solution can help control the unmanaged data growth at the source, by proactively managing the enterprise application data while ensuring application integrity. The solution lessens the impact of data growth by archiving historical databases or compressed files and save them on a hardware device. IBM Optim provides pre-defined built-in templates that define the most common business objects within leading ERP and CRM application products, including Oracle JDE EnterpriseOne, Oracle E-Business Suite, Oracle PeopleSoft, SAP, and Siebel that can be customized as per the clients requirements. Thus by archiving historical data, only the current data is available in the production environment, therefore application performance improves dramatically. Being scalable and consistent Optim Data Growth solutions include comprehensive capabilities for managing enterprise application data across applications, databases, operating systems, and hardware platforms. IBM Optim Data Growth Solution helps:  Archiving historical data from applications and systems freeing valuable resources, thereby reducing hardware, storage and maintenance costs.  Maintain optimal application performance levels.  Archive, manage and retain application data according to the business and compliance policies.  Respond quickly to audit and discovery requests.  Centrally manage and control archiving across applications, databases, operating systems and platforms.  Streamline the production database to reduce processing overhead.  Lower IT costs, and support data-retention compliance programs.  Provide universal access to archived information. Thus implementing a proven IBM Optim data growth solution can help enterprises take control of their mission- critical data throughout its entire lifecycle while providing universal access to current and archived data.