Informatica shares nine steps to successful information lifecycle management
June 7, 2011 - Informatica Corporation (NASDAQ: INFA), the world’s number one independent provider of data integration software, shares nine steps to successful information lifecycle management.
Keith Jaslow, principal technical consultant, Informatica, said, “The size of production databases is growing exponentially. Increasing regulation also means that more frequently organisations must retain their data indefinitely.
“As data volumes grow, the time and effort necessary for end users and database administrators to perform essential tasks on production systems increases. Data entry responsiveness declines and reports take longer to run, database backups are slower and essential administrative tasks such as upgrading applications or applying software patches become more time consuming.
“Information lifecycle management (ILM) is growing in popularity as a means of better aligning the business value of data with the most appropriate and cost-effective IT infrastructure, from the time information is added to the database until it can be destroyed. Data archiving provides a highly effective application ILM solution.”
The following nine archiving best practices ensure optimal management of data during its life cycle:
1. Understand data growth trends. As organisations grow, adjust business strategies, or undergo mergers and acquisitions, data volumes expand and storage requirements change.
To plan an effective archiving strategy organisations need visibility into the resulting data growth trends.
A best-practice archiving solution will include tools that let organisations evaluate where data is currently located as well as which applications and tables are responsible for the most data growth. Organisations must perform this evaluation on an ongoing basis to continually adjust their archiving strategy as necessary and maximise return on investment for its archiving efforts.
2. Determine success criteria. To define the most appropriate archiving strategy, organisations must determine their objectives. Some will emphasise performance, others space savings and others will specifically need to meet regulatory requirements.
Examples of archiving goals may include:- improve response time for on-line queries to ensure timely access to current production data- shorten batch processing windows to complete before the start of routine business hours- reduce time required for routine database maintenance, backup, and disaster recovery processes- maximise the use of current storage and processing capacity and defer the cost of hardware and storage upgrades- meet regulatory requirements by purging selected data from the production environment and providing secure read-only access to it- archive before upgrade to reduce the outage window required by the upgrade.
3. Establish a data retention policy. Once an organisation understands its environment and success criteria, it must classify the different types of data it wishes to archive.
Organisations can then create data retention policies that specify criteria for retaining and archiving each classification of data. These archiving policies must take into account data access patterns and the need to perform transactions on data.
Data retention policies must maintain consistency across modules, where appropriate. The archiving solution must be flexible enough to accommodate separate retention policies for different data classifications and let them modify these policies as requirements change.
4. Select a solution with pre-packaged business rules. The number one concern for organisations implementing a data growth management solution is to ensure the integrity of the business application. The process of archiving must take into account the business context of the data as well as relationships between different types of data.
Data management is rendered even more complex because transactional dependencies are often defined at the application layer rather than the database layer. This means that a data growth management tool cannot simply reverse engineer the data model at the time of implementation. Any auto-discovery process is bound to be insufficient because it will miss all of the relationships embedded in the application. These rules and relationships can become quite complicated in large prepackaged products, which may have tens of thousands of database objects and a large number of integrated modules.
Successfully archiving data in these solutions requires an in-depth understanding of how the application defines a database and the set of rules that operate against the data. A best-practice archiving solution includes pre-packaged business rules that incorporate an in-depth understanding of the way a particular enterprise solution stores and structures data.
5. Extend the business rules. Since not every enterprise resource planning (ERP) or customer relationship management (CRM) user runs all of its applications the way the vendor envisions, an archiving solution must let organisations modify and customise the prepackaged archiving business rules.
A best-practice solution should include a graphical developer toolkit that resembles standard database design tools and makes it easy to modify the prepackaged archiving rules.
6. Test the business rules. Once the organisation has developed business rules, it needs to test them by simulating what will happen when data is actually archived. A best-practice solution provides simulation reporting that shows database administrators exactly how many records a given archiving policy will remove from the production system and how many will remain because the ERP classifies them as an exception. Using simulation reporting, database administrators can iteratively adjust their archiving policy to meet their archiving objectives.
7. Create user access policies. Many organisations will want to control which users access historical data in the archive and which data access method, screen, report, or query, they can use to access the data.
A best-practice solution will let an organisation configure user access policies that specify which users are authorised to access historical data and which reports they are able to use.
8. Ensure restoration. A restoration capability functions as an insurance policy should specific transactions need to be modified after archiving. Only by having such a restoration capability can most organisations convince business users that it is safe to implement an archiving solution.
9. Follow a time-tested methodology. No organisation wants its implementation, no matter how customised, to be on the bleeding edge of experimentation. It wants to be sure that the vendor it works with has seen and addressed the types of challenges likely to arise during an implementation.
Organisations should choose a vendor that has developed an implementation methodology for complex archiving solutions that meets the outlined business objectives and has been successfully applied over a large number of implementations.
Jaslow said, “Organisations that succeed in implementing a best-practices archiving solution will improve application performance by eliminating unnecessary data from their production database, reducing total cost of ownership by lowering hardware costs and maintaining regulatory compliance.”
-ENDS-
About Informatica
Informatica Corporation (NASDAQ: INFA) is the world's number one independent provider of data integration software. Organisations around the world rely on Informatica for maximising return on data to drive their top business imperatives. Worldwide, over 4,630 enterprises depend on Informatica to fully leverage their information assets residing on-premise, in the Cloud and across
Keith Jaslow, principal technical consultant, Informatica, said, “The size of production databases is growing exponentially. Increasing regulation also means that more frequently organisations must retain their data indefinitely.
“As data volumes grow, the time and effort necessary for end users and database administrators to perform essential tasks on production systems increases. Data entry responsiveness declines and reports take longer to run, database backups are slower and essential administrative tasks such as upgrading applications or applying software patches become more time consuming.
“Information lifecycle management (ILM) is growing in popularity as a means of better aligning the business value of data with the most appropriate and cost-effective IT infrastructure, from the time information is added to the database until it can be destroyed. Data archiving provides a highly effective application ILM solution.”
The following nine archiving best practices ensure optimal management of data during its life cycle:
1. Understand data growth trends. As organisations grow, adjust business strategies, or undergo mergers and acquisitions, data volumes expand and storage requirements change.
To plan an effective archiving strategy organisations need visibility into the resulting data growth trends.
A best-practice archiving solution will include tools that let organisations evaluate where data is currently located as well as which applications and tables are responsible for the most data growth. Organisations must perform this evaluation on an ongoing basis to continually adjust their archiving strategy as necessary and maximise return on investment for its archiving efforts.
2. Determine success criteria. To define the most appropriate archiving strategy, organisations must determine their objectives. Some will emphasise performance, others space savings and others will specifically need to meet regulatory requirements.
Examples of archiving goals may include:- improve response time for on-line queries to ensure timely access to current production data- shorten batch processing windows to complete before the start of routine business hours- reduce time required for routine database maintenance, backup, and disaster recovery processes- maximise the use of current storage and processing capacity and defer the cost of hardware and storage upgrades- meet regulatory requirements by purging selected data from the production environment and providing secure read-only access to it- archive before upgrade to reduce the outage window required by the upgrade.
3. Establish a data retention policy. Once an organisation understands its environment and success criteria, it must classify the different types of data it wishes to archive.
Organisations can then create data retention policies that specify criteria for retaining and archiving each classification of data. These archiving policies must take into account data access patterns and the need to perform transactions on data.
Data retention policies must maintain consistency across modules, where appropriate. The archiving solution must be flexible enough to accommodate separate retention policies for different data classifications and let them modify these policies as requirements change.
4. Select a solution with pre-packaged business rules. The number one concern for organisations implementing a data growth management solution is to ensure the integrity of the business application. The process of archiving must take into account the business context of the data as well as relationships between different types of data.
Data management is rendered even more complex because transactional dependencies are often defined at the application layer rather than the database layer. This means that a data growth management tool cannot simply reverse engineer the data model at the time of implementation. Any auto-discovery process is bound to be insufficient because it will miss all of the relationships embedded in the application. These rules and relationships can become quite complicated in large prepackaged products, which may have tens of thousands of database objects and a large number of integrated modules.
Successfully archiving data in these solutions requires an in-depth understanding of how the application defines a database and the set of rules that operate against the data. A best-practice archiving solution includes pre-packaged business rules that incorporate an in-depth understanding of the way a particular enterprise solution stores and structures data.
5. Extend the business rules. Since not every enterprise resource planning (ERP) or customer relationship management (CRM) user runs all of its applications the way the vendor envisions, an archiving solution must let organisations modify and customise the prepackaged archiving business rules.
A best-practice solution should include a graphical developer toolkit that resembles standard database design tools and makes it easy to modify the prepackaged archiving rules.
6. Test the business rules. Once the organisation has developed business rules, it needs to test them by simulating what will happen when data is actually archived. A best-practice solution provides simulation reporting that shows database administrators exactly how many records a given archiving policy will remove from the production system and how many will remain because the ERP classifies them as an exception. Using simulation reporting, database administrators can iteratively adjust their archiving policy to meet their archiving objectives.
7. Create user access policies. Many organisations will want to control which users access historical data in the archive and which data access method, screen, report, or query, they can use to access the data.
A best-practice solution will let an organisation configure user access policies that specify which users are authorised to access historical data and which reports they are able to use.
8. Ensure restoration. A restoration capability functions as an insurance policy should specific transactions need to be modified after archiving. Only by having such a restoration capability can most organisations convince business users that it is safe to implement an archiving solution.
9. Follow a time-tested methodology. No organisation wants its implementation, no matter how customised, to be on the bleeding edge of experimentation. It wants to be sure that the vendor it works with has seen and addressed the types of challenges likely to arise during an implementation.
Organisations should choose a vendor that has developed an implementation methodology for complex archiving solutions that meets the outlined business objectives and has been successfully applied over a large number of implementations.
Jaslow said, “Organisations that succeed in implementing a best-practices archiving solution will improve application performance by eliminating unnecessary data from their production database, reducing total cost of ownership by lowering hardware costs and maintaining regulatory compliance.”
-ENDS-
About Informatica
Informatica Corporation (NASDAQ: INFA) is the world's number one independent provider of data integration software. Organisations around the world rely on Informatica for maximising return on data to drive their top business imperatives. Worldwide, over 4,630 enterprises depend on Informatica to fully leverage their information assets residing on-premise, in the Cloud and across
