information lifecycle management for oracle apps data erik jarlstrom director of north american...
TRANSCRIPT
Information Lifecycle Management for
Oracle Apps Data
Erik Jarlstrom
Director of North American Pre-sales
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What does this have to do with Oracle Databases?
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Corporate Summary
Founded in 1989 Over 2000 customers in 30 Countries Committed to providing enterprise database
archiving and test data management solutions Reputation of high quality and reliable products Partners with industry leading database and storage
solution providers Recognized by Gartner, Giga, and Meta as
database archiving market leader
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Agenda
Database Growth and Impact
Strategy: Information Lifecycle Management
Active Archiving
Enterprise Database Archiving
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Database Growth Impacts IT Budgets
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Current Data
Historical Data
40% CAGR may be a conservative estimate!“With growth rates exceeding 125%, organizations face two basic options: continue to grow the infrastructure or develop processes to separate dormant data from active data.” Source: Meta Group 2003
“…databases will grow 30x during the next decade, or roughly 40% annually.”Source: Meta Group 2001
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Oracle Applications Data Growth Example
5 Years (GB) 6 Years (GB) 7 Years (GB)
Entire Database 200 300 450
Financials Modules
130 195 292.5
Accounts Payable 60 90 135
General Ledger 40 60 90
Accounts Receivable 30 45 67.5
Other Modules 70 105 157.5
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Related Symptoms
Application users complain their system is “slow” to:– Perform online account inquiries and financial period closeouts– Enter transactions and process payments– Post batches and generate reports– Process weekly/monthly/quarterly depreciation runs
Increasing operating costs– Higher hardware and software license and support costs– Longer development and test cycles– Labor intensive time and effort for system administrative tasks – Extended maintenance times for managing backup, recovery
and cloning processes– Additional headcount required to adequately manage a larger
environment
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Potential Solution: Ignore Database Growth
…and continue to add– People– Processes– Technology
…and continue to decrease– Performance– Availability– Time for other projects
ProductionDatabase
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Traditional Approaches
Add More Capacity – Bottom line impact– Uncontrolled continuous cost
Institute rigorous database tuning– Does not directly address data growth– Reaches point of diminishing returns
Delete Data (i.e. Purge)– Legal and retention issues– Data may be needed for data warehousing
In-House Development– Complex undertaking– Application specific– Support / upgrade / maintenance /
opportunity cost
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Understand data retention requirements– All data has a life cycle from acquisition to disposal
Define availability level requirements– At various stages, data has different:
• Business value• Access requirements• Performance requirements
Implement storage strategy to meet availability requirements– Each stage should be stored on the appropriate type of storage
Segregate application data to support strategy– Data should be managed to match the business value
Acquisition of Data
Heavy Access
Medium AccessRare Access
Disposal
Strategy: Information Lifecycle Management
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Matching Access and Performance to Business Value
High-cost,Fast response(Sub-second)
Low-cost, Slow response
(30 seconds to days)
Fre
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f acc
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and
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Rela
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f reco
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Email / Report / Record creation, Document receipt, Statement print time
Retention period
Disposition
All retrievals from low-cost, lower-performance, archival mediafrom this point forward
High-performanceDisk purge
High-cost,Fast response(Sub-second)
Low-cost, Slow response
(30 seconds to days)
Email / Report / Record creation, Document receipt, Statement print time
Retention periodRetention period
Disposition
All retrievals from low-cost, lower-performance, archival mediafrom this point forward
High-performanceDisk purge
Rela
tive va
lue o
f reco
rdFre
quen
cy o
f acc
ess
and
retri
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l
High-cost,Fast response(Sub-second)
Low-cost, Slow response
(30 seconds to days)
Fre
quen
cy o
f acc
ess
and
retri
eva
l
Rela
tive va
lue o
f reco
rd
Email / Report / Record creation, Document receipt, Statement print time
Retention periodRetention period
Disposition
All retrievals from low-cost, lower-performance, archival mediafrom this point forward
High-performanceDisk purge
High-cost,Fast response(Sub-second)
Low-cost, Slow response
(30 seconds to days)
Email / Report / Record creation, Document receipt, Statement print time
Retention periodRetention period
Disposition
All retrievals from low-cost, lower-performance, archival mediafrom this point forward
High-performanceDisk purge
Rela
tive va
lue o
f reco
rdFre
quen
cy o
f acc
ess
and
retri
eva
l
© 2003 Enterprise Storage Group, Inc. Source: Enterprise Storage Group, May 2003
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RDBMS and High-Concurrency Storage (RAID)
Tape or Optical Storage
RDBMS,File Systems, NAS, Optical
Implement Storage Strategies to Meet Availability Requirements
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ORDER_DATE > 01-JAN-2002
ORDER_DATE > 01-JAN-1998 &< 31-DEC-2001
ORDER_DATE < 31-DEC-1997
Segregating Application Data to Support Storage Strategy
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Information Lifecycle ManagementArchiving Strategy
Flat FilesPath 1
Archive
“Current” “History/Reporting”
Archive Database
“On-LineArchive”
“Off-LineArchive”
(Adjust timeframes to meet internal & statutory requirements)
Archive
RestoreTape
ProductionDatabase
Years 1 - 2 Years 3 - 5 Years 6 - 7 Years 8+
Archive
Restore
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Solution: Active Archiving
Data Access (locate, browse, query, report)
Production Database
Archive Database
ArchiveFiles
Archive Files
Reduce amount of data in the application database– Remove obsolete or infrequently used data– Maintain “business context” of archived data– Archive relational subsets vs. entire files
Enable easy user access to archived information– View, research and restore as needed
Support Data & Storage Management Strategies
Archive&
Restore
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Example Active Archiving Policies
ProductionDatabase
ArchiveDatabase
Ongoing Archive Processing
Company A 24 months GL, AR, AP, PO, and FA data
Older GL, AR, AP, PO, and FA data
Quarterly – GL, AR, AP, PO, and FA data
Company B 24 months GL and FA data
Older GL and FA data Yearly – GL and FA data
Company C 24 months Order Management (OM) data
12 months AP and PO data
Older OM, AP, and PO data
Monthly – OM, AP, and PO data
Company D 15 months AR, AP, PO, and OM data
Older AR, AP, PO, and OM data
Quarterly – AR, AP, PO, and OM data
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Archiving Historical Data
GL – Balances, Journals …AP – Payments, Invoices, Vendors…AR – Receipts, Invoices …FA – Depreciation, AdjustmentsPurchasing – POs, Reqs,OM – Orders, …INV - Transactions
Locate, Browse, Query, Report . . .
Data Access
General Ledger
Payables
Receivables
Assets
Production Database
Archive Database
Archiving Oracle Apps Data
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Transparent Access – How?Responsibility-Driven Data Access
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Production
Transparent Access - Forms
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Archive
Transparent Access - Forms
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Archive & Production
Transparent Access - Forms
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Production
Transparent Access - Reports
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Archive
Transparent Access - Reports
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Archive & Production
Transparent Access - Reports
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Top Requirements for Enterprise Database Archiving
Extract subsets of related data to offload– Able to go beyond catalog-defined relationships
Selectively/relationally delete all or some archived data
Selectively/relationally restore Access, browse, query archived data Preserve business context of archived data Comprehensive archive data management Architecture for long term enterprise-wide
strategy
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Challenge: Referential Complexity
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Manage Your Enterprise Data Smarter
Relationship Engine
RelationalTools
Archive for DB2
Archivefor Servers
Pre-Production
(Test, Dev, Training, …)
Production
OracleSQL
ServerSybase Informix
DB2 UDB
DB2
ClarifyCRMPeopleSoftOracle Apps
Test Smarter with
Relational Tools
Store Smarter with
Active Archive Solutions
Legacy
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Suggested Resources
Databases on a Diet: Meta - Jan 2003
Banking on Data: InformationWeek – Aug 4, 2003
– Bank of New York implements active archiving
Enterprise Storage Group (ESG) Impact Report on Compliance - May 2003
– The effect on information management and the storage industry
Princeton Softech’s Web site and whitepapers
www.princetonsoftech.com
