Download Maximize Oracle Performance by Archiving Historical Data

Information Lifecycle
Management for
Oracle Apps Data
Erik Jarlstrom
Director of North American Pre-sales
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
“…databases will grow 30x during the next decade, or roughly 40% annually.”
Source: Meta Group 2001
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
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
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Current Data
Historical Data
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
70
105
157.5
Other Modules
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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
Production
Database
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– Performance
– Availability
– Time for other projects
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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Strategy: Information Lifecycle
Management
 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
Acquisition of Data
Disposal
Rare Access
Heavy Access
Medium Access
 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
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Matching Access and Performance
to Business Value
record
record
of of
value
value
Relative
Relative
Frequency
access
and
retrieval
Frequency
of of
access
and
retrieval
Email / Report / Record creation,
Document receipt,
Statement print time
All retrievals from low-cost, lower performance, archival media
from this point forward
High-performance
Disk purge
Disposition
High-cost,
Fast response
(Sub-second)
Low-cost,
Slow response
(30 seconds to days)
Retention period
© 2003 Enterprise Storage Group, Inc.
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Source: Enterprise Storage Group, May 2003
Implement Storage Strategies to Meet
Availability Requirements
RDBMS and HighConcurrency
Storage (RAID)
RDBMS,
File Systems,
NAS, Optical
Tape or Optical
Storage
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Segregating Application Data to
Support Storage Strategy
ORDER_DATE >
01-JAN-2002
ORDER_DATE >
01-JAN-1998 &
< 31-DEC-2001
ORDER_DATE <
31-DEC-1997
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Information Lifecycle Management
Archiving Strategy
“Current”
Production
Database
Years 1 - 2
“History/Reporting”
Archive
Path 1
Archive
“On-Line
Archive”
Archive Database
Years 3 - 5
Restore
Archive
Flat Files
Tape
Restore
Years 6 - 7
(Adjust timeframes to meet internal & statutory requirements)
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“Off-Line
Archive”
Years 8+
Solution: Active Archiving
Archive
Files
Production
Database
Archive
Database
Archive
&
Archive Files
Restore
Data Access (locate, browse, query, report)
 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
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Example Active Archiving Policies
Production
Database
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Archive
Database
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
Archiving Oracle Apps Data
Archiving Historical Data
Production
Database
GL – Balances, Journals …
AP – Payments, Invoices, Vendors…
AR – Receipts, Invoices …
FA – Depreciation, Adjustments
Purchasing – POs, Reqs,
OM – Orders, …
INV - Transactions
Locate, Browse, Query, Report . . .
Data Access
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Archive
Database
General Ledger
Payables
Receivables
Assets
Transparent Access – How?
Responsibility-Driven Data Access
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Transparent Access - Forms
Production
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Transparent Access - Forms
Archive
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Transparent Access - Forms
Archive & Production
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Transparent Access - Reports
Production
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Transparent Access - Reports
Archive
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Transparent Access - Reports
Archive & Production
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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





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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
Challenge: Referential Complexity
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Manage Your Enterprise Data Smarter
Test Smarter with
Relational Tools
Store Smarter with
Active Archive Solutions
Pre-Production
(Test, Dev, Training, …)
Production
PeopleSoft
Relational
Tools
ClarifyCRM
Archive
for Servers
Oracle
Apps
Archive for
DB2
Relationship Engine
Oracle
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SQL
Server
Sybase
Informix
DB2
UDB
DB2
Legacy
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
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Questions
Erik Jarlstrom
Princeton Softech
[email protected]
916.939.8191
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