1. Information Lifecycle Management for
Oracle Apps Data
Erik Jarlstrom
Director of North American Pre-sales

2. What does this have to do with Oracle Databases?

3. 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

5. Agenda Database Growth and Impact
Strategy: Information Lifecycle Management
Active Archiving
Enterprise Database Archiving

6. 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

7. 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
Accounts Receivable 30 45
67.5
Other Modules 70
105
157.5

8. 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

9. Potential Solution: Ignore Database Growth
…and continue to add
People
Processes
Technology
…and continue to decrease
Performance
Availability
Time for other projects
Production Database

10. 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

11. 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
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 Access
Rare Access
Disposal

12. Matching Access and Performance to Business Value
© 2003 Enterprise Storage Group, Inc.
Source: Enterprise Storage Group, May 2003

13. Implement Storage Strategies to Meet Availability Requirements
RDBMS and High-Concurrency Storage (RAID)
RDBMS,
File Systems, NAS, Optical
Tape or Optical Storage

14. 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

15. Information Lifecycle Management Archiving Strategy
“On-Line Archive”
“Off-Line Archive”
“Current”
“History/Reporting”
Path 1
Archive
Archive
Production Database
Archive Database
Tape
Flat Files
Archive
Restore
Restore
Years 1 - 2
Years 3 - 5
Years 6 - 7
Years 8+
(Adjust timeframes to meet internal & statutory requirements)

16. Solution: Active Archiving
Data Access (locate, browse, query, report)
Production
Database
Archive Database
Archive
Files
Archive Files
Archive
&
Restore
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

17. Example Active Archiving Policies
Production Database
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

18. Archiving Oracle Apps Data
Archiving Historical Data
Archive Database
GL – Balances, Journals …
AP – Payments, Invoices, Vendors…
AR – Receipts, Invoices …
FA – Depreciation, Adjustments
Purchasing – POs, Reqs,
OM – Orders, …
INV - Transactions
General Ledger
Payables
Production
Database
Receivables
Assets
Locate, Browse, Query, Report . . .
Data Access

19. Transparent Access – How? Responsibility-Driven Data Access

20. Transparent Access - Forms
Production

21. Transparent Access - Forms
Archive

22. Transparent Access - Forms
Archive & Production

23. Transparent Access - Reports
Production

24. Transparent Access - Reports
Archive

25. Transparent Access - Reports
Archive & Production

26. 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

27. Challenge: Referential Complexity

28. Manage Your Enterprise Data Smarter
Test Smarter with
Relational Tools
Store Smarter with
Active Archive Solutions
Pre-Production
(Test, Dev, Training, …)
Production
PeopleSoft
ClarifyCRM
Oracle Apps
Relational Tools
Archive
for Servers
Archive for DB2
Relationship Engine
Oracle
SQL Server
Sybase
Informix
DB2 UDB
DB2
Legacy

29. 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

30. Questions Erik Jarlstrom Princeton Softech