Information Lifecycle Management for

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Presentation transcript:

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

What does this have to do with Oracle Databases?

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

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

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

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

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

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

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

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

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

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

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

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)

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

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

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

Transparent Access – How? Responsibility-Driven Data Access

Transparent Access - Forms Production

Transparent Access - Forms Archive

Transparent Access - Forms Archive & Production

Transparent Access - Reports Production

Transparent Access - Reports Archive

Transparent Access - Reports Archive & Production

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

Challenge: Referential Complexity

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

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

Questions Erik Jarlstrom Princeton Softech ejarlstrom@princetonsoftech.com 916.939.8191