Informatica ILM Archive and Application Retirement

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1 Informatica ILM Archive and Application Retirement Thierry AUDOT Technical Manager EMEA 26 th September

2 Live Archiving What are key users pain points? My reports take forever to run! I need all of my data for analysis! Application User Business Analyst The daily back-up doesn t fit in the nightly window anymore! What about the upgrade next year? DBA Director of Applications 2

3 Live Archiving The Challenge of Increasing Data Growth BEFORE SOLUTION Growing storage costs Diminishing performance Increasing maintenance & Compliance work AFTER SOLUTION Predictable manageable growth Improved, stable performance Reduced maintenance & compliance work 3

4 ILM Data Archive Multiple Alternative Methods to Manage Data Growth PARTITION Smart partitioning Individual table Entity-based Production Data Partitioned Production Data Improve performance, maintain in same database Access archived data through production interface Production Data Seamless Access Archive Database Move data out of production Less maintenance Archive data to optimized file format for storage reduction Production Data Optimized File Archive Compressed (up to 98%) Immutable Accessible 4

5 Informatica Data Archive Unified Information Lifecycle Policy NA EMEA ORDERS ORDERS >5 YRS NA ORDERS >7 YRS NA ORDERS PARTITION 2 YRS >2 YRS >5 YRS EMEA ORDERS >7 YRS EMEA ORDERS Production Data Partitioned Data Archive Database Optimized File Archive Very Frequent Less Frequent Infrequent Rare 100% 80% Maintenance Window Storage Size Cost 100% 100% 60% 100% 100% 75% 25% 20% 2% 5% Production Partitioning DB Archive File Archive 5

6 Smart Partitioning Partition Based on Entities, Not Just Individual Tables Order Table Order Id Date Mode Customer Id /5/2012 Online /5/2012 Direct /5/2012 Online /5/2012 Direct /5/2012 Online /5/2012 Direct /5/2012 Online Order Item Table Order Id Product ID Unit Price Quantity Order Table Order Id Date Mode Customer Id /5/2012 Online /5/2012 Online /5/2012 Online /5/2012 Online Order Item Table Order Id Product ID Unit Price Quantity Order Table Order Id Date Mode Customer Id /5/2012 Direct /5/2012 Direct /5/2012 Direct Order Item Table Order Id Product ID Unit Price Quantity T a b l e S p a c e 1 T a b l e S p a c e 2 Partition TS1: Where ORDER_MODE= Online Partition TS2: Where ORDER_MODE= Direct 6

7 Archive Process - Features Live Process Uses dynamically generated SQL Runs on the production database server Single engine relocates to multiple formats Complete logging and audit trails Schedulable, repeatable process Restartable in case of interruption Data structure synchronization process 7

8 Archive Database - Features NOT a complete replica of production Transactional data only Archived Transactional Data Read only Only core transactional tables Data remains in original format: same names, columns, datatypes, etc. No replicated data Single schema Located on any server 8

9 Restore Process - Features Automated, standard functionality Multiple options All archived data Criteria based Archive Cycle Single transaction Undo functionality Always tested, rarely used 9

10 Seamless Access Layer - Features Uses existing application user interface Dynamically generated database layer Leverages existing security Handles customizations and extensions Does not modify application code Supports 3 RD party query/report tools Standard functionality for Oracle Applications, PeopleSoft, and Siebel 10

11 Optimized File Archive Features Optimized file format Highly compressed Accessible with included DataDiscovery Portal JDBC interface enables access from third party reporting and SQL tools Secured cannot be modified Does not need to be decompressed before searching No separate indexing 11

12 Data Archive Accelerators Comprehensive out-of-the-box content for leading packaged applications Functional entity definitions Business rule validation Seamless access to archived data Future version support History upgrade when upgrading production Application specific functionality 12

13 Two Important Accelerator Components Entity Definition Logical unit to archive Database and application level relationships Policy scoping criteria Business Rules Transaction chaining Within an entity To other applications Testing of Fields, Flags & Codes 13

14 Business Rule Validation Oracle Applications Total number of archivable candidates. These pass all the business rules below. Total number of exceptions categorized below Total number of candidates within scope of the policy All relevant business rules for this module Exception counts per business rule 14

15 Informatica Data Archive For Application Retirement 15

16 Who Cares about Legacy Applications? Different Perspectives, Different Concerns I may need records for a legal situation You need to keep the data for 7 years Attorney Compliance Officer Our data centers are maxed out! We need to eliminate the cost of these apps VP of IT CIO Proprietary and Confidential 16

17 Legacy Applications What are the Costs? Software licenses Web Server App Server Thick Client Maintenance fees Hardware Application Subject matter expertise Energy Database Poor utilization of resources Operating System Hardware Skill-sets are scarce Technology platforms are not viable Expensive to maintain 17

18 What is Application Retirement? Application Retirement is the process of shutting down a structured data application by relocating all data into an application independent format and providing ongoing access to the key business data. Application Retirement is also known as: Decommissioning Sunsetting End-of-life (EOL) Proprietary and Confidential 18

19 Informatica ILM Application Retirement Focus on the data BEFORE AFTER Web Server App Server Thick Client Reports Search Metadata Application Database Application Data Data Structures Operating System Catalog Hardware Storage Interface 19

20 ILM Approach to Retired Data Retire, Access, Purge Legacy Data Sources Connect Retire Verify Optimized File Archive Access Manage Purge Purged Data Proprietary and Confidential Retire data confidently from any structured data source Validate completeness of your data before decommissioning Store retired data in a massively compressed and accessible file archive Manage retention policies, access data, and purge data permanently Achieve compliance with all government regulations and industry standards 20

21 The Optimized File Archive What is it? A repository for archived structured data Protects data with its immutable format Massively compresses data Controls access with built-in security Supports data from various sources simultaneously Enables access through a variety of methods Proprietary and Confidential 21

22 Retire multiple applications to a single location JDE DB2 CRM VSAM Kronos SQL Server T&E Mgmt Win2K MFG Informix PeopleSoft Oracle Optimized File Archive Access Various Metho ds 22

23 Access to Retired Data Flexibility to use your preferred method CSV XML SQL Informatica Data Discovery BI / Reporting / SQL Tools MS Excel and MS Access Extract to CSV, XML, or SQL ODBC/JDBC Access retired data directly using the method of your choice Proprietary and Confidential Optimized File Archive Use built-in functionality or 3rd party tools 23

24 Proven Solution 24

25 25

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