Ibm Optim Techical Overview 01282009

IBM Optim Technical Overview Charles Lucas IBM Data Management Specialist

Agenda
Challenges
Optim Concepts
Optim Architecture
Optim for Archiving
Optim Test Data Management
Optim Data Privacy
Summary

Challenges

Challenges Facing Customers Today
Mitigate Risk
Effectively and securely manage archived data
Protect data privacy
Accurate, prompt responses to auditing requests
Maintain Performance in face of Data Growth
Improve application performance by moving historical transaction records to a safe, secure archive
Achieve Service Level Agreements (SLAs) consistently
Control Costs
Reduce infrastructure costs; utilize cost effective tiered storage
Minimize cost and time for compliance
Improve productivity of development team

Challenges: Reduce Risk
Insiders and hackers are targeting data for profit
Data in and of itself has monetary value:
Credit Card Number With PIN - $500
Drivers License - $150
Birth Certificate - $150 Source: USA TODAY research 10/06
Average cost of a data breach in 2007 was $197 USD per customer record leaked Source: Ponemon Institute
This has been a driving factor for creating data protection and privacy regulations
How to protect Personal Identifiable Information (PII)?

Challenges: Dealing with Data Growth
Data is growing at a very rapid rate
Annual growth rates for databases exceed 125%
Mergers & acquisitions
Data Warehousing
The Data Multiplier effect
OLAP cubes, data marts, and so on
Copies of data for test, development, quality assurance, disaster recovery, etc.
Retention of data for compliance purposes
Info 2.0 applications are verbose
How to manage data growth and aging effectively?

Challenges: Control Costs
Growing storage costs due to rapid data growth
Cost of storing and managing the many copies of your production data
Cost of implementing data privacy measures for compliance across different databases and applications
Cost of archive retrievals for compliance requests and e-discovery
Growing development time costs
How to control storage and data management costs?

Optim Concepts

Optim Concepts
Complete Business Object
Federated Data
Enterprise Architecture
Terminology

Complete Business Object
Referentially-intact subset of data across related tables and applications; includes metadata
Provides “historical reference snapshot” of business activity
Federated object support across enterprise data stores
Payments

Federated Data Support Retek / Oracle Other apps / any DBMS Custom Inventory Management / DB2 Capture related business objects and processes from across the enterprise

Enterprise Architecture Platform independent architecture acts as central point to extract, store, restore and transform application data.

Optim Terminology
Referentially-Complete
Optim extracts data based on primary/foreign key relationships (“parent/child”) between tables.
Handling data this way reduces errors and allows data to be moved without breaking application software
Subsetting
Using Optim to create a reduced size but referentially complete copy of a database for development or test.
Masking
Changing sensitive data before testing by replacing it with false but equally valid data.

Optim Architecture

Optim Architecture
Optim Workstation
Optim installed on a Windows PC capable of performing all Optim functions directly against a data source or by connecting to an Optim Server.
Optim Server
Optim installed on a Unix or Windows server that handles requests from Optim Workstations or the command line.
Open Data Manager (ODM)
Allows access to archive files as an ODBC data source.
Allows access to archived tables through Oracle Heterogeneous Services as a Database Link

Optim Architecture Architecture Optim Workstation Optim Server Enterprise Reporting Tools ODM Optim Universal Database Access Layer ERP CRM Custom App Optim Directory Dev QA Archive Archive Archive Archive

More Important Terminology
Optim Directory
A DBMS-based repository for Optim metadata
DB Alias
How Optim refers to a database
Access Definition
A description of what to extract and how to extract it
Relationship
User defined connection between the data in two tables based on matching one to many columns in each table
Primary Key
User defined set of columns unique within a table

The Optim Directory
An “instance” of Optim
Holds all Optim metadata in database tables
Security possible using windows domain/user
Maintains a directory of archive Files
Created by Optim configuration when “Configure the First Workstation” is performed
Additional users can get access by using the “Configure Additional Workstation” dialog

Database Alias
Defines database in an Optim directory.
Created by Optim Configuration
Allows any database object to be addressed and accessed by a 3-part address:
DB Alias
Owner
Object Name
Allows consistent naming across the enterprise
More than just a connect string!

Created in Optim Design GUI
Defines a set of tables and relationships which can be traversed relationally
Archive Actions, which are stored procedures or DML statements, may be fired at key points of control
Every extract, delete or restore requires an Access Definition
These may be named and shared or local and tied to a single job.
Access Definition

Relationships are automatically found when primary keys and foreign keys are defined in DB.
User-defined primary keys and relationships can be created in Optim in GUI designer or imported.
Relationship can be cross-database (between two databases, named by DB Alias)
Relationships Primary Keys Relationships Optim Directory Database Alias

Optim For Archiving

Archive, Retention and e-Discovery Production Extract Restore Archive E-Discovery Universal Access to Data
Optim safely moves inactive or historical data to an archive
Archive can be accessed in many ways

Optim Data Growth Solution: Archiving Production Selective Restore Archives
Complete Business Object is historical snapshot of activity
Storage device independence enables ILM
Immutable file format enables data retention compliance
Current Historical Restored Reporting Data Historical Data Reference Data Archive Universal Access to Application Data Application Application XML ODBC / JDBC

Optim Test Data Management

Why Optim Test Data Management?
Improve development productivity
Faster turnaround time
Supports test automation
Easier to create/verify test results
Multiple sandboxes
Better quality data (more frequent refreshes)
Control costs
Reduce storage per test instance
Ease DBA workload

Test Data Management
Easily maintain test environments
Create targeted, “right-sized” subsets faster and more efficiently than cloning
Production Compare Dev QA Test Load Insert / Update Compare Extract Files Extract

Optim Test Data Management Data Fixes Compare Results TEST Go Live Production Application Refine Data Copy Production Data for Testing Refresh Test Data Optim Extract Optim Edit Optim Compare Optim Extract Optim Edit

FIND CUSTOMER NOTE INFO EXIT TABLE FIND ORDERS NOTE INFO EXIT TABLE FIND DETAILS NOTE INFO EXIT TABLE Single Table Editors The Relational Editor Traditional vs. Relational Tools
One table or view at a time
No edit of related data from multiple
Simultaneous browse/edit of related data from multiple tables and databases
Insert, delete, update
Audit trail, access controls
CUSTOMERS ORDERS DETAILS ........................ ........................ ........................ ........................ ........................

Find unexpected changes (or validate expected changes)
For application testing, QA, and to verify database contents
Single-table or multi-table compare
Creates compare file and/or compare Report of results
Optim Compare Master Copy Latest Test Files Reports Compare

Optim Data Privacy

Why IBM Data Privacy?
Protecting sensitive data
Regulatory & Compliance
PCI
HIPPA
EU Safe Harbour
Many more…
Off shoring testing
Sub subcontracting test & dev.
Good business practice
Training environments

Optim Data Privacy Solution
Substitute confidential information with fictionalized data
Deploy multiple masking algorithms
Provide consistency across environments and iterations
Enable off-shore testing
Protect private data in non-production environments
Production Contextual, Application- Aware, Persistent Data Masking EBS / Oracle Custom / Sybase Siebel / DB2 Test EBS / Oracle Custom / Sybase Siebel / DB2

Data Privacy
A comprehensive set of data masking techniques to de-identify data
R eplaces (masks) confidential data with contextually accurate but fictionalized data
Production Transform and Mask Masked Test Data

De-Identify test data
Can Be Performed
During Extract Process from DB
During Insert/Load Process to DB
Or as a Standalone Convert Process
Transform or mask sensitive data using :
Standard rules: Literals, Special Registers, Expressions, Default Values, Look-up tables
Intelligent transformation rules: PCI, Addresses etc.
Custom mapping rules: user exits
Converted extract file is safe to share – sanitized data

Masked fields are consistent Data is masked DB2 Client Billing Application Consistent mapping Across the enterprise 132009824 157342266 SSN#s 132009824 157342266 SS#s 323457245 134235489 SSN#s 323457245 134235489 SSN#s

Map unlike column names
Transform/mask sensitive data
Datatype conversions
Column-level semantic date aging
Literals
Registers
Calculations
Default values
Exits
Social Security (US)
Credit Card
Email
Hash Lookup
Lookup
Random Lookup
NAME tables (US)
ADDRESS table (US)
Shuffle
String manipulation
Currency conversion
Masking Functions

Example: Bank Account Numbers
First Financial Bank’s account numbers are formatted “123-4567” with the first three digits representing the type of account (checking, savings, or money market) and last four digits representing customer ID
To mask account numbers for testing, use the actual first three digits , plus a sequential four-digit number
The result is a fictionalized account number with a valid format:
“ 001-9898” becomes “001-1000”
“ 001-4570” becomes “001-1001”
Complexity 1

Example: First and Last Name
Direct Response Marketing, Inc. is testing its order fulfillment system
Fictionalize customer names to pull first and last names randomly from the Customer Information table:
“ Gerard Depardieu” becomes “Ronald Smith”
“ Lucille Ball” becomes “Elena Wu”
Optim ships with over 5,000 male/female names and over 80,000 last names
Complexity 2

Example: Addresses
Direct Response Marketing, Inc.
is testing its order fulfillment system
Fictionalize customer addresses to
pull an entire address from the
Customer Information table:
“ 111 Campus Drive Princeton, NJ 08540 ” becomes…
“ 1223 E. 12 th Street NY, NY 10079”
Optim ships with over 100,000 valid CASS addresses
Complexity 3

Example: Intelligence
Generating valid social security numbers (as defined by the US Social Security Administration)
Generate valid credit card numbers (as defined by credit card issuers)
Generate desensitized e-mail addresses
Generate Email address based on format: name@domain
Complexity 3

Using Custom Masking Exits
Apply complex data transformation algorithms and populate the resulting value to the destination column
Selectively include or exclude rows and apply logic to the masking process
Valuable where the desired transformation is beyond the scope of supplied Column Map functions
Example: Generate a value for CUST_ID based on customer location, average account balance, and volume of transaction activity
Complexity 4

Summary

Summary
IBM Optim helps solve 3 major challenges for enterprises today:
Migrate Risks
Maintain performance in the face of major data growth
Reduce Costs
IBM Optim enables effective ILM
The IBM Data Growth solution keeps high performance of applications in the face of data growth by archiving inactive data
Once archived, it supports prompt, accurate responses to audit and discovery requests

Summary
Test data management can speed delivery of developed applications
IBM Optim’s data masking capabilities protect privacy by de-identifying sensitive data
Pre-built modules for many popular applications are supported by IBM Optim
Optim is a recognized market leader and used successfully by customers in almost all industries

Ibm Optim Techical Overview 01282009

by lucascibm

Accessibility

Categories

Upload Details

Usage Rights

2 Embeds 44

Statistics

Ibm Optim Techical Overview 01282009 Presentation Transcript

http://www.slideshare.net	42
http://www.linkedin.com	2