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© 2012 IBM Corporation
Zarządzanie cyklem Ŝycia danychPeter Harrison, Smarter Planet Solutions Lead Architect CEE
© 2012 IBM Corporation
The Information Challenge
© 2012 IBM Corporation
On average, data repositories for large applications grow by 50% annually
© 2012 IBM Corporation
How are Organizations Responding to Data Growth?
Hardware Capacity
Performance
Dat
abas
e S
ize
• Use database partitioning
• Use database vendor compression
• Buy more Storage & CPU hardware
© 2012 IBM Corporation
�Performance degradation � Key business processes - payroll,
shipping, financial period close, information reporting - not being completed on time
� SLAs missed
� Applications not available when customers want to do business with you
� Customer satisfaction impacted
�Regulatory compliance �Data retention (Sox, Euro-Sox, J-Sox)
�Budget Pressures�Increased hardware storage costs due to
growing data
Challenges associated with Data Growth
�Storage cost spiral
� Multiplier effect
�Deteriorating service levels� Customer & employee complaints
� Increased fire fighting
�Increased maintenance burdens� Time spent on tuning and partitioning
� Longer backup windows
� Backup and recovery time increases
�Batch window creep
© 2012 IBM Corporation
Storage optimization can
reduce storage requirements
by over 90%!
© 2012 IBM Corporation
Benefits of Data Growth Management
• Reduce/Control Costs:– Storage costs - production level data is typically one of the
most expensive storage platforms
– Reduce CPU & disk upgrades and related downtime
– Enable tiered storage strategies
– Administrative costs - software license fees, hardware costs
& the people to manage data growth
(DBA, system & storage admin)
• Improve Application Performance:– Improved availability – no downtime caused by batch
process overruns;
– meet SLAs
– Improved/faster backup and recovery
© 2012 IBM Corporation
The results can have significant financial impact
For every 20% that is spent on storage, 80% cost is spent on theoperational elements of managing that stored informati on
© 2012 IBM Corporation
… with a rapid payback and high ROI
3 Yr Accumulative benefit
3,8M EUR
3 Yr ROI
151%
Payback period
2,5 months
€ 0,0
€ 2,0
€ 4,0
€ 6,0
€ 8,0
€ 10,0
€ 12,0
€ 14,0
€ 16,0
Day 0 Year 1 Year 2 Year 3 Year 4 Year 5
Exp
endi
ture
(M)
base case Optim DG
Sample assumptions: 10 TB in production, growth 20% per annum, 4 copies, 45 EUR/GB total annual storage cost
© 2012 IBM Corporation
Requirements to manage data across its lifecycle
Validate test resultsDefine policiesReport & retrieve
archived data
Enable compliance with retention &
e-discovery
Move only the needed information
Integrate into single data source
Create & refresh test data Manage data growthClassify & define data
and relationships
Develop database structures & code
Enhance performance
Discover where data resides
Develop &Develop &TestTest
Understand &Understand &DefineDefine
Optimize, Archive Optimize, Archive & Access& Access
Consolidate &Consolidate &RetireRetire
Information Governance Core DisciplinesLifecycle Management
Application Owners
& Data Stewards“I need to understand what data exists and how its related in order to define the policies and standards to manage that
information as it ages. “
“I need to store data according to enterprise standards.” [Leverage Data Architect]
Test & QA Teams “I need a repeatable process to configure and refresh my test databases quickly to meet business demands.”
“I need to identify bottlenecks in system performance.”
Operations Team
DBAs
“I need a method to tune application performance and archive aged data.”
“I need to archive legacy data that we do not want to move to the new application but provide access to it on-demand.”
Developers “I need to consolidate & integrate data across multiple systems.”
Slide 10
A1 Remove AccessAuthor; 2010-11-23
© 2012 IBM Corporation
13.Govern Lifecycle of Information13.1 Baseline database sizes and storage architecture13.2 Discover business objects13.3 Classify data and define service levels13.4 Archive data and unstructured content13.5 Establish policies for management of test data13.6 Define policies for legal discovery of electronic documents13.7 Analyze content
Information Lifecycle Governance
© 2012 IBM Corporation
UNIVERSAL
ACCESS
UNIVERSAL
ACCESS
IBM Optim Solution Overview
Optim Designer
Eclipse-Based
Optim ServerOptim Server
Web-Based Management
Console
DRADRA
InfoSphereData Arch.InfoSphereData Arch.
3rd party model data3rd party
model data
InfoSphereDiscoveryInfoSphereDiscovery
TARGETS
Archive FilesArchive Files
Archive DatabaseArchive Database
XMLXML
OtherOther
WORMWORM
Tape or CDTape or CD
Custom / Legacy / P
ackaged
Application Data
Custom / Legacy / P
ackaged
Application Data
Non-Production EnvironmentsNon-Production Environments
Subset/MaskSubset/Mask
Additional Options
ODBC / JDBC
XML
SQL
Excel
Access
ArchiveArchive
ERP/CRM Applications
Custom/Other
IBM Mashups
© 2012 IBM Corporation
All projects require that you “Discover and Define”
You can’t manage what you don’t understand
• Data distributed over multiple applications,
databases and platforms
– Where are the entities located?
– How are different DBs related?
• Complex, poorly documented data
relationships
• Inconsistent data models and designs
– Different vocabularies across the
organization
– Documentation poor or non-existant
– Not often kept up-to-date
– Applications manage the relationships and
business rules – not in the DB
• Where is the sensitive data?
?
??
??
??
?
???
?
?
?
?
?
?
?
??
?
??
?
??
?
?
?
?
Distributed Data Landscape
© 2012 IBM Corporation
Understanding data relationships across the enterprise
Capture related business objects from across the enterprise
Define
CRM on
Oracle database
ERP / Financials
on DB2
Custom Inventory Mgmt
on DB2
• Represents application data record – payment, invoice, customer
– Referentially-intact subset of data across related tables and applications; includes metadata
• Provides “historical reference snapshot” of business activity
• Federated extract support across enterprise data stores
© 2012 IBM Corporation
Employ effective test data management practicesDevelop &
Test
•Create targeted, right-sized test environments
•Substitute sensitive data with fictionalized yet contextually accurate data
•Easily refresh, reset and maintain test environments
•Compare data to pinpoint and resolve application defects faster
•Accelerate release schedules
Production or Production Clone
100 GB
25 GB
50 GB
25 GB
Development
Unit Test
TrainingIntegration
Test
Extract
Relational subset
Load / MaskInsert / UpdateCompare
© 2012 IBM Corporation
Current
Production
Historical
Retrieve
Retrieved
Universal Access to Application Data
Application Application XML ODBC / JDBC
Step 13.4: Optim™ Data Growth Solution: Archiving
Archives
Reporting
Data
Historical
DataReference
Data
Archive
Optim
Mashup
Archiving is an intelligent process for moving inactive or infrequently accessed data that still has value, while providing the ability to search and retrieve the data
© 2012 IBM Corporation
Leverage Cost-Effective Storage Alternatives
Non DBMSRetention Platform
ATA File ServerEMC CenteraIBM RS550HDS
Compressed
Archives
Offline Retention Platform
CDTapeOptical
Compressed
Archives
Production
Database
Archive
Definitions
Archive
Restore
Archive Reporting
Database
Compressed
Archives
Online
Archive
5-6 years
Offline
Archive
7+ years
Current
Data
1-2 years
Active
Historical
3-4 years
© 2012 IBM Corporation
Proven with customers across the world…
© 2012 IBM Corporation
Summary
• Databases are growing at an unprecedented rate
• Cost of storing data increases as the data grows
• The larger the database, the slower the performance
• Archive historical data to reclaim space, improve performance
– Prevent data growth from impairing business results
• Automate Business Object Discovery to gain new Data Insights,
Ensure Accuracy and Speed Implementation
• Control database size at desired level
– Minimize storage footprint, cut costs
– Streamline routine maintenance
• Significant cost savings and rapid ROI!!!
© 2012 IBM Corporation
The IBM Data Governance Unified Process: Driving Business Value with IBM Software and Best Practices
Sunil Soares : Director of Data Governance, IBM Software Group
IBM DATA GOVERNANCE UNIFIED PROCESS
IBM - Pioneering Information Governance