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Oracle Enterprise Manager Cloud Control 12c: Managing Data Center Chaos

You're reading from   Oracle Enterprise Manager Cloud Control 12c: Managing Data Center Chaos Take back control of your data center with this practical step-by-step tutorial to using Oracle Enterprise Manager. Real-life examples and case studies help you manage rationally rather than through day-to-day firefighting.

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Product type Paperback
Published in Dec 2012
Publisher Packt
ISBN-13 9781849684781
Length 394 pages
Edition 1st Edition
Languages
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Author (1):
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PORUS HOMI HAVEWALA PORUS HOMI HAVEWALA
Author Profile Icon PORUS HOMI HAVEWALA
PORUS HOMI HAVEWALA
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Table of Contents (19) Chapters Close

Oracle Enterprise Manager Cloud Control 12: Managing Data Center Chaos
Credits
About the Author
Acknowledgements
About the Reviewers
www.PacktPub.com
Preface
1. Chaos at Data Centers 2. Enter Oracle Cloud Control FREE CHAPTER 3. Ease the Chaos with Performance Management 4. Ease the Chaos with Configuration Management and Security Compliance 5. Ease the Chaos with Automated Provisioning 6. Ease the Chaos with Automated Patching 7. Ease the Chaos with Change Management 8. Ease the Chaos with Test Data Management 9. Ease the Chaos with Data Masking 10. Ease the Chaos with Exadata Management 11. Real-life Examples and Case Studies, and It's a Wrap: The Future is the Cloud Index

Benefits and capabilities


When you create a data subset, you can define subset criteria (such as a where condition), which will limit the amount of data that will be extracted for the subset. As a result, the storage requirements in the target database are reduced. This is one of the most important benefits of data subsetting, since it helps to reduce expensive storage costs.

You can select multiple applications, that is, schemas (in the case of multi-tenanted databases) for the subset. The definition of tables associated with these applications and the relationships between them will be extracted from the Application Data Model into the subset definition, along with additional metadata of the constraints and indexes. You can totally avoid the manual labor normally associated with collecting this information and writing appropriate scripts.

Table rules can be defined with where clauses and bind variables that limit the data that is extracted. Table statistics are then analyzed to get an estimate...

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