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Full Description
Businesses now rely almost entirely on applications and databases, causing data and storage needs to increase at astounding rates. It is therefore imperative for a company to optimize and simplify the complexity of managing its data resources. Plenty of storage products are now available, however the challenge remains for companies to proactively manage their storage assets and align the resources to the various departments, divisions, geographical locations and business processes to achieve improved efficiency and profitability. Data Lifecycles identifies ways to incorporate an intelligent service platform to manage and map the storage of data. The authors give an overview of the latest trends and technologies in storage networking and cover critical issues such as world-wide compliance.
Data Lifecycles:
Provides a single-source guide to data and storage methodologies, processes, technologies and compliance issues.
Addresses the need of an encompassing intelligent data and storage management platform for modern businesses.
Gives an overview of the latest data technologies and concepts such as utility computing and information lifecycle management.
Clearly defines and describes lifecycle management and strategies to ensure growth of critical business data.
Shows how to dramatically reduce the total cost of storage ownership and provide rapid return on investment.
Enables customers to make decisions directed toward the purchase of storage tools and storage management solutions.
This text is an ideal introduction to modern data lifecycle management for network managers, system administrators, storage/system architects, network managers, information management directors as well as CIO/CTOs and their teams, senior IT managers and decision makers, and database administrators.
Contents
Preface. Who should read this book.
Purpose of this book.
1 Introducing Utility Computing.
1.1 Real problems and real solutions.
1.2 New storage management.
2 The Changing IT Imperative.
2.1 Introduction to utility computing.
2.2 General market highlights.
2.3 Real challenges and opportunities.
2.4 Summary.
3 Being Compliant.
3.1 So what are the regulations?
3.2 Financial services companies.
3.3 Telecommunications companies.
3.4 Utilities companies.
3.5 Public authorities and government.
3.6 Managing data for compliance is just a specialised form of data management.
3.7 Just plain junk data!
3.8 The bottom line-what is mandated?
4 Data Taxonomy.
4.1 A new data management consciousness level.
4.2 Data personification.
4.3 Classification model and framework.
4.4 Customer reporting.
4.5 Summary.
5 Email Retention.
5.1 Email management to achieve compliance.
5.2 What is archiving?
5.3 How should organisations manage their email records?
5.4 Email retention policies are for life-not just for Christmas.
5.5 How companies can gain competitive advantage using compliance.
5.6 What laws govern email retention?
5.7 Write once, secure against tampering.
5.8 Storage recommendations for email.
5.9 Conclusion.
6 Security.
6.1 Alerting organisations to threats.
6.2 Protecting data and IT systems.
6.3 Conclusions.
Reference.
7 Data Lifecycles and Tiered Storage Architectures.
7.1 Tiered storage defined.
7.2 RAID review.
7.3 Tape-based solutions.
7.4 Recoverability of data: you get what you pay for.
7.5 Conclusion.
Bibliography.
Recommended Reading.
8 Continuous Data Protection (CDP).
8.1 Introduction.
8.2 CDP data-taps.
8.3 CDP operations.
8.4 Conclusion.
9 What is the Cost of an IT Outage?
9.1 Failure is not an option.
9.2 Finding the elusive ROI.
9.3 Building a robust and resilient infrastructure.
9.4 Conclusion-Analysing business impact.
10 Business Impact.
10.1 Business impact.
10.2 The paradigm shift in the way IT does business.
10.3 The Holy Grail: standard software platform.
10.4 Summary.
Bibliography.
11 Integration.
11.1 Understanding compliance requirements.
11.2 Understanding hardware and its constructions.
11.3 Understanding user expectations.
11.4 Knowing the capabilities of your data management tools.
11.5 Solution integration-business data and workflow applications.
11.6 A ten-point plan to successful DLM, ILM and TLM strategy.
11.7 Conclusion.
References.
Index.
