Emc information storage management book free download

Not long ago, information storage was seen as only a bunch of disks or tapes attached to the back of the computer to store data. Even today, only those in the storage industry understand the critical role that information storage tech- nology plays in the availability, performance, integration, and optimization of the entire IT infrastructure.

Over the last two decades, information storage has developed into a highly sophisticated technology, providing a variety of solutions for storing, managing, connecting, protecting, securing, sharing, and optimizing digital information. With the exponential growth of information and the development of sophisti- cated products and solutions, there is also a growing need for information stor- age professionals. IT managers are challenged by the ongoing task of employing and developing highly skilled information storage professionals.

This book is designed and developed to enable professionals and students to achieve a comprehensive understanding of all segments of storage technology. This book has 16 chapters, organized in four sections. Advanced topics build upon the topics learned in previous chapters. This book has a supplementary website that provides additional up-to-date learning aids and reading material. EMC Academic Alliance Universities and colleges interested in offering an information storage and man- agement curriculum are invited to join the Academic Alliance program.

This program provides comprehensive support to institutes, including teaching aids, faculty guides, student projects, and more. EMC Proven Professional is the premier certifica- tion program that validates your knowledge and helps establish your credibility in the information technology industry. Structure and Organization of FC Data 6. NAS Devices 7. Host-Based Remote Replication We have become information Key Concepts Data and Information dependents of the twenty-first century, liv- ing in an on-command, on-demand world that Structured and Unstructured Data means we need information when and where it Storage Technology Architectures is required.

We access the Internet every day to perform searches, participate in social network- Core Elements of a Data Center ing, send and receive e-mails, take pictures and Information Management videos through digital cameras, and satisfy many other personal and professional needs. Equipped Information Lifecycle Management with a growing number of content-generating devices, more information is being created by individuals than by businesses. Information created by individuals gains value when shared with others.

When created, information resides locally on devices such as cell phones, cameras, and laptops. To share this information, it needs to be uploaded via networks to data centers. It is interesting to note that while the majority of information is created by individuals, it is stored and managed by a relatively small number of organizations. Figure depicts this virtuous cycle of information. The importance, dependency, and volume of information for the business world also continue to grow at astounding rates.

Businesses depend on fast and reliable access to information critical to their success. Some of the business applications that process information include airline reservations, telephone billing systems, e-commerce, ATMs, product designs, inventory management, e-mail archives, Web portals, patient records, credit cards, life sciences, and global capital markets.

The volume of data that busi- ness must manage has driven strategies to classify data according to its value and create rules for the treatment of this data over its life cycle. These strategies not only provide financial and regulatory benefits at the business level, but also manageability benefits at operational levels to the organization. Data centers now view information storage as one of their core elements, along with applications, databases, operating systems, and networks.

Storage technology continues to evolve with technical advancements offering increas- ingly higher levels of availability, security, scalability, performance, integrity, capacity, and manageability. Centralized information storage and processing Network Network Wired Wireless Wireless Wired Uploading Accessing information information Users of Creators of information information Demand for more information Figure Virtuous cycle of information This chapter describes the evolution of information storage architecture from simple direct-attached models to complex networked topologies.

It introduces the information lifecycle management ILM strategy, which aligns the infor- mation technology IT infrastructure with business priorities. Chapter 1 n Introduction to Information Storage and Management 5 1.

Storage is a repository that enables users to store and retrieve this digital data. Before the advent of computers, the procedures and methods adopted for data creation and sharing were limited to fewer forms, such as paper and film. This data can be generated using a computer and stored in strings of 0s and 1s, as shown in Figure Data in this form is called digital data and is accessible by the user only after it is processed by a computer.

Video Photo Book Letter Digital Data Figure Digital data With the advancement of computer and communication technologies, the rate of data generation and sharing has increased exponentially. This enables the conversion of various types of content and media from conventional forms to digital formats. This cost benefit has increased the rate at which data is being generated and stored. Inexpensive and easier ways to create, collect, and store all types of data, coupled with increasing individual and business needs, have led to accelerated data growth, popularly termed the data explosion.

Data has different purposes and criticality, so both individuals and businesses have contributed in varied proportions to this data explosion.

The importance and the criticality of data vary with time. Most of the data created holds significance in the short-term but becomes less valuable over time.

This governs the type of data storage solutions used. Businesses generate vast amounts of data and then extract meaningful information from this data to derive economic benefits. Therefore, busi- nesses need to maintain data and ensure its availability over a longer period. Chapter 1 n Introduction to Information Storage and Management 7 Furthermore, the data can vary in criticality and may require special han- dling. For example, legal and regulatory requirements mandate that banks maintain account information for their customers accurately and securely.

Some businesses handle data for millions of customers, and ensures the security and integrity of data over a long period of time.

This requires high- capacity storage devices with enhanced security features that can retain data for a long period. Structured data is organized in rows and col- umns in a rigidly defined format so that applications can retrieve and process it efficiently.

Structured data is typically stored using a database management system DBMS. Data is unstructured if its elements cannot be stored in rows and columns, and is therefore difficult to query and retrieve by business applications. For example, customer contacts may be stored in various forms such as sticky notes, e-mail messages, business cards, or even digital format files such as. Due its unstructured nature, it is difficult to retrieve using a cus- tomer relationship management application.

Unstructured data may not have the required components to identify itself uniquely for any type of processing or interpretation. Businesses are primarily concerned with managing unstructured data because over 80 percent of enterprise data is unstructured and requires significant storage space and effort to manage.

Businesses need to analyze data for it to be of value. Information is the intelligence and knowledge derived from data. Businesses analyze raw data in order to identify meaningful trends. On the basis of these trends, a company can plan or modify its strategy.

Effective data analysis not only extends its benefits to existing businesses, but also creates the potential for new business opportunities by using the information in creative ways.

Job portal is an example. These websites collect the resumes and post them on centrally accessible locations for prospective employers. In addition, companies post avail- able positions on job search sites. In this manner, the job search engine uses data and turns it into information for employers and job seekers. Legal, regulatory, and contractual obligations regarding the availability and protection of data only add to these concerns.

Outages in key industries, such as financial services, telecommunications, manufacturing, retail, and energy cost millions of U. In a computing environment, devices designed for storing data are termed storage devices or simply storage. The type of storage used varies based on the type of data and the rate at which it is created and used. One crucial factor in information handling and decision making is an individual's ability to process information and to make decisions under limitations that might derive from the context: a person's age, the situational complexity, or a lack of requisite quality in the information that is at hand — all of which is exacerbated by the rapid advance of technology and the new kinds of system that it enables, especially as the social web emerges as a phenomenon that business cannot ignore.

And yet, well before there was any general recognition of the importance of information management in organisations, March and Simon [8] argued that organizations have to be considered as cooperative systems, with a high level of information processing and a vast need for decision making at various levels. Instead of using the model of the 'economic man', as advocated in classical theory [9] they proposed 'administrative man' as an alternative, based on their argumentation about the cognitive limits of rationality.

Additionally they proposed the notion of satisficing, which entails searching through the available alternatives until an acceptability threshold is met - another idea that still has currency. In addition to the organisational factors mentioned by March and Simon, there are other issues that stem from economic and environmental dynamics. There is the cost of collecting and evaluating the information needed to take a decision, including the time and effort required.

In particular, established organizational rules and procedures can prevent the taking of the most appropriate decision, leading to sub-optimum outcomes. According to the Carnegie Mellon School an organization's ability to process information is at the core of organizational and managerial competency, and an organization's strategies must be designed to improve information processing capability [15] and as information systems that provide that capability became formalised and automated, competencies were severely tested at many levels.

This environment consists of three interrelated dimensions which continuously interact with individuals, organizations, and systems. These dimensions are the physical, informational, and cognitive. Venkatraman has provided a simple view of the requisite capabilities of an organisation that wants to manage information well — the DIKAR model see above. He also worked with others to understand how technology and business strategies could be appropriately aligned in order to identify specific capabilities that are needed.

Bytheway has collected and organised basic tools and techniques for information management in a single volume. Such an information portfolio as this shows how information can be gathered and usefully organised, in four stages:.

Stage 1 : Taking advantage of public information: recognise and adopt well-structured external schemes of reference data, such as post codes, weather data, GPS positioning data and travel timetables, exemplified in the personal computing press. Shirky provides an overview of these two approaches. Stage 3 : Sifting and analysing: in the wider world the generalised ontologies that are under development extend to hundreds of entities and hundreds of relations between them and provide the means to elicit meaning from large volumes of data.

Structured data in databases works best when that structure reflects a higher-level information model — an ontology, or an entity-relationship model. Stage 4 : Structuring and archiving: with the large volume of data available from sources such as the social web and from the miniature telemetry systems used in personal health management, new ways to archive and then trawl data for meaningful information.

Map-reduce methods, originating from functional programming, are a more recent way of eliciting information from large archival datasets that is becoming interesting to regular businesses that have very large data resources to work with, but it requires advanced multi-processor resources. My preferences. Sign In. Information Storage and Management V4.

Associate Level. Associate — Information Storage and Management Version 4. Step 1 - Complete one of the recommended training options listed below. Option 2: On Demand Class.