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Live Data

Data Collocation Tiers: What They Mean and What You Need

When a data colocation company talks about "tiers", they are referring to the different levels of reliability they can offer for your server maintenance and storage. This grading system ranges from Tier I to Tier IV, with IV being the topmost reliability in power, cooling and availability. Prices can rise significantly based on the tier level offered by a data center. A government's intelligence department would use Tier IV, however most companies can benefit fine from a Tier I or Tier II system and get the most for their buck. Choosing the right colocation center based on tier performance can differ according to the operational needs of a specific company. For VoIP telephone services, it would be more important to make sure servers aren't going down for a few hours at unexpected notice since customers are heavily involved. For others, a basic Tier I will meet business needs while maintaining an economical balance for return on investment.

Tier I

The Tier I system is the longest living data colocation design having been around since the 1960s. It offers one pathway with no redundancies, which are used in case the main power pathway fails. Floor height, which is important to prevent damage against floods and can determine the effectiveness of a cooling system, stands at about 12 inches. The weight capacity of the platform on which the server stands is about 85 pounds per square foot. Weight capacity is important when considering the chances of a collapse (if say, you live on the earthquake-prone West coast of North America). Yearly downtime is estimated to be about 29 hours due to site infrastructure deficiencies (which are inevitable). Costs can be about $450 per square foot a month.

Tier II

Tier II holds all the qualities of a Tier I system except that the main feature is its redundant component, providing an alternative power source in the event the main circuit supply fails. Floor height is at 18 inches instead of 12 and the weight capacity is at 100 pounds instead of 85. Downtime is calculated to be around 22 hours a year. A Tier II system can cost about $650 per square foot a month.

Tier III

Tier III is a level up from Tier II, only now you have multiple electrical delivery paths that act independently, with any given circuit providing power to the servers at a time. In other words, instead of having only one circuit delivering power to equipment, with a back-up plug in that 'sleeps' until needed, now you have separate circuits connecting to the multiple plug-ins located in the equipment for more reliability. Floor height jumps to anywhere between 30 to 36 inches and weight capacity increases to 150 pounds. Downtime dramatically decreases to just below 2 hours a year, but costs soar to $900 per square foot of construction. Major telecoms or non-vital government departments might usually opt for a Tier III system.

Tier IV

Finally, the ultimate in performance, the Tier IV system. This design has everything of the first three Tiers plus added layers of protection, using multiple redundancies for each piece of equipment. Basically, if one power hub goes out, let alone the circuits and plugs in involved at the lower electrical layers, another will take over. In extreme cases, there will be back-ups for back-ups. Floor height remains at 30 to 36 inches since anything higher will not affect security or cooling greatly and might, in fact, create dust-build up that can cause trouble for servers in the long run. The weight capacity can exceed 150 pounds, depending on the data center's specific infrastructure design. Downtime is at an all-time low of less than one hour per year, but costs are a hefty estimate of $1,100 per square foot a month or more.

As mentioned above, Tier I or, preferably Tier II systems will do fine for most business needs. It's only the big players that will need higher reliability and actually have the resources to finance investments in Tier III or Tier IV systems. Speaking with a data center's representatives about your server needs and their site infrastructure will help aid your decision greatly. Also keep in mind that the Tier system is only one of the many qualities to look for in selecting a data center to store your server. Other important factors not to be neglected are security, cooling, remote assistance and, of course, price.

About the Author

Saleh Tousi is the CEO of SmarttNet, a Vancouver IT company offering comprehensive business Internet services including
Vancouver colocation
since 1995.


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Data Mining


Data Mining


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The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it's still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge. Since the previous edition's publication, great advances have been made in the field of data mining. Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data. Each chapter is a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. This is the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges. * Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects. * Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields. *Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

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"Practical Data Migration" gives you techniques and strategies for ensuring that your data migration project achieves maximum returns for your company. This book provides a structured approach to data migration enabling you to get the right data, in the right place, at the right time. Every new computer system needs start up data before it can be put into operation and realize the benefits implicit in new software. The success of every company merger, de-merger or restructuring relies on the success of merging or dividing data. Often, data migration goes wrong - as recently highlighted by the media in organizations as crucial as the NHS, The Inland Revenue, and the Department of Work and Pensions. To realize return on investment, data loaded at 'go live' should be the best available; to maximize the utility of the novel features of a new computer system data should also be the most appropriate obtainable. There has been no published method for finding and re-processing data in legacy systems - until now. "Practical Data Migration" provides tried and tested approaches, strategies and techniques for ensuring your data migration project goes smoothly with minimal disruption to your organization. "Practical Data Migration" is not slanted towards any particular operating system, target system, data migration tool or industry. It is a business facing approach that will work, and has worked, in any business environment. This is a practical guide to running successful data migration projects containing original methods, an example project as a model of best practice and ideas on rescuing data migration projects that have gone wrong. "Practical Data Migration" contains a wealth of real life examples and hints that have been shown to work in practice. It explains how to maximize the benefits of data migration, both as part of a new system implementation and as a key tool in business merger and de-merger activities. It blends real life experiences, with cutting edge developments from the Rapid Application Development arena, as well as more traditional metadata modelling concepts, and offers clear definitions of commonly used jargon that surrounds the subject. "Practical Data Migration" debunks the mysteries that surround this subject, providing a template for judging the performance of in-house or brought in skills. It encourages adaptation to local cultural or environmental constraints, but provides a model of best practice that should be the starting point for their project specific implementation of the method. For the IT practitioner who has been given responsibility for managing a data migration project, it provides techniques well-founded in practice, a host of hints and tips and anecdotes to reassure that the author has "been there, done that."

Data Mining: Concepts and Techniques


Data Mining: Concepts and Techniques


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This is the third edition of the premier professional reference on the subject of data mining, expanding and updating the previous market leading edition. This was the first (and is still the best and most popular) of its kind. Combines sound theory with truly practical applications to prepare students for real-world challenges in data mining. Like the first and second editions, Data Mining: Concepts and Techniques, 3rd Edition equips professionals with a sound understanding of data mining principles and teaches proven methods for knowledge discovery in large corporate databases. The first and second editions also established itself as the market leader for courses in data mining, data analytics, and knowledge discovery. Revisions incorporate input from instructors, changes in the field, and new and important topics such as data warehouse and data cube technology, mining stream data, mining social networks, and mining spatial, multimedia and other complex data. This book begins with a conceptual introduction followed by a comprehensive and state-of-the-art coverage of concepts and techniques. Each chapter is a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. Wherever possible, the authors raise and answer questions of utility, feasibility, optimization, and scalability. relational data. -- A comprehensive, practical look at the concepts and techniques you need to get the most out of real business data. -- Updates that incorporate input from readers, changes in the field, and more material on statistics and machine learning, -- Scores of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects. -- Complete classroom support for instructors as well as bonus content available at the companion website

Data Mining (Hardcover)


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The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it`s still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge. Since the previous edition`s publication, great advances have been made in the field of data mining. Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data. Each chapter is a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. This is the resource you need if you want to apply today`s most powerful data mining techniques to meet real business challenges. * Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects. * Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields. *Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Data Communications & Teleprocessing Systems


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"Data communications is still the fastest-growing aspect of computing. The subject has always been made artificially complex, and modern developments tend to complicate the issue even more. Satellite communications, local area networks, optical fibres, digital networks, the integrated services digital network, and the open system interconnection are examples of the rapid growth in the communications industry. Regardless of where you live, there are still universal principles that lie at the heart of all data communications. This book deals with these principles and addresses them in simple terms and in a logical sequence so that we will be able to locate easily the essential information we need to know to have a good understanding of data communications."

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