Data Takes Over Enterprise

Just a few years ago, duplicate data deletion was a stand-alone feature, and data deduplication offered an alternative to the storage systems in the enterprise backup and archiving department. It also found new uses in cloud gateways to filter out unnecessary chunks of data before entering the array or virtual tape library. Now, it has become a unified computing system of the pre-integrated functionality. Understanding how to use this technology more effectively becomes a requirement.   At the same time IT managers should re-examine storage issues and ask the vendors who provide them with storage. 1. Data de-duplication technology for backup performance ...

The traditional It delivery model has many problems, whether from the delivery cycle or from planning to experience, there are a lot of difficult to determine the factors, many times because of some subjective or objective reasons cause project lag or miscarriage. Today to recommend the SaaS Pioneer Enterprise called Cloud technology, founder Shipeixin is to see the current enterprise IT delivery pain point, in September 13 began to build the first fully automatic and full self-service enterprise cloud service platform. It can be considered "a platform to subvert the existing enterprise IT delivery model, a community of application experience and software learning, a professional it person ...

This paper is an excerpt from the book "The Authoritative Guide to Hadoop", published by Tsinghua University Press, which is the author of Tom White, the School of Data Science and engineering, East China Normal University. This book begins with the origins of Hadoop, and integrates theory and practice to introduce Hadoop as an ideal tool for high-performance processing of massive datasets. The book consists of 16 chapters, 3 appendices, covering topics including: Haddoop;mapreduce;hadoop Distributed file system; Hadoop I/O, MapReduce application Open ...

The purpose of data mining is to find more quality users from the data. Next, we continue to explore the model of the guidance data mining method. What is a guided data mining method model and how data mining builds the model. In building a guided data mining model, the first step is to understand and define the target variables that the model attempts to estimate. A typical case, two-dollar response model, such as selecting a customer model for direct mailing and e-mail marketing campaigns. The build of the model selects historical customer data that responds to similar activities in the past. The purpose of guiding data mining is to find more classes ...

Zhang Fubo: The following part of the forum is mainly four guests, talk about cloud practice. Beijing First Letter Group is the Beijing government's integration company, mainly responsible for the capital window of the construction, they are also in the domestic, in the government industry earlier in a company, as the first letter Group Technical Support Center General Manager Zhang Ninglai for us to do the report. Zhang: Good afternoon, we have just introduced, I am from Beijing First Letter Development Co., Ltd., I bring today is the result of our practice in cloud computing technology these years. Today is mainly divided into three parts, we mainly do is the field of e-government applications, we are mainly ...

The data again "big" no useful is equal to zero, to collect "slow data" "Live data" on the internet every moment in the production of data, people's lives everywhere in the various devices, such as computers, mobile phones, smart appliances, sensors and so on, can always leave traces of human behavior, real-time data generation, These increased geometric levels of data deposition on the Web, become large data. These large numbers of data again "big" no useful is equal to zero, to collect "slow data" "Live data ...

"Tenkine Server Channel" Enterprise Create exclusive data center, first look at their own pockets, how much money you can afford? 　　Consider the following points: How much does it cost to build a site? 　　How much does it cost to purchase and build hardware and software? 　　Daily operation and maintenance management, how much does it cost? 　　How much does it cost to maintain upgrades on a regular basis? Lin Lin all sorts of add up, the price is not expensive. So the cost of building data centers and investing in multiple investments is obvious. Please look at the following data: "1" Data center It hardware in the technology development cycle ...

Integration strategy Data integration refers to the combination of data from different systems for business users to study different industry behavior and customer behavior data processing methods. In the early days of data integration, data was limited to trading systems and their applications.   The development of business decision is guided by the decision platform, and the limited dataset provides the foundation of creating the decision platform. Data capacity and data types have grown dramatically over the past 30 years, with data warehousing technology from scratch, and infrastructure and technology to meet analysis and data storage requirements. All this has revolutionized the prospects for data integration. ...

First, the initial understanding of large data seems to be overnight, big data becomes one of the most fashionable words in the IT industry. First of all, big data is not a completely new thing, Google's search service is a typical large data use, according to customer demand, Google real-time from the global mass of digital assets (or digital garbage) ...

Integration strategy Data integration refers to the combination of data from different systems for business users to study different industry behavior and customer behavior data processing methods. In the early days of data integration, data was limited to trading systems and their applications.   The development of business decision is guided by the decision platform, and the limited dataset provides the foundation of creating the decision platform. Data capacity and data types have grown dramatically over the past 30 years, with data warehousing technology from scratch, and infrastructure and technology to meet analysis and data storage requirements. All this has revolutionized the prospects for data integration. ...