Valid Data Definition

In the internet age, large data is hot, many people must pro data, but can really say that the big data is not much, not to mention how to use large data to dig out the great business value. 　　How do you define large data? What are the characteristics of large data? This paper aims to clarify the concept of large data, illustrate the application of large data and explore the future development of large data. 　　Q1: Is big Data a commercial hype? The industry's definition of large data is 4 "V": Large volume (Volume), multiple species (produced), fast (velocity) ...

The purpose of data warehouse is to build an integrated data environment oriented to analysis, and to provide decision support for enterprises (Decision-support). In fact, the data warehouse itself does not "produce" any data, at the same time does not need to "consume" any data, data from the outside, and open to external applications, which is why called "Warehouse", not called "factory" reasons. Therefore, the basic structure of the data warehouse mainly contains the data inflow and outflow process, can be divided into three layers-source data, data Warehouse, data application: From the graph can be seen data warehouse data from ...

Foreword 2012 years time "big data" the argument gradually appears in our vision, to 2013 years "The Big Data" became the hottest discussion topic, then what is the big data, the big data actually has what magic to let the person go hot to discuss? Let's look at the definition of large data: "Big Data", Or the vast amount of data, refers to the volume of data involved in the large scale to be unable to pass the current mainstream software tools, within a reasonable time to achieve capture, management, processing, and collation to help the business decision-making more positive purpose information. (In Victor Maire-...

October 24, China TMT International Chamber of Commerce in Beijing Fairmont Center held a forum on the theme of "Big Data big impact", will be well-known it commentators Xie on the current speculation on the Big Data topic, made a wonderful speech, causing the audience enthusiastic response. China Broadband Industry fund chairman of the site reviews, "This is my six months to hear the best about big data speech." In the cloud will be a speech finishing, the full text is as follows: Well-known it commentators Xie I have been about the past six months or so time to write 10 articles on large data, the magazine also published, this is just out ...

Large data is a vague expression of large-scale phenomena. 　　The term has now been overheated by entrepreneurs, scientists, governments and the media. Five years ago, a Google research team announced a remarkable achievement in the world's top science magazine Nature. The team can track the spread of flu in the United States, which does not depend on any medical examination. They are tracking even faster than the CDC. Google's tracking results are only a day's delay, and the CDC needs to compile a large number of physicians ' diagnoses to get a spread of the trend chart ...

This article originally contained the FT website, original title: Big Data:are We making a big mistake, it seems that I saw a bit late, but still share it. Because it does discuss some of the issues I've been thinking about recently, it's a speculative article. 　　If you've never known big data before, this can be considered a primer. This article is only opinion, because the query is more simple than the proof, but the big data is now hot, these negative comments, if as a conversation to collect, is also good ...

The previous article introduced some basic concepts of data quality, data quality control as the basic link of Data Warehouse, is the foundation of guaranteeing the application of upper layer data. Data quality assurance consists mainly of data Profiling, data auditing and data revision (information correcting) three parts, the previous article describes the content of the information Profiling, Profiling the data in the process of obtaining the summary statistics, so the following ...

Cloud computing and large data are now hot topics, and how to combine the two together to achieve large data projects on the cloud is a new practice area. Senior data expert David Gillman, based on his own experience, lists the basic elements that need to be considered in the cloud's large data scenarios, including real-time indexing of data, free-mode search and analysis, monitoring of data, and providing real-time alerts to help users better assess and select solutions. When it comes to implementing large data projects on the cloud, David highlights three real-time elements, real-time indexing, real-time data, and real-time monitoring. Have a ...

Cloud computing and large data are now hot topics, and how to combine the two together to achieve large data projects on the cloud is a new practice area. Senior data expert David Gillman, based on his own experience, lists the basic elements that need to be considered in the cloud's large data scenarios, including real-time indexing of data, free-mode search and analysis, monitoring of data, and providing real-time alerts to help users better assess and select solutions. When it comes to implementing large data projects on the cloud, David highlights three real-time elements, real-time indexing, real-time data, and real-time monitoring. Have a ...

Cloud computing and large data are now hot topics, and how to combine the two together to achieve large data projects on the cloud is a new practice area. Senior data expert David Gillman, based on his own experience, lists the basic elements that need to be considered in the cloud's large data scenarios, including real-time indexing of data, free-mode search and analysis, monitoring of data, and providing real-time alerts to help users better assess and select solutions. When it comes to implementing large data projects on the cloud, David highlights three real-time elements, real-time indexing, real-time data, and real-time monitoring. Have a ...