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Web Analytics: Advanced Data Analysis in Excel (II.)

Intermediary transaction http://www.aliyun.com/zixun/aggregation/6858.html ">seo to diagnose Taobao guest cloud host technology Hall last blog has described how to install Advanced Data analysis features of Excel, and introduced regression analysis   , to tell the truth length is a little long, mainly installed that screenshot more; This article mainly introduces descriptive statistics, sampling analysis and histograms. First, the description of statistics in the median, the number of data distribution ...

Big data analysis old birds give rookie learn from the experience of the younger brothers

The author of this article: Wuyuchuan &http://www.aliyun.com/zixun/aggregation/37954.html ">nbsp; The following is my experience in the past three years to do all kinds of measurement and statistical analysis of the deepest feelings, or can be helpful to everyone. Of course, it is not ABC's tutorial, nor detailed data analysis method introduction, it is only "summary" and "experience." Because what I have done is very miscellaneous, I do not learn statistics, mathematics out ...

Statistical significance test of data in Web Analytics

Intermediary transaction http://www.aliyun.com/zixun/aggregation/6858.html ">seo diagnose Taobao guest cloud host technology Hall in the website analysis, often do site optimization test, will compare the conversion rate of different schemes, such as bounce rate, Order Purchase rate, button clicks, etc., will also record the visitors or customers detailed data performance. But many times the difference is very small, whether it is to maintain the status quo or full use of the content of the new plan, it is difficult to have a conclusion, so ...

Large Data Technology stickers: Building a guided data mining model

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 similar ...

Large Data Technology stickers: Building a guided data mining model

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 ...

Website Data analysis: Parameter estimation and confidence interval

Intermediary trading http://www.aliyun.com/zixun/aggregation/6858.html ">seo diagnose Taobao guest Cloud host Technology Hall we always want to be able to look at some sample data to explore the overall performance characteristics of the data, In the site data analysis is also the case, we try to infer from the recent days of data performance to speculate on the current site's overall situation is how, there is no better or worse signal, ...

How enterprise Big Data starts: from small data to big data

At present, there are many talk about large data at home and abroad, mostly talk about the operation level, or from the service side, the service side raised more. I want to communicate with you the problem is as a variety of enterprises, especially the client side of the enterprise, the big data and what their relationship, or as the enterprise side how to participate, this is the biggest problem facing the enterprise now. The main answer to this question is that large data should start small. Because now many enterprises are facing the biggest problem is not how to use large data, but some of the internal small data integration problems, or small data are not good in the case of how to use ...

What is the real face of big data?

In this era, the words "Big Data", "Cloud storage" and "cloud computing" are absolutely the first of your vision and hearing in a group of mixed Internet, whether it's technology or product or operation or business. But what is big data? What's the big data for? What is it? It takes a cool look.   In fact, big data is not a iffy technology, but a common skill, a skill to discover value from data. I. Four misconceptions about large data 1. One big data is the data big "everbright is not enough ...

How enterprise Big Data starts: from small data to big data

At present, there are many talk about large data at home and abroad, mostly talk about the operation level, or from the service side, the service side raised more. I want to communicate with you the problem is as a variety of enterprises, especially the client side of the enterprise, the big data and what their relationship, or as the enterprise side how to participate, this is the biggest problem facing the enterprise now. The main answer to this question is that large data should start small. Because now many enterprises are facing the biggest problem is not how to use large data, but some of the internal small data integration problems, or small data are not good in the case of how to use ...

Analysis and discussion on the basic structure of website Data Warehouse

Intermediary transaction SEO diagnosis Taobao guest Cloud host technical Hall The purpose of the data Warehouse is to build an integrated data environment for 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 ...

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