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Jessica May
  • Beijing
  • China, mainland
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Jessica May's Page

Profile Information

Short Bio:
Business analytics and data process software professional, BI technology consultant
My Website or LinkedIn Profile (URL):
http://www.raqsoft.com
Field of Expertise:
Business Analytics, Marketing Databases
Years of Experience in Analytical Role:
11
Professional Status:
Manager
Interests:
Networking
What is your Favorite Data Mining or Analytical Website?
http://www.datasciencecentral.com/
Your Company:
Raqsoft co.,ltd
Industry:
BI

Jessica May's Blog

How to Compute Moving Average in R Language and Python

Posted on October 14, 2014 at 1:00am 1 Comment

A moving average is used to smooth out a time series. Computing moving average is a typical case of ordered data computing. Its basic computing method is to create a subset composed of N consecutive members of a time series, compute the average of the set and shift the subset forward one by one. The following example teaches you how to compute moving average in R language.…

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A use case to read and analyze Excel data in Java

Posted on October 8, 2014 at 12:26am 0 Comments

Generally, Java programmers use poi or other open source packages to read and compute Excel data. These open source packages support low-level programming, which increases the overall learning cost and complicates the operation. But with the help of esProc, Java can avoid these problems.…

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Data alignment join in Java for easier text analytics

Posted on September 28, 2014 at 8:00am 0 Comments

The join statements of the database can be used conveniently to perform the operation of alignment join. But sometimes the data is stored in the text files, and to compute it in Java alone we need to write a large number of loop statements. This makes the code cumbersome. Using esProc to help with programming in Java can solve the problem easily and quickly. Let’s look at how this works…

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Calculation cases of Link Relative Ratio and Year-on-year Comparison in data analytics

Posted on September 22, 2014 at 2:00am 0 Comments

Cross-row and group computation often involves computing link relative ratio and year-on-year comparison. Link relative ratio refers to comparison between the current data and data of the previous period. Generally, it takes month as the time interval. For example, compare the sales amount of April with that of March, and the growth rate we get is the link relative ratio of April. Hour, day, week and quarter can also be used as the time…

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