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Questions On Using Data Analytics

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How-To: Data Analytics By Zach Hazen | Submitted On November 15, 2015 Recommend Article Article Comments Print Article Share this article on Facebook Share this article on Twitter Share this article on Google+ Share this article on Linkedin Share this article on StumbleUpon Share this article on Delicious Share this article on Digg Share this article on Reddit Share this article on Pinterest This is a very simple post aimed at sparking interest in Data Analysis. It is by no means a complete guide, nor should it be used as complete facts or truths. I 'm going to start today by explaining the concept of ETL, why it 's important, and how we 're going to use it. ETL stands for Extract, Transform, and Load. While it sounds like a very …show more content…

What programs am I going to use to transform the data? What am I going to do once I have all the numbers? What kind of visualizations will emphasize the results? All questions you should have answers to. Step 2: Get Your Data (EXTRACT) This sounds a lot easier than it actually is. If you 're more of a beginner, it 's going to be the hardest obstacle in your way. Depending on your use there are typically more than 1 way to extract data. My personal preference is to use Python, which is a scripting programming language. It is very strong, and it is used heavily in the analytic world. There is a Python distribution called Anaconda that already has a lot of tools and packages included that you will want for Data Analytics. Once you 've installed Anaconda, you 'll need to download an IDE (integrated developer environment), which is separate from Anaconda itself, but is what interfaces with the programs itself and allows you to code. I recommend PyCharm. Once you 've downloaded all of the things necessary to extract data, you 're going to have to actually extract it. Ultimately, you have to know what you 're looking for in order to be able to search it and figure it out. There are a number of guides out there that will walk you more through the technicalities of this process. That is not my goal, my goal is to outline the steps necessary to analyze data. Step 3: Play With Your Data (TRANSFORM) There are a number of programs and ways to accomplish this. Most aren 't free,

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