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2.英文原版,PDF格式;
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Data analytics involves taking some data and exploring and testing it to produce insights. You can put a variety of names on this process from Business Intelligence to Data Science but fundamentally the approach does not change. Understand a problem, identify the right data, prepare the data appropriately, and run the appropriate analysis on it to find insights and report on them. This is difficult. You are probably seeing this data for the first time. Worse still, the data usually has issues you will only uncover during your journey. Meanwhile, the problem domain must be understood so the data that represents it can be understood. But what is discovered in the data often helps define the problem domain itself.
Faced with this open-ended challenge, many analysts become lost in the data. They explore multiple lines of enquiry. One line of enquiry can invalidate or confirm a previous line. The structure and exceptions in the data are discovered during the process and must be accounted for. Many of the analyses themselves can be executed in a multitude of ways, none of which are categorically correct but instead must be interpreted and justified. Just when you thought you had a handle on the problem, new data arrives and everything you have already done is potentially invalidated. This makes planning, executing, and reproducing data analytics challenging.
If you have ever been in this situation then this book is for you.
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08_Guerrilla_Analytics_A_Practical_Approach_To_Working_With_Data_2015.pdf
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