Showing posts with the label implementing ideas

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The Quick and Easy Way to Analyze Numpy Arrays

The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array. Sum You can find the sum of Numpy arrays using the np.sum() function.  For example:  import numpy as np  a = np.array([1,2,3,4,5])  b = np.array([6,7,8,9,10])  result = np.sum([a,b])  print(result)  # Output will be 55 Mean You can find the mean of a Numpy array using the np.mean() function. This function takes in an array as an argument and returns the mean of all the values in the array.  For example, the mean of a Numpy array of [1,2,3,4,5] would be  result = np.mean([1,2,3,4,5])  print(result)  #Output: 3.0 Standard Deviation To find the standard deviation of a Numpy array, you can use the NumPy std() function. This function takes in an array as a par

An effective methodology for BI Implementation

Given below is an approach that one could follow to ensure an effective implementation of any BI project. Steps in Business Intelligence Project Requirements elicitation is the most important activity in a BI exercise. We need to very clearly understand the motivation behind the management's need for analytics and their short-term, medium-term and long-term objectives.  You may conduct a workshop with all stakeholders to understand these requirements. Identifying and involving all stakeholders in the requirements discussion is very important to gain buy-in for the BI initiative throughout the enterprise. Anyone would like to see a sample of analytics and play around a little to get a sense of the benefit/impact of analytics. Hence developing a quick prototype and showcasing the same to all stakeholders will help you get the necessary impetus for the initiative.  CAVEAT: Please ensure that the prototype development does not take more than two weeks. References Read mo