Showing posts with the label Teradata developer course

Featured Post

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

Top Teradata Course details that you need to learn

Teradata is most popular database among data warehousing projects. You will learn Teradata from any institute you want. My post intention is you just take a look on course contents you need to learn. Course Contents You Need to Look Before You Start Related: Top Data warehousing Interview Questions Introduction to Teradata Data warehousing concepts and SCD’s OLTP & OLAP Teradata Architecture & Physical Design Teradata Vs. Other RDBMS BYNETPEs AMPs Vprocs Clique Cluster Data Storage Data Distribution Data Access Teradata Space Management Fault Tolerance Data Protection Teradata Indexes and Performance Tuning and Optimization UPI – Unique Primary Index NUPI – Non Unique Primary Index USI – Unique Secondary Index NUSI – Non Unique Secondary Index PPI – Partition Primary Index MLPPI – Multilevel Partition Primary Index STJI – Single Table Join Index MTJI – Multi Table Join Index AJI – Aggregate Join Index Global Temporary Tables and Vola