Input datasets used for analysis can be large and if all of your data is stored in oracle database, downloading them into excel, moving them across file servers and reading them into python is just, lets say, not so smart move. Also, with the number of iterations, the overload of this process is just an… Read More Handling Oracle DB data using Python
A series is said to be stationary when the statistical properties (importantly mean, variance and auto-correlation from time series forecasting perspective) of the series is time invariant (i.e. don’t vary with the time). In simpler terms, when observed across any regular time intervals they will remain the same. However, this is a more of an… Read More Why Non-Stationarity shouldn’t be ignored in Time Series Forecasting?
Packages in R have made analytical solution development a lot easier by providing ready to use pre-build functionalities, saving analysts a lot of time and effort. Also, more importantly, which also happens to be a fact, packages have extended the ability to use a far greater, wider and deeper knowledge and skill with a lesser… Read More 10 steps to build a R Package