A logistic regression is a model that is appropriate to use when the dependent variable is binary, i.e. 0s and 1s, True or False, Yes or No. The logistic regression is part of the regression analysis library and could therefor be interpreted as a predictive analytics model.

With the rise of cloud computing and big data, columnar databases have increased in popularity. One of the main reasons for its rise in popularity is due to its efficiency for analytical queries and therefore business intelligence tools. This post aims to identify the key differences between these two database types and point you in the right direction for your future data warehouse.