Nice to meet you too @CristiƔn Munizaga! I wouldn't necessarily compare these two tools as they serve different needs. Pandas profiling is mainly used to profile the data to get a better understanding how the data behaves. For example, if you want to see the amount of null values in a specific column you can profile your table and learn how many nulls you have in your columns. Elementary is more a data observability solution that enables you to monitor the data and validate that there are no issues in the data over time. So now when you have an idea how many nulls you have in a column, you can decide if you want to monitor the amount of null values over time using Elementary. A common practice that we see across our users is that they profile the data using tools like pandas profiling and then they know what tests are important for them to define with Elementary on their data sets. What do you think about this approach? does it make sense? Down the road and in order to simplify this process we might add data metrics and profiling of the data to Elementary as well but in general these are complementary tools which work nicely together.