Databricks Databricks-Certified-Professional-Data-Scientist - Databricks Certified Professional Data Scientist Exam

In the data preparation phase of the Data Analytics Lifecycle, the data range and distribution can be obtained. If the data is skewed, viewing the logarithm of the data (if it's all positive) can help detect structures that might otherwise be overlooked in a graph with a regular, nonlogarithmic scale.

When preparing the data, one should look for signs of dirty data, as explained in the

previous section. Examining if the data is unimodal or multimodal will give an idea of how many distinct populations with different behavior patterns might be mixed into the overall population. Many modeling techniques assume that the data follows a

normal distribution. Therefore, it is important to know if the available dataset can match that assumption before applying any of those modeling techniques.