Every data science project starts with business understanding$-$ a business problem. After the business problem is identified and stated, Data Engineers collect relevant data $($structured$,$ semi$-$structured, or unstructured$)$ to be used to build models for a successful resolution of the business problem. Then, Data Analysts use data wrangling tools to quickly view relevant characteristics of their datasets and identify $\_\_\_\_\_\_\_\_\_\_\_$ that are likely to result in interesting observations.