Chapter 8 – Using Data Profiling for Exploratory Data Analysis (EDA)

1. B – To summarize data characteristics and gain insights – EDA serves as a pivotal phase in the data analysis workflow, aiming to summarize data characteristics, identify patterns, detect outliers, and gain insights into data structure.
2. A – Identifying potential outliers – Benefits of a well-carried-out EDA include familiarizing analysts with the dataset, assessing data scope, identifying data quality issues, revealing patterns and trends, and aiding in the selection of appropriate modeling techniques.
3. C – Column Transformation – Power BI’s data profiling capabilities include the following:
   • Column Quality Assessment
   • Column Distribution Analysis
   • Column Profile Views
4. B – Within Power Query, open the View tab – Data profile views can be accessed in Power Query by opening Power Query and selecting the View tab.
5. B – Histograms...