Summary  
This chapter covers how to programmatically profile and explore dataset columns by computing summary statistics, value distributions, and quality metrics to identify and address issues such as missing values, misspellings, outliers, and duplicate rows.

General domain of usage  
Data cleaning and preprocessing

We will use the **Column Profiler** in Power Query to evaluate our bicycle dataset to identify errors, necessary transformations, and other data quality needs. The Column Profiler provides detailed insights into the data, including **value distribution, data quality, and summary statistics**. By analyzing these metrics, we can pinpoint issues such as duplicate or missing values, understand the distribution of our data, and decide on the necessary transformations to clean and prepare our dataset for analysis.


Power BI is an essential tool for any aspiring data analyst or business professional. Learn how to transform raw data into insightful visualizations and interactive dashboards, connect to various data sources, and create compelling reports for informed decision-making.

Dive into the world of Power BI and build a solid foundation. You'll cover everything from installation and setup to connecting data sources and creating your first report.

Explore essential data preparation techniques, including cleaning, transforming, and combining multiple data sources. You'll also tackle handling missing values, data profiling, and various data manipulation methods.


Master the fundamentals of data modeling, from understanding data models and creating relationships to getting the hang of DAX basics. You'll also learn to create measures and calculated columns.


Discover various visualization techniques and customize visuals for better insights. You'll also explore advanced features like slicers, filters, and drill-down/drill-through capabilities to enhance your data analysis.


Boost the usability and storytelling power of your reports by using themes, configuring report pages, and leveraging advanced features like the Analyze feature and identifying outliers. You'll also create groups, bins, and clusters for deeper insights.


Data Profiling and Exploration

Awesome!

Data Profiling and Exploration