Power BI Analytics Project

In this project, I worked with a dataset from Dataquest to explore and analyze data using Power BI. The project involved creating multiple visualizations and performing detailed data analysis to uncover insights. Here’s what I accomplished:

1. DAX Statistical Functions:

   • Used DAX formulas to calculate statistical metrics like sum, average, max, min, count, standard deviation, variance, and median. These helped analyze trends and summarize key information in the data.

2. Histogram with Groups and Bins:

   • Created a histogram by grouping data into 30-day bins, which allowed me to analyze trends in subscribers over time.

3. TOP N Analysis:

   • Applied a TOP N filter using DAX to identify the top-performing countries and channels by total signups and subscriptions.

4. Outlier Detection:

   • Built a scatter plot to detect outliers in the data, making it easier to identify unusual patterns.

5. Time Series Analysis with Play Axis:

   • Created animated visuals using the Play Axis feature to analyze how total signups and subscribers evolved over time.

6. Clustering in Scatter Plot:

   • Performed clustering in a scatter plot and identified 4 clusters in the dataset. This helped segment the data based on similarities.

7. Group Data for Analysis:

   • Grouped channels like "Organic" and "Unknown" into a custom group called HighSubscriberGroup, which included a total of 36,103 subscribers.

8. Binned Subscribers by 30-Day Period:

   • Analyzed subscribers by grouping them into 30-day bins to observe time-based subscription patterns.

9. Analyze Distribution with the Analyze Feature:

   • Used the Analyze feature in Power BI to explore factors affecting the distribution of subscribers, such as channels and regions.

10. Teach a Lesson to Power BI:

    • Utilized the Key Influencers visual to teach Power BI how to identify what factors influence subscriptions the most.