A Global Landscape of Unicorns Around the World

This was one of the first datasets I had worked on after the completion of Power BI modules from Udemy and the first data analytics challenge hosted by Maven Analytics.

Objective

To analyze the following KPI Metrics:

• Unicorn companies with the highest return on investment
• Timeline to transform an entity into Unicorn
• Concentration (Presence) of Unicorns across the globe
• Key investors who have funded maximum unicorns
• Growth Patterns
• Valuation and Funding Analysis

Procedure

For this project, I used Power BI's GET DATA feature to import the data and select 'Text/CSV' since it is stored in a CSV format. After loading the data into the power query editor, I checked if all the columns followed the correct data type and whether the headers were promoted before making all the necessary changes to the table. I named the table ‘Unicorn Companies’ for identification. For this table, I had to update the data types and replace the values of certain columns to analyze and visualize the data better. I added an ID column for identification and help in data modelling. I created a duplicate table of Unicorn Companies and renamed it as ‘Investors Table’. Since I needed only three columns, namely the ID column, Company Name and Investors column, I deleted all the remaining columns and made the necessary changes to the rest. After making changes, both tables were loaded into power bi canvas for data modelling. Using the ID column in both tables, a one-to-many relationship with one way filter was created by connecting the ID column from the Unicorns Table to the ID column of the Investors Table. Calculated columns and measures were created to analyze the required KPIs. To visualize these KPIs, I have created a dashboard of different cards, charts and graphs with the addition of filters to regulate the data flow as per the need of the analysis.

The static image of the resulting dashboard is revealed below. (Click on the image to view it.)

Your feedback on this project is much appreciated.