This includes the powerBI file used to generate a generic overview dashboard for the PoC

This repository contains the Power BI dashboard project that includes advanced analysis based on the provided dataset. The dashboard aims to provide insights and visualize key metrics related to addresses, ENS names, followers, votes, proposal interactions, NFTs, and associated rewards.

The dataset used for this Power BI project consists of the following columns:

address: The unique identifier for each address.

• ens_name: The Ethereum Name Service (ENS) name associated with each address.
• follow_count: The count of followers for each address.
• follow_count_space: The count of followers categorized as "space" followers.
• follow_count_non_space: The count of followers categorized as "non-space" followers.
• total_votes: The total number of votes received by each address.
• total_proposal_interaction: The total number of interactions on proposals for each address.
• total_proposal_interaction_in_space: The total number of interactions on proposals categorized as "space" interactions.
• total_proposal_interaction_non_space: The total number of interactions on proposals categorized as "non-space" interactions.
• total_nft: The total count of NFTs associated with each address.
• rewards_nft: The total rewards associated with NFTs for each address.

Overall Summary Metrics:

Provides an overview of the total number of addresses, ENS names, followers, votes, interactions, NFTs, and rewards.

Distribution Analysis:

Visualizes the distribution of key metrics such as follow count, votes, interactions, NFTs, and rewards across the dataset using histograms, box plots, or bar charts.

Correlation Analysis:

Analyzes the correlation between different variables such as follow count and votes, follow count and NFTs, etc. using scatter plots or correlation matrices.

Top Performers Analysis:

Identifies and ranks the top addresses or ENS names based on metrics like follow count, votes, interactions, etc. using tables or visualizations such as bar charts or heatmaps.

Time-based Analysis:

Tracks and visualizes the trends and changes over time for metrics like follow count, votes, interactions, etc. using line charts or time series analysis.

Comparison Analysis:

Compares the performance of different addresses or ENS names based on metrics like follow count, votes, interactions, etc. using tables or visualizations like stacked bar charts or radar charts.

Relationship Analysis:

Explores the relationship between follow count and other metrics such as votes or NFTs using scatter plots or bubble charts.

Insights and Highlights:

Identifies and highlights key insights or interesting patterns in the data using text boxes or annotations. Usage

Install Power BI Desktop from the official Microsoft website. Download or clone the repository. Open Power BI Desktop and open the .pbix file from the repository. Connect the dashboard to your dataset or replace the existing dataset with your own. Adjust the visuals and filters as needed. Save the Power BI project and share it with others or publish it to the Power BI service for online access.

Power BI Desktop (latest version recommended) to open and modify the Power BI project. A compatible dataset that includes the columns mentioned above. Contributing

This project is licensed under Mosaic.fun