📊 Twitter Analytics Dashboard (Power BI)
🧠 Project Overview This Power BI project presents a comprehensive Twitter Analytics Dashboard built using advanced data visualization and filtering techniques. The goal was to extract meaningful insights from Twitter data by showcasing user engagement, impressions, click types, and more — all within a highly interactive and dynamic report.
✅ Features & Visualizations
- Visual Metric Cards Key performance indicators (KPIs) at a glance:
Total media views
Average impressions
Engagement rate
Total tweet count
Total likes
Maximum retweets
Tweets per weekday
Impressions per day
- Total Clicks Pie Chart Displays proportional breakdown of URL clicks, profile clicks, and hashtag clicks
Applies to tweets with >500 impressions
Interactive drill-down feature to explore click types at the tweet level
- Click Breakdown by Tweet Category Clustered bar chart showing sum of clicks by:
Media tweets
Link tweets
Hashtag tweets
Displayed only when:
Tweet date is even-numbered
Word count is above 40
At least one interaction exists
- Engagement Type Comparison Visualization Compares replies, retweets, and likes
Focused on tweets with media engagements above the median
Filters applied:
Tweets from June to August 2020
Time slots: 3PM–5PM IST and 7AM–11AM IST
Odd-numbered dates, even-numbered media views
Character count > 20
Excludes tweets containing words with the letter 'S'
💡 Key Learnings During development, I enhanced my skills in:
Complex conditional filtering and custom visuals in Power BI
Creating time-based and interaction-based chart rendering
Leveraging drill-down features for granular data exploration
Structuring dashboards for performance and clarity
These skills are directly applicable in real-world business intelligence scenarios. 🚀 Getting Started To explore the dashboard:
Clone the repository
Open the .pbix file in Power BI Desktop
Interact with filters and visuals to explore insights
🛠 Tools Used Power BI Desktop
Data Modeling & DAX
Twitter engagement dataset (sample)