Technology Mergers and Acquisitions – EDA Dana Dvash
Overview
This project explores over 1,600 global tech M&A deals from Kaggle. The goal was to analyze how deal activity and values have evolved over time, identify the biggest acquirers, and highlight major patterns shaping the tech industry.
Dataset
Source: Kaggle – Technology Mergers & Acquisitions
Size: ~1.6K rows, 11 columns
Key Features: Acquiring company, acquired company, date, deal status, and price
Main Variable: Price_MUSD – deal value in millions of USD
Data Cleaning
Main steps:
Converted all prices to numeric USD values (M/B format fixed)
Removed duplicates, invalid or missing records, and broken links
Filtered out deals with unclear or non-final status
Dropped very small deals (<10M USD)
Rows before: 1,636 Rows after: 1,519
Outliers
Used IQR to detect 63 outlier deals. These were kept since they represent real large-scale acquisitions (e.g., LinkedIn, WhatsApp).
Descriptive Statistics
Deal prices are heavily right-skewed:
Mean ≈ 1.2B USD, Median ≈ 250M USD
Most deals fall under 5B, but a few exceed 40B
There’s little correlation between deal value and year — large acquisitions occur sporadically.
Visual Insights
- Distribution of Deal Prices Most deals cluster below 5B USD, with a few major outliers driving the total market value.
- Deals Over Time Peaks around 2014–2016 and 2020–2021 reflect innovation waves (cloud, AI, social media).
- Disclosed Prices by Year Slight upward trend in transparency after 2010, though inconsistent.
- Top Acquirers Google, Microsoft, Apple, IBM, and Cisco dominate global tech M&A.
- Correlation Heatmap Weak relationships between variables suggest deal value depends more on company strategy than time.
Key Takeaways
M&A activity follows major tech trends.
Large corporations dominate acquisitions.
Most deals are modest in size, with rare billion-dollar exceptions.