Data Analysis of Mergers by Tech Cos.
I chose this data to look at the mergers and acquisitions made by major companies through history to look at trends and see if there are any exciting points we can find.
The data for this project contains list of acquisitions made by the following companies: Microsoft, Google, IBM, HP, Apple, Amazon, Facebook, Twitter, eBay, Adobe, Citrix, Redhat, Blackberry, Disney. The data also includes the "date, year, month of the acquisition, name of the company acquired, value or the cost of acquisition, business use-case of the acquisition, and the country from which the acquisition was made". The source of the data comes from Wikipedia, TechCrunch, and CrunchBase.
The major parent companies in the data are:
If we look at the number of acquisitions made by the year, we see that the number of acquisitions made is on an upward trend until 2014, when we see the numbers go down slightly. An interesting point is the year 1999 when it doubles. We can find out that this was the peak of the dot-com era. The opposite side is the year 2009. We see a dip in the number of acquisitions, and we can conclude that this was due to the 2009 financial crisis. We also see in years 2010 and 2011 skyrocketing while year 2012 dips. This might be due to the fact that years 2010 and 2011 "overloaded" to make-up for year 2009.
When looking at Acquisitions made by the month, we see that there is not much difference between the months. The most significant amount being June and the least amount being November. But from this data, there is not much information we can extract as trends.
Leaders in acquisitions
Looking at each company's acquisitions, three companies lead the race for the number of acquisitions made. Them being Microsoft, Google, and IBM. The three tech giants are known for being leaders in the industry for an extended period which can result in many acquisitions. In comparison, we see that Facebook, Amazon, Twitter, and apple are not the leaders. However, they have made significant acquisitions, all while entering the industry later in the timeline. For example, here is a useful list of all large mergers and acquisitions made by big tech companies: https://www.tahadharamsi.com/finance/list-of-mergers-and-acquisitions-by-big-tech/
Looking at this visualization, we see how various acquisitions made by all the companies have changed throughout history. Starting from the late 1990s, we see a different field of players who have made acquisitions and mergers.
This is the average price of acquisitions made by the major companies.
This is the number of countries the acquired companies were from. Because we are looking at companies based in America, the distribution between the location is not very diverse.
Lastly, this is a word cloud that I created from the acquired business type. We see that Software is the most significant type of company that would get acquired and that the data includes many companies.
(Data cleaning to generalize the types of business… Group by by the business column -> categorize(filter/find groups with 20 less as minority and keep majority) -> merge minority groups
Next Steps - Predictions using Data
In conclusion, things I would have liked to work on but could not was predicting the type of acquisitions for the future. Find out the number of acquisitions that will be made and determine the next trend of business types that will lead the acquisition list.