LinkedIn Connections Analysis
Data: Author’s Connections Data (2017–2022)
Introduction
For my second personal project, I decided to analyse my LinkedIn data. I requested my data from LinkedIn and used Google Sheets and Power BI to perform my analysis.
Analysis Process
Framing the purpose of the analysis
At first, I collected all my data. Then I reviewed each file and settled on just my connections. I concluded that I would analyse the
- total number of connections I have.
- connection made over time. In the Power BI report, you would see this first as years (2017–2022) and you can drill down to quarters in a particular year, months of a year, or even days in the month.
- professions and their connection count.
- companies and their connection count.
Data collection — Data Request
I followed the steps in this article to get my data. I had first requested my full archive and then waited some days before it was available. I did not start the project immediately so I later requested only my connections data since I wanted a recent copy. This was available in less than an hour.
Data cleaning
I cleaned the data in Google Sheets. After skimming through, I noticed some rows with blank values except for the ‘Connected On’ date field. It seems those users had deleted their accounts. I removed these rows. Afterwards, I validated the data type of the columns and converted other languages to English. In Power BI, I promoted the first row to headers, re-validated data types and merged the first name and last name columns. I also had to replace abbreviations in the positions and companies columns with full words. I replaced the same positions that were in different forms with one. An example of this was N.Y.S.C intern, NYSC Intern, and NYSC Service Year.
Data analysis and visualization
I sketched out the appropriate visualizations for my analysis. I made a DAX measure to count the number of connections and plotted my charts considering accessibility.
Result
You can view and interact with the dashboard here.
Conclusion
- I have 1867 connections after removing null accounts.
- I have made higher connections than the previous year in all the years except 2020 which is lower than 2019 and 2022 because the year has not ended.
- Most of my connections (270 of them) have “Engineer” in their titles.
- The company where I have the most connections is Semicolon with a count of 59 and then Covenant University with 27. This could most likely be because I attended those institutions.
Thank you for reading this till the end. Please connect with me and let me know how I could do better!
