Most In Demand Tech Skills for Data Analysts
I analyzed online job listings from January 2020 to find the answers. In this article, I’ll share the answers and provide a suggested learning path for aspiring data analysts.
This is my third article looking at technology skills in data-intensive positions. See the previous articles on data scientists here and data engineers here.
Without further ado, here are the top 10 technologies from data analyst job listings as of January 2020.
Data analysts turn data into information. They play a vital role by making data actionable for decision makers.
Data analysts often take data provided by data engineers, analyze it, and make recommendations. They create visualizations to display their findings in dashboards and presentation.
I scraped information from SimplyHired, Indeed, and Monster, to see which keywords appeared with “Data Analyst” in job listings in the United States. I used the Requests and Beautiful Soup Python libraries.
I used the same keywords gleaned from my analysis of data scientist and data engineer job listings. LinkedIn was not searched because it previously locked me out of my account after scraping its site. ☹️
For each job search website, I calculated the percentage of total data analyst job listings for that site that each keyword appeared in. Then I averaged those percentages across the three sites for each keyword.
Here is an expanded chart showing the 30 most common technologies.
Here’s the same data in tabular form.
Many other technology keywords were searched; these were the 30 highest scoring. Let’s look at the most common technologies.
SQL is short for Structured Query Language. It shows up in over half of all listings. SQL is used for working with relational databases. SQL comes in many flavors, including MySQL, Oracle, SQL Server, PostgreSQL, and SQLite. Each version shares most of the same core API. There are quality free offerings.
Excel is almost as common as SQL. It’s the dominant spreadsheet program. It’s part of the Microsoft Office 365 suite of software tools. Although it can’t handle huge quantities of data like SQL databases, Excel is great for doing analysis quickly. Google Sheets is a competitor with a free version and similar core functionality.
Tableau shows up in about a quarter of listings. It’s drag-and-drop business intelligence software that makes it easy to create visualizations and dashboards. Tableau’s visualization capabilities are far better than Excel’s. Tableau has a free public version, but if you want to keep data private you need to shell out some money.
Python shows up in about a quarter of listings. It’s a very popular free open source programming language for working with data, websites, and scripting. It’s the primary language for machine learning.
R is also in over 20% of listings. It’s a popular free open source language for statistics, especially in academia.
In previous articles I looked at the most in demand tech skills for data scientists and data engineers.
