
Table of Content
Introduction
In 1995, less than 10% of the world population used the Internet. Now, internet users make up 58% of the global population and generate over 2.5 quintillion bytes of Data a day. As technological advancements continue to outpace the number of people with relevant STEM knowledge, there’s an increasing need, more than ever before, for engineers, data scientists, and data analysts. The demand for data analysts is so high that the average salary for a data analyst in the US is around $70,000!
In this article, I’ll give you my perspective on what a data analyst does, the skills required to be a data analyst, and some takeaways from my experiences.
What a Data Analyst Really Is
I’ve read several articles that gave me a laundry list of things that a data analyst does, but in the simplest sense, you are analyzing and visualizing data. Each company has their own databases that you can query from. These companies also have their own tools for data visualizations, like Tableau, that you use to visualize your insights and findings.
In business, there are many types of data, like product data, marketing data, and operations data, and similarly, there are several types of data analysts, like product analysts, marketing analysts, and operations analysts. What differentiates these jobs from each other is the domain knowledge relevant to each category, but ultimately, they are synonymous with the term ‘data analyst’.

The spectrum of what a data analyst does ultimately depends on the company that you’re working for, but generally, a data analyst will go through the following workflow in the image above. Let’s walk through it.
Problem
Each analysis starts with a problem or a task. The level of difficulty of these tasks can differ greatly. An example of a simple task is if you were asked to write a query to provide a statistic, like yesterday’s sales in dollars. An example of a more difficult task is when the answer isn’t clear and you’re asked to explore the data. E.g. If you were asked to figure out why last month’s sales performed much worse than other months.
Explore and Query
Once you receive a problem, you’ll usually write a query or a number of queries to explore and gather the information that you need to solve the problem. This means that you’ll probably need to know SQL or Python (or both) to gather the information you need.
Continuing with the previous example, if you were asked to figure out why last month’s sales performed much worse than other months, you might query the average customer review rating last month to see if there was a problem with the product, or you might query last month’s marketing spend compared to other months to see if there was a significant cut in marketing spend.
Gather Insights
The next step is to gather your insights. Sometimes, gathering your insights means copying and pasting your insights into an Excel sheet. Other times, it means saving your queries that you used to find the information that you need for the next step.
Visualize Insights
Once you gather your insights, you may be required to visualize your findings. Sometimes, it’ll be as simple as making a bar graph in Excel. Other times, it means creating an extensive dashboard to be used by C-suite executives. The skills required in this step depends both on the company and the project. It includes but is not limited to, Powerpoint, Excel, Tableau, Matplotlib, etc…
Communicate Your Findings
Lastly, you’ll be required to communicate your results, whether it be through a slide deck with several static graphs or a dashboard with several KPI metrics. Similar to the STAR method for answering behavioral, you would walk through the problem, the task, the approach you took, and the end results(s).
Note:
I know that I’m generalizing by simplifying and I know this doesn’t encompass every single thing that a data analyst does in his/her day-to-day. However, for those who have absolutely no idea what a data analyst does the same way some of you have no idea what a speech-language pathologist does, this provides a decent idea of what they do.
Skills Required to be a Data Analyst
If this sounds of interest to you, that’s great! At the beginning of 2020, Jeff Hale published an article, "Most In Demand Tech Skills for Data Analysts". Through scraping and analyzing several job posting websites, he concluded that the top four skills for data analysts from most important to least are SQL, Excel, Tableau, and Python.
SQL
What is SQL?
SQL is a programming language used to access and manipulate databases. Think of databases as a collection of tables, with a table being a collection of rows with the same variables. Think of an Excel table, like the one below:

A query is a request for data from a database table or combination of tables. Using the table above, I would write a query if I wanted to find all patients that were older than 23 years old. As a data analyst, you’ll be querying data on a frequent basis, either to retrieve information for other employees or to solve more complex problems.
How to Learn SQL
- If you want to learn beginner SQL, check out my article, "Learn Beginner SQL in 5 steps in 5 minutes!" Yes, there are different syntaxes for different types of SQL languages, but generally, they follow the same format.
- If you learn better by doing, Codecademy has a very good and concise course on SQL here. This is how I personally learned the basics of SQL.
- Once you learn the basics, you can practice your learnings with these practice questions.
Excel
What is Excel?
In case you don’t already know, Excel is a spreadsheet program that allows you to enter data into the rows and columns of a sheet. You should know how to use basic functions like SUMIF, IF statements, and COUNT to name a few. Additionally, you should know how to create graphs and pivot tables. In practice, because companies value collaboration, you may be required to use Google Sheets, which is essentially the same thing.
How to Learn Excel
To be honest, Excel is something that I learned through experiences. If you don’t have the opportunity to learn by doing, there are some amazing YouTube videos (that are also free) that you can use to learn Excel! See below.
Tableau
What is Tableau?
Tableau is a data visualization tool that’s widely used across all industries. Typically, companies use Tableau to create dashboards, which are tools that display live and real-time metrics for businesses to look at. For example, a marketing team might create a dashboard that displays daily conversions, daily marketing spend, and daily website traffic.
How to Learn Tableau
- If you want to learn how to use Tableau, they have a series of training videos that you can go through on your own here. They also provide live training and eLearning experiences.
- Alternatively, I purchased a course years ago on Data Science Essentials, and in this course, it walks you through downloading and using Tableau. If this is something that you’d be interested in, you can check out the course here.
Python
What is Python?
Python is a versatile programming language that is popular among data analysts and data scientists. Specifically, in Python, there are various libraries that one can use to perform data analyses like NumPy, Pandas, and Sci-kit Learn.
If you want to learn how to use Python and these libraries, there are several resources that you can leverage online, like DataCamp, Udemy, Coursera, and Udacity. While I don’t have any particular preference in learning Python, I encourage you to choose one resource and stick to it!
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