I often get asked, “What does a data analyst do?” While a lot of the work data analysts do is fairly standard across most jobs, the answer to this question won’t be the same for every data analyst.

For example, some data analysts might use Power BI for data visualization instead of Tableau. Some positions require knowledge of Python or R while others don’t. Some data analysts might have meetings every day, while others may just publish reports and communicate by Microsoft teams.

Therefore, I thought I would answer this question to the best of my ability by summarizing what I do as a data analyst.

My work is primarily composed of four activities: querying data with SQL; cleaning and analyzing data in Microsoft Excel; performing additional analysis and visualizing data in Power BI; and communicating via Microsoft Teams and email.

First, SQL. A big portion of my job requires updating and publishing 15ish reports every quarter. For SQL, this requires running existing queries each quarter to pull the data and export it into an Excel spreadsheet for future steps.

The interesting part of the process is when colleagues (people who use my data) want additional data/variables included in my reports or want to change something else about my reports which requires query updates.

Here, I use what is being asked of me and my knowledge of SQL to achieve what my coworkers are asking. This often requires a lot of trial and error, but I enjoy this problem-solving aspect of my job.

Additionally, my coworkers will ask for data or analysis of something not contained in my reports. This is called an ad-hoc data request and requires me to use parts of existing queries to create a new query to get the requested data. This usually is a fairly quick process.

Second, Excel. Once the data for the aforementioned reports is pulled with SQL and exported into a spreadsheet, I can clean the data. Cleaning data means to put it into the correct format, remove duplicate or irrelevant observations, and do anything else to make the data more accurate and able to be analyzed.

After cleaning the data, I then analyze it by utilizing formulas in Excel to perform calculations, attach values from another spreadsheet, etc. As a final step, I check some of the columns of the data to make sure it looks correct and is categorized correctly.

Third, Power BI. Once in Power BI, I connect to the Excel workbook of my data and create interactive charts and graphs to show trends and give information to people in my organization. Power BI and similar programs provide an excellent way to visualize data which makes it easier to find useful information and tease out trends in the data.

Last, communication. While most of time during my workday is spent using SQL, Excel, and Power BI, the data I pull is for the use of various members throughout my organization. So, I must talk to these colleagues to learn what data they need and how it can best be presented to them.

I do this by maintaining strong lines of connection using Microsoft teams for instant messaging and email generally for more substantive conversations.

Once again, this is what I do in my job as a data analyst, but it won’t be the same for every data analyst in the world. However, programs like SQL and Excel are used in the majority of data analyst positions and many analysts have some duties similar to mine.

Thanks for reading!

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