What Does a Data Analyst ACTUALLY Do?
It's not all coding and dashboards
Since becoming a data analyst, I've held a few different roles and worked on some very different teams.
Today, I want to break down the day-to-day work of a data analyst.
Right off the bat, I’d like to mention that there are many variables that affect the scope of work that a data analyst will do.
I’ll review some of these in detail throughout the article.
Let’s get started.
What is a Data Analyst?
A data analyst primarily does 3 things.
Gathers the data
Analyzes the data
Presents the data.
However, the specifics of the role can vary greatly depending on:
The varying types of analyst roles.
You have business analysts, business intelligence analysts, product analysts, and many many more.
Domain
What industry is your company in and what team do you support specifically. Not every data role is going to be on the IT team.
Company tech stack
What tools does your company use
Team size
I’ve been a solo analyst supporting a specific department and I’ve also been on a data team with other analysts and engineers. The size of your team and your company is going to determine some of your responsibilities.
Each of these will affect the scope of your work to some degree.
Despite these variations, the core responsibilities of gathering, analyzing, and presenting data remain fairly constant.
Next, let’s look at…
The Workflow of a Data Analyst
Let’s review the 3 workflow steps of a data analyst that I’ve already mentioned.
1. Gathering Data
The first step is to determine the data needed for any given project.
This done often through meetings with stakeholders.
And stakeholders are whomever you’re creating the project for. This could be any company leader or otherwise that you support throughout the business.
Interacting and collaborating with stakeholders is a HUGE part of the role of a data analyst.
In my experience, you often have to meet with stakeholders multiple times throughout the project.
A project can also take anywhere from a few days to a few months to complete depending on those requirements and your access to the data as well as the data quality.
Requirements can also sometimes change throughout the life of a project and many approvals are often needed before it’s finished.
2. Analyzing Data
Before analyzing, data must be ingested into your data warehouse. This is often done with the help of your data engineers.
The tools and methods used for data ingestion and analysis vary by company, but Snowflake would be an example of a tool you might use for your data warehouse and then Matillion is an ETL tool you might use to get that data from it’s original source into Snowflake.
Most companies also use many different tools to fulfill the needs of the business across every department.
And example of this could be a tool like Typeform that the marketing department uses to gather survey data.
Sometimes this data is already ingested, sometimes not.
Once you have access to the data, you might need to perform additional manipulations through SQL to get the views of the data that you need and perform the analysis.
BI tools like Power BI and Tableau can also be used to transform your data prior to presenting your data in the form of a dashboard.
3. Presenting Data
The final step involves developing reports and presenting insights using BI tools like those I just mentioned.
This process might also bring to light data quality issues in which case the data team or the stakeholder might need to clean up their data, depending on where the issue lies.
As additional meetings are held throughout the length of the project, you may also be given additional requirements to fulfill.
These are all things that can prolong the completion of a project and why projects can sometimes take weeks or even months to complete.
I want to mention again that a lot of this will depend on what your role is and what resources your company has access to.
Finally let’s take a brief look at…
The Day-to-Day of a Data Analyst
A data analyst's daily activities can vary quite a bit. For me, it’s often the case that no two days look the same.
In smaller teams, analysts may wear multiple hats, while larger teams might offer more routine.
I’ve known solo data analysts at startups who had to do ALL SORT of tasks.
But then with bigger companies like Amazon or Google, roles start to get very niche.
Like I mentioned at the beginning of the article, company and team size will affect your work greatly.
For me, a typical day might include meetings, deep work, and development. Rarely is a project started and completed on the same day. In fact, this never happens unless it’s a one-off, ad-hoc task.
I’m almost always working on multiple projects at once too.
Conclusion
If you’re still an aspiring analyst, I hope this removes a bit of the mystery surrounding what a data analyst does.
If you’re already in the field, I hope this helped you see how your work might differ from others.
I also put together an entire video on this topic if you’re interested in going more in-depth into the workflow of a data analyst.
That’s it for this week.
See you next time ✌️