There’s a lot of information about how to become a data analyst but there’s little that guide you in the right direction when you first become one. To avoid going down the wrong one way road this is my advice on how to become successful as new data analysts.
Always check your work
The worst thing for any data analyst is giving the wrong number to your stakeholder. This creates doubt in your ability to provide the correct information and hurts your credibility as an analyst. To avoid mistakes always cross check your numbers against other sources. If it’s an important project ask a senior analyst or your manager to look over your numbers before you present to the stakeholder.
Learn the business and key performance indicators ( KPIs )
To become a great data analyst, it’s important to understand the company business, how the company makes money, and to learn the KPIs used to measure success. Once you learn the business and KPIs you’ll be able connect your stakeholder request to the business and the impact they want to drive.
For example, let’s say you support the marketing department for an online retail company. The marketing manager would like to make changes to the website and asks what KPIs should be used to measure success. Since you took the time to understand the business you’re able to ask the right questions to recommend appropriate KPIs such as conversion rate and average order value to measure success.
Get context for the request
I was once asked to pull user level data that wouldn’t fit into an Excel worksheet because it was more than one million rows. I knew it was going to be a nightmare for my stakeholder to load into Excel because of memory constraints. I asked why this data was needed and based on the context I was able to provide the view my stakeholder really wanted with a few thousand rows of data.
It’s common for a stakeholder to ask for one thing but mean something else because they can’t articulate what they want. A great data analyst will dig deeper to understand what’s driving the request and deliver what is actually needed.
Learn how to present data results in a clear manner
Simply showing a table of numbers without explaining the context and business impact is not useful. Explain to your stakeholder how the numbers relate together using charts to show trends and point out relevant information. Data literacy is a problem in many companies and being able to communicate results a stakeholder can understand and use to make decisions are essential skills of a great analyst.
Identify a problem and provide a solution
For example, the company’s website recently had a drop in visitors. The marketing department asked you to help identify a possible cause. You breakdown the website visitors by channel and see a drop from organic search. At this point you can show the results to your stakeholder and you would be done.
A great analyst would ask questions to the team responsible for the website to confirm if any changes had been made recently. You’re told there were changes on the same day when visitors from organic search started to drop. Now you can go back to your stakeholder and say "traffic dropped to the website from organic search visitors due to changes made on the website that caused a drop in Google search rankings". Going this extra mile shows you not only found the source of the problem but took initiative to provide a solution.
Learn to work smarter, not harder
In my first full-time job, I worked long hours to complete my tasks because I was inefficient. It was difficult to apply what I learned in school to a real-life setting. A majority of my work was in Excel so I learned all the keyboard shortcuts and how to develop VBA macros to reduce my time on repetitive tasks. I trained myself to work faster and over time I was able to complete everything within business hours.
When I became a data analyst, I saved SQL and Python code snippets for reference to avoid writing similar code for different requests. I kept track of key dates that impacted company KPIs and links to documentation for reference. I appeared to complete tasks in record time and always had an answer on hand to stakeholder questions but this was all due to learning how work smarter, not harder.
Conclusion
Whether your starting your career as a data analyst or changing Careers to become one, don’t feel overwhelmed that you aren’t successful at first. Focus on one skill at a time and move on to the next one when you’ve reached a level you deem as successful. The path to success requires time and practice but now that you know the way, I hope it comes to you sooner rather than later.
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