Five Key Considerations Before Embarking on a Data Analyst Career

Four months ago, upon completing my final exams, I found myself in the fortunate position of knowing precisely what my next steps should be.

My career goal was clear: secure a job as a data analyst and gain invaluable experience in the field.

This blog will outline five crucial aspects to consider, encompassing two hard skills, an interview strategy, and two soft skills.

One of the most effective ways to achieve success in any endeavor is through self-learning, and I will share my insights on this approach in a future blog post.

First and foremost, if you aspire to work as a data analyst, advanced SQL knowledge is non-negotiable. Reiterate after me: Advanced SQL is of paramount importance.

• I’m immensely grateful to my past self for mastering advanced SQL. The amount of work I handle involving SQL is staggering, and the level of comprehension required to extract data accurately is unparalleled.
• Decision-making in this field hinges on the results you produce, which ultimately depend on the output generated by your queries. At some point, you’ll become adept at visualizing datasets within subqueries or CTEs, knowing exactly the output they will yield. I’ll cover where and how to learn this skill in an upcoming post.

The second most critical skill is statistics. We cannot afford to ignore this mathematical aspect of data analysis.

• In my technical interviews, questions about my projects were less common than inquiries about core statistical methods and KPIs.
• It’s not just about memorizing formulas; understanding the principles of statistics is paramount.

Moving on to the third key consideration, different companies approach data analysis differently, even if they use the same tools. You can discern these differences by examining job descriptions (JDs) that outline the KPIs a company prioritizes.

• Companies may not explicitly list all their requirements, but it’s your responsibility to understand the organization’s unique approach to data analysis.
• This knowledge will greatly assist you in interviews and streamline your job selection process.

The fourth point of emphasis is to focus on the narrative within the data, not just the visualization.

• While visualization is undeniably important, understanding the story the data tells makes presenting it significantly easier.

Lastly, no matter where you work with data, always verify the consistency of the data.

• I cannot stress this enough — checking data consistency should be your first task. I learned this lesson the hard way, wasting a considerable amount of time.
• Don’t repeat my mistake; ensure data consistency from the outset.

By considering these five crucial aspects, you’ll be well-prepared to embark on a successful career as a data analyst.

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