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  • Writer's pictureKelly Adams

The Underrated Skill for Data Analysts: Business Knowledge

Updated: Feb 22


Free photo people analyzing and checking finance graphs in the office

As data analysts, we frequently discuss our tools, whether it's Power BI, SQL, or others. Additionally, there are debates about the order in which to learn these skills. However, while proficiency with these tools is crucial, especially for new analysts, we often overlook another vital skill: business knowledge.


As a data analyst, the primary objective is not just to analyze data but to get insights from it that can drive business decisions. Essentially, you are a problem solver for business challenges. This context is fundamental before diving into data.


Examples:

Why Business Knowledge Matters for Data Analysts:

  • E-commerce Company: Imagine being an analyst for an online computer vendor. You're assigned to assess sales data. Without business context, you might overlook key insights. For instance, recognizing that the company recently launched a loyalty program can help you understand the uptick in sales among both new and returning customers.

  • Subscription-Based Service: Tasked with studying customer loss for a subscription service? Not being aware of recent changes in pricing or marketing strategies might lead you to misinterpret an increase in churn rates.

  • Healthcare Data: When analyzing patient satisfaction data for a healthcare provider, being informed about recent policy changes or regulations becomes invaluable. A policy shift in insurance, for example, could influence patient opinions. Lacking this knowledge could alter your conclusions.

A Personal Experience:

In my first few weeks at a job, I stumbled. I neglected the business context while writing a SQL query centered on customer behavior. Though my query fetched the desired data, it missed the broader context. I wasn't aware of a new company policy, urging more frequent customer site visits, which affected my analysis. Now, I prioritize the underlying business rationale with every query, ensuring my insights stays relevant.


5 Reasons to Prioritize Business Understanding:

If you're still not convinced, here are five more reasons to always consider the business context:

  1. Problem Framing: Understand the objectives, KPIs (key performance indicators), and the goals of the business. This clarity ensures your efforts resonate with company needs.

  2. Data Relevance: Business knowledge helps you discern valuable data from the noise. This can save time and resources.

  3. Data Interpretation: Business acumen is crucial for interpreting data. After your analysis, can you understand how it can help the business? This highlights important insights.

  4. Effective Communication: Analysis often needs translation for a non-technical audience. Solid business context allows you to explain the 'why' and the 'how' of your findings.

  5. Solution Recommendations: Initial analyses usually sets the stage for actionable strategies. A deep business understanding ensures these strategies are both viable and align with the organization's goals.


Developing Business Knowledge

Now that I've talked about the importance of business knowledge here are a strategies on how to do it:

  1. Engage with Stakeholders: Regularly communicate with product managers, sales teams, marketing professionals, and other stakeholders. Their insights offer different perspectives on the business's priorities, challenges, and goals.

  2. Read Industry News: Stay updated with the latest trends, challenges, and breakthroughs in your industry. You can use resources like websites, magazines, and industry reports.

  3. Take Business Courses: Consider enrolling in business courses or workshops. Use platforms like Coursera, Udemy, or LinkedIn Learning which offer courses on business fundamentals, strategy, and more.

  4. Join Other Projects: Being a part of projects that span across different departments can give you a broader view of how the organization operates and how data analysis can help other departments.

  5. Feedback: After presenting your analysis, seek feedback. Understanding what was valuable and what wasn't can give insights into the business's actual needs and help you improve future analyses.

  6. Network: Have conversations with peers from other companies. Sharing experiences can provide a broader perspective on common industry issues. I'm a fan of using LinkedIn for this but you can also attend conferences or local meetups.

  7. Always Ask 'Why?': Whenever you're given a task or project, always ask why it's important to the business. Understanding the bigger picture helps your analysis to be more impactful.


In summary, data analysis is more effective when it's a collaborative effort with business knowledge. This approach guarantees that your insights translate to informed decisions, and positive impacts on the organization.

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