10 Concepts Every Data Analyst Should Know

4 Jun 2026 · 1 min

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In this concise instructional video, Kedeisha Bryan outlines the ten foundational concepts that every data analyst must master. She emphasizes that data cleaning is the essential first step, followed by a solid grasp of SQL joins, aggregation functions, and effective data visualization. She then covers core statistical tools such as descriptive statistics and the critical distinction between correlation and causation. The video proceeds to practical workflow knowledge—ETL pipelines and A/B testing—before highlighting the importance of understanding business KPIs and, finally, the art of data storytelling. Throughout, Bryan stresses that competence in these areas directly impacts an analyst’s ability to deliver clear, actionable insights and advance their career.

Chapters

Here are 10 concepts that every data analyst should know. 1, data cleaning. If you can't prep data, nothing else matters. 2, SQL joins. Inner, left, don't even think about the right join. Know them like the back of your hand. 3, aggregations. Sum, count, average. This is the foundation of creating metrics. 4, data visualization. Charts that tell a story, not just display numbers. 5, descriptive statistics. Mean, median, standard deviation, the basics. 6, correlation versus causation. Know the difference, it'll save your career. 7, ETL pipelines. How data actually moves from source to dashboard. 8, A/B testing. How companies make decisions with data. 9, KPIs. If you don't know what the business is measuring, you're just guessing. 10, data storytelling. Because the analyst who can explain it wins every time. Clarity over complexity. Save this list.