What You Need to Become a Data Analyst

Becoming a data analyst is more accessible than ever — but what exactly do you need to get started? Let’s break it down into tools and knowledge.

Tools You Should Learn

• Excel / Google Sheets – Foundational for data cleaning and quick analysis.

• SQL – Essential for querying databases.

• Python or R – For more advanced data manipulation, analysis, and automation.

• Tableau / Power BI – Popular tools for building interactive dashboards and visualizations.

• Jupyter Notebooks – Great for data exploration and storytelling with Python.

Core Knowledge Areas

• Statistics – Understand distributions, correlation, regression, and basic probability.

• Data Cleaning & Preparation – Know how to handle missing data, outliers, and inconsistencies.

• Data Visualization – Learn how to present data clearly and effectively.

• Business Acumen – Understand the industry you're working in and the questions stakeholders care about.

-- Using QUALIFY:
SELECT 
product
, market
, SUM(revenue) AS market_revenue 
FROM sales
GROUP BY product, market
QUALIFY DENSE_RANK() OVER (PARTITION BY product ORDER BY SUM(revenue) DESC)  <= 10
ORDER BY product, market_revenue
;

-- Without QUALIFY:
SELECT 
product
, market
, market_revenue 
FROM
(
SELECT 
product
, market
, SUM(revenue) AS market_revenue
, DENSE_RANK() OVER (PARTITION BY product ORDER BY SUM(revenue) DESC) AS market_rank
FROM sales
GROUP BY product, market
)
WHERE market_rank  <= 10
ORDER BY product, market_revenue
;

Soft Skills Matter Too

Communication, critical thinking, and curiosity are just as important as technical skills. The best analysts don’t just crunch numbers — they find insights and tell compelling stories with data.

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Start small, build a portfolio with real-world projects, and keep learning. The path to data analysis is a marathon, not a sprint — but it’s an exciting one!