The role of data analyst became one of the most sought-after in Latin America. Companies need to understand what works, what doesn't, and how to predict what's coming. For that, they need someone who can translate data into decisions. But behind the title, there isn't always clarity: what does an analyst really do? What tools do they use? How much do you earn in this role? In this blog we're going to tell you all that.

The task of a data analyst

A data analyst collects, organizes, interprets and visualizes data to answer key business questions. Their work isn't only technical: they need to understand the context, detect patterns and communicate them clearly so others can make decisions.

Real examples:

• At a fintech: they analyze users' payment behavior and detect risks.

• At an e-commerce: they measure the impact of an advertising campaign on sales.

• At a health startup: they cross-reference user data with clinical results to identify product improvements.

Key soft skills: critical thinking, curiosity, communication ability.
Most used hard skills: SQL, Excel/Google Sheets, Python, Power BI or Tableau.

→ You can see more examples of real tasks in this Harvard Business Review guide

What type of data does an analyst analyze, and what is it for?

The data analyst works with structured information that lets you find patterns, detect problems or make decisions with evidence. Some common types of data:

• Users: clicks, navigation, sessions, location.
  → They help improve experiences, products and messages.

• Marketing and sales: campaigns, leads, revenue, conversion rates.
  → They're used to optimize budgets and detect which channel performs best.

• Operations: inventory, deliveries, times, support.
  → They detect operational failures or help automate repetitive tasks.

• Feedback and surveys: comments, ratings, NPS.
  → They detect improvements, failures or unmet needs.

• Finance: revenue, margins, expenses.
  → They underpin investment, cut or expansion decisions.

In all cases, the analyst's value is turning raw data into a story that others can understand to decide better.

→ This approach is known as data storytelling, and you can learn it in programs like the Data Analysis career at Coderhouse or with resources like Storytelling with Data.

How much does a data analyst earn in LATAM?

Salaries vary according to the country, the industry and experience. These are updated averages for 2026:

• Argentina: ARS 800,000 - 1,300,000 / month

• Mexico: MXN 25,000 - 45,000 / month

• Colombia: COP 3,500,000 - 7,000,000 / month

• Remote for U.S. companies: USD 1,500 - 3,000 / month

→ Source: Glassdoor LATAM and Levels.fyi LATAM Report

In addition, IBM's report on digital skills positions data analysts as one of the 5 most in-demand roles in the next decade.

What tools do you have to learn first

This depends on your starting point, but this is an initial stack with a good “effort vs. results” ratio:

1. Excel or Google Sheets (advanced): for quick analysis, cleaning, basic visualizations.

2. SQL: to query databases (indispensable).

3. Power BI or Tableau: to create dashboards that communicate.

4. Python (basic to intermediate level): to automate analysis, use libraries like Pandas or Matplotlib.

→ See the Data Analysis career at Coderhouse
→ You can also practice with real datasets from Kaggle or Google Dataset Search

How to start from scratch and without experience?

This is a realistic plan for someone who works and wants to reorient their career in 6 months:

1. Choose a practical, project-focused program.

2. Add 1 hour per day or 6 to 8 per week to learn.

3. Do exercises with real data.

4. Show your progress on LinkedIn (use #PortfolioData and #DataAnalytics).

5. Apply for junior or transition roles. Today, demonstrated potential is valued much more than degrees.

→ This Towards Data Science guide shows you how to put together a portfolio from scratch.

Conclusion

Being a data analyst isn't just about handling tools. It's about thinking logically, asking good questions and translating numbers into decisions. Want to test whether this world is for you? Explore the content of the Data Analysis career, review real cases and start with a simple challenge.

If you'd like to keep exploring this topic, you can also read prompt engineering for data analysts: the skill few master.

Recommended Coderhouse courses

If you want to go deeper into data analysis and applied artificial intelligence, Coderhouse has programs for all levels:

• Data Analytics Course: to learn to analyze data, build dashboards and make decisions based on real information.

• AI Engineering Course: to incorporate AI and machine learning models into your data projects.

• Introduction to Artificial Intelligence Course: to understand the AI ecosystem and complement your data profile with knowledge about language models.