Data analysis

Data analysis is often pitched as a matter of Python and models, but an analyst’s daily work looks different: understanding what the business is actually asking, pulling the right data with SQL, cleaning it and presenting it so someone can make a decision. At TintoDev we work with analysts when we build the data layer of a system, and what we value most in them is the judgement to doubt a number before reporting it. This category follows that order. It starts with SQL and a visualisation tool such as Power BI or Tableau, adds basic statistics so you do not draw conclusions from noise, and leaves Python as the next step, for when Excel and SQL are no longer enough. We pick courses with practical cases and realistic data. Many are in Spanish; for Python and applied statistics, the reference courses are usually in English.

Who it is for

• People who want to switch careers into data analysis and do not know where to start.
• Finance, marketing or operations professionals who already work with data in Excel and want to go further.
• Students who need a portfolio of projects they can show in an interview.
• Developers who want to understand how the data their systems produce gets used.

What you will learn

• SQL to extract, join and aggregate data without relying on manual exports.
• Excel and Power BI or Tableau to clean, explore and communicate results.
• Basic statistics: distributions, misleading averages, correlation and sampling.
• How to turn a business question into a query and a metric.
• Python with pandas as the next step, for analyses you repeat or data that does not fit in Excel.

Recommended order

1. SQL and Excel first. They are the foundation of the role’s daily work.
2. A visualisation tool (Power BI or Tableau) and a project of your own, published.
3. Basic statistics applied to your own analyses rather than studied in the abstract.
4. Python once all of the above feels comfortable and you have problems that justify it.

Complete Data Analyst Masterclass 2025

This English-language course tries to cover a data analyst's full toolkit: Python, SQL, Power BI, statistics and an introduction to machine learning. We would recommend it to people who want to see every piece of the job in one program and then decide where to go deeper, because the published syllabus includes projects with data from several industries and interview preparation.

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Google Looker Studio desde Cero 2025

This is a Spanish-language course for learning Looker Studio, Google's free dashboard tool, from scratch. We would recommend it to small teams, marketers and analysts who need shareable reports without paying for licenses, because according to the description you build your own dashboards connected to Google Sheets, SQL, Google Analytics and other sources.

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ANALISIS DE DATOS CON PYTHON DESDE CERO 2025

This is a short, direct Spanish-language course for starting data analysis in Python without installing anything, using Google Colab. We would recommend it to people who have never coded and want to get to cleaning tables and making charts quickly, because the published syllabus focuses on the four libraries used most day to day: NumPy, Pandas, Matplotlib and Seaborn.

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Frequently asked questions

What do I need to learn to become a data analyst?

SQL, Excel, a visualisation tool such as Power BI or Tableau, and basic statistics. That covers the work of most entry-level roles. Python is the natural next step, but it is not the best place to start.

Do I need to know how to code to be a data analyst?

Not to start. SQL is a query language, not a general-purpose programming language, and Excel and Power BI do not require code. Python becomes more important as the role grows into automation or more complex analysis.

How long does it take to learn data analysis?

With steady study, the foundations (SQL, Excel and a visualisation tool) take a few months. Being ready for a first job depends mostly on having two or three projects of your own that show how you think, not on how many courses you have finished.

Python or R for data analysis?

Python, unless you work in research or on a team where R is already the standard. Python also lets you automate tasks and connect to other systems, and it is the more common choice outside academia. What you learn about analysis in one carries over to the other.

Are there data analysis courses in Spanish?

Yes, there are plenty of courses in Spanish, especially for SQL, Excel and Power BI. The catalogue mixes Spanish and English courses, and each listing shows the language of the course. For Python applied to data and for statistics, the reference courses are usually in English.