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¡Bienvenido de nuevo a "El Puente al Machine Learning"! En el capítulo anterior, conectamos nuestro entorno a un origen de datos. Ahora, vamos a arremangarnos y hacer lo que define el 80% del trabajo de un analista: la limpieza de datos. Seguro te ha...

¡Bienvenido al tercer capítulo de "El Puente al Machine Learning"! En el post anterior, instalamos nuestro laboratorio de ciencia de datos. Ahora que tienes tu entorno listo, es hora de hacer lo que mejor sabemos hacer: conectarnos a un origen de dat...

YouTube is not just entertainment — it’s data gold. Every like, view, and comment tells a story. In this project, I built a YouTube Content Intelligence Platform using SQL, Python, and Power BI to uncover what drives engagement, subscriber growth, an...

Workflow Consolidate all data Build a data model Established foundational DAX measures for KPIs Store each KPI in the Power Pivot Develop a dashboard designed for end users, allowing them to understand the results easily. Tools Tools:MS Excel...

Dynamic queries let you adapt your data transformations on a whim without having to manually edit each step in the transformation that would be affected by the change. This can be done using parameters. What are Parameters in M Code? Parameters are v...

Power BI's data transformation has two interfaces, there is the Graphical UI where you can select different preselected steps to put them in a certain order and there's also the M code editor where you can dive straight into the code behind the trans...

Most Power BI users rely on the Power Query UI for data transformations, this is the window that opens up when you click "Transform data" in the Home tab. Clicking and adding different steps in the Transform window actually generates M code. opening ...
