nguyenduchuyvn / udacity-data-analysis-and-viz-with-microsoft-power-bi

This repository is for projects in Udacity's Data Analysis and Visualization with Microsoft Power BI Nanodegree Program that covers in-demand skills necessary to become a successful data analyst like data pre-processing, visualization and analysis using Microsoft Power BI as the primary tool.

Data Analysis and Visualization with Microsoft Power BI Nanodegree Program

This repository is for projects in Udacity's Data Analysis and Visualization with Microsoft Power BI Nanodegree Program that covers in-demand skills necessary to become a successful data analyst like data pre-processing, visualization and analysis using Microsoft Power BI as the primary tool.

Each project contains a detailed README file documenting the project description, specs, processes and findings.

---

Nanodegree Courses:

1. Introduction to Preparing and Modeling Data:

Covers: Power BI’s built-in Extract-Transform-Load (ETL) tool, Power Query, learn foundational data modeling principles, some introductory DAX (Data Analytics Expressions), and touch on troubleshooting and optimization.

2. Creating Visualizations with Power BI

Covers: a variety of common and more advanced data visualizations, how to design reports around these data visuals in order to focus user attention on key insights, help users navigate different features and report pages and enable accessibility options for diverse audiences, how to use filters and slicers, and deliver a couple of advanced features capable of elevating how users navigate and engage with visuals and the report itself.

3. Advanced Data Analysis

Covers: an introduction to data analysis looking at different terms and techniques such as descriptive and inferential statistics, histograms, linear regression and an introduction to the concepts of correlation and probability. After taking the introductory lessons on data analytics, the course then moves to M, the language of Power Query, and learning to build custom formulas as part of the data transformation process. The overarching goal of the course is to help students become effective at the process of retrieving, analyzing and visualizing data in order to answer questions and draw conclusions.