This repository is for projects in Udacity's Data Analysis and Visualization with Microsoft Power BI Nanodegree Program.

Program Overview:

The Data Analysis and Visualization with Microsoft Power BI program is designed to equip learners who want to develop in-demand skills in data pre-processing, visualization, and analysis using Microsoft Power BI as the primary tool. In this program I learnt to connect Microsoft Power BI to multiple data sources, process and transform data to prepare it for reporting and visualization, built compelling data visualizations that tell a story and employed best design practices, and drew insights from data dashboards and visualizations that can allow for insights and help a business make critical decisions.

Courses:

Introduction to Preparing & Modeling Data

Lesson 1: Introduction to Preparing & Modeling Data • Describe the Microsoft Power BI data Pipeline. • Recognize the range of stakeholders a data modeler should collaborate with. • Become familiar with the role of Power Query, data modeling, and reporting to meet business needs.

Lesson 2: Key Concepts in Data Modeling • Conceptualize data modeling, including fact tables, dimension tables, key columns, and relationships. • Define the role each component plays in reporting.

Lesson 3: Getting Your Data & Initial Transformations • Access a range of data sources using Get Data. • Leverage Power Query to perform initial transformations to make your queries user friendly. • Develop a familiarity with data types and their role in Microsoft Power BI.

Lesson 4: Bigger Transformations & Data Tables • Correct—and know when to correct—errors and gaps. • Make more complex column changes within queries. • Morph data across queries to align with reporting needs. • Choose and build the right data table for your purposes.

Lesson 5: Relationships & Relationship Related DAX • Select the correct relationships for your data model. • Create implicit and quick measures. • Leverage relationships and filters in common DAX functions.

Lesson 6: Reports & DAX for Common Reporting Needs • Choose between a measure and calculated column. • Create basic report visualizations such as Matrixes and Cards. • Make DAX functions that leverage conditional logic. • Troubleshoot and organize your Microsoft Power BI file

Creating Visualizations with Microsoft Power BI

Lesson 1: Welcome to Creating Visualizations with Microsoft Power BI • Describe the learning objective of the course. • Explain why data visualization is important for business intelligence. • Identify the main stakeholders that BI analysts interact with. • Identify when data visualization is useful and when it is not.

Lesson 2: Building Compelling Data Visualizations • Identify important business metrics and pair them with appropriate data visuals. • Build common data visuals, including bar charts and line charts. • Design complementary visuals, including cards, donut charts, and tables. • Build more complex data visuals, including scatter plots and bubble maps. • Recognize standard formatting options for Microsoft Power BI visuals and navigate the unique formatting features that vary between visuals.

Lesson 3: Designing User-Friendly Reports • Customize Microsoft Power BI themes with unique color palettes. • Insert elements like images, shapes, and buttons to create compelling and versatile layouts for their reports. • Apply design principles that reduce noise and highlight data stories. • Maximize accessibility for diverse user groups.

Lesson 4: Creating Interactive Reports for Data Exploration • Design visuals that interact with one another and help users explore data by filtering and drilling for insights. • Identify the differences between filters and slicers in a Microsoft Power BI report, including when to use each and differences in functionality. • Apply filters to data visuals, pages, and reports. • Customize the filter pane for reporting needs. • Help users explore the data with different types of slicers

Lesson 5: Elevating Reports with Advanced Report Features • Customize Microsoft Power BI reports in ways that foster interactivity and help users tell compelling data stories. • Build custom data stories with Microsoft Power BI bookmarks. • Empower users with navigation buttons. • Design drill-through pages for deep-dive analysis.

Advanced Data Analysis

Lesson 1: Welcome to Advanced Data Analysis in Microsoft Power BI • Describe the learning objectives of the course. • Explain what data analysis is and why it’s important. • Identify the main stakeholders that data analysts interact with. • Identify when data analysis is useful and when it is not.

Lesson 2: Advanced Data Analytics • Define, investigate, and analyze data in order to draw conclusions. • Use historical analysis to investigate, aggregate, and describe data. • Use predictive analysis to understand relationships between data and forecast the probabilities of future outcomes

Lesson 3: Power Query Transformations • Compare and contrast Power Query and DAX. • Use M in Power Query to manually edit table columns. • Write custom formulas using the advanced editor in order to effectively clean and format imported data.

Lesson 4: DAX Functions • Write custom DAX formulas to perform calculations or format data. • Use DAX to create calculated tables. • Troubleshoot common DAX errors and fix the underlying issues with their code.

Lesson 5: Advanced Visualizations • Use advanced visualizations in order to analyze data and draw conclusions. • Distinguish between advanced and standard visualizations. • Customize advanced visualizations with filters, formatting, and trend analysis.