Advanced Analytics

This path will provide you in-depth knowledge of the full range of Power BI best practices, with particular emphasis on building data models specifically optimized for Power BI.

This path is similar to the Data Analyst learning path above, but is geared to building a strong and broad foundation of data analysis skills, as compared to being more specifically focused on passing the PL 300 exam.

This Learning Path in statistical analysis and inference equips learners with practical skills to conduct tests, estimate sample sizes, and understand test assumptions. 

This Learning Path delves into data analysis techniques, focusing on Power BI functions. It guides learners to enhance their data insight extraction skills.

This path is the most in-depth and rigorous on the list, designed to provide you expert-level skills in all of the key pillars of Power BI. 

This Learning Path delves into Power BI development, focusing on creating effective reports and visualizations. It covers parameter management, using PowerPoint and more!

This Learning Path delves into data analysis and visualization using both R and Python, covering data cleaning, data frames, and the use of packages like dplyr, tidyverse, skim R, and seaborn. It offers hands-on examples, such as creating various plots, performing group-based operations, and utilizing descriptive statistics for effective data interpretation.

This learning path offers a deep dive into data management and analysis, emphasizing the hands-on use of Python and Scala languages for manipulating CSV and JSON files, and the application of SQL for data querying. 

Implement advanced & practical analytical techniques inside of Power BI and find insights you never thought possible in an intuitive way

Level up your SQL query fluency even without prior SQL experience.

Amplify your Power BI visualizations with R's comprehensive statistical analysis and graphics language

Learn valid inference techniques for two-sample and two-variable data questions.

Master key data modeling and DAX concepts and techniques to optimize performance in Power BI

Dramatically enhance Power BI's capabilities by incorporating Python's flexible and powerful data wrangling, data analysis and data visualization functionality

Master the ultimate tool for executing and analyzing DAX queries against various sources including Power BI and SSAS

Clean data and perform Natural Language Processing through Python's functions, algorithms and programming methods

Learn about the three fundamental rules that should guide your decision on choosing the correct type of chart

Learn the best practices for transforming data in the query editor

Showcase the best techniques around bookmarks, tooltips, selections, drillthrough & theming

Relationship best practices in Power BI

Develop compelling dashboards within Power BI using a range of analytical and visualisation techniques

Expert walk-through of week #1 solution with Sam McKay and Brian Julius

Identify trends in sales and customer behavior and assess the performance of different stores or regions using the LFL Analysis in Retail

Dynamic data labels at the end of the line

Take a deep dive into the world of utilisation and timesheet data

Deep dive into the world of F1 and create an analysis of the drivers' stats

Develop an analysis report about the Football/Soccer Players Summer Transfers Season 2022-23

Challenge your data skills in creating an analysis report on substance

Create an analysis report on environmental data and potentially impact how this data is visualized and recorded

Jump into this twitter related dataset and showcase some interesting insights based on the text of the tweet and the stock reference or tagged within the tweet itself.

Challenge your data skills by creating a report on transport and shipping data 

Use the data documenter tool to create an effective report template 

This Excel formulas cheat sheet covers advanced forecasting formulas, statistical analysis, data manipulation functions, error handling, and more.