Advanced Analytics

This Learning Path delves into data analysis and modeling, focusing on Filter and Row Contexts for data computations, and the use of functions like SUM, SUMX, and Calculate.

This path is designed to help you build expert level skills in the implementation, monitoring and governance of Power BI, including making optimal use of the Service through dataflows, datasets, thin reports, etc.

This path is designed to help you harness the full power of Power BI in combination with R and Python. You will learn how to conduct advanced analyses and gain insight into complex business questions.

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 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. 

This path is designed to build the broad range of expert-level knowledge necessary to confidently pass the PL-300 Data Analyst certification exam (replacement for DA-100).

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 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.

Master the most powerful tool for data modeling and DAX calculations in Power BI and Analysis Services

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

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

The first of the two-part preparation course for the Microsoft's DP-500 Exam Certification

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

Enhance your Power BI reports and analysis with R's visualization, text analysis and statistical modeling capabilities.

Advanced course using Power BI & DAX to solve complex but common business problems and scenarios you'll face everyday

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

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

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

Using visual layering and transparency masks to improve data storytelling Advanced tricks for conditional formatting icons

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

Dynamic data labels at the end of the line

Learn the best practices for transforming data in the query editor

Join a casual conversation with Sam and the Power BI Challenge Winner, Brian.

This session will cover which Python and R packages and examples can facilitate functionalities found in Power BI

Enhance your development skills by creating a supplier insights report

Challenge your data skills in creating an analysis report on substance

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

An excellent opportunity for you to create a one-page data report for Covid-19 analysis

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

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

Use the data documenter tool to create an effective report template 

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

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