Advanced Analytics

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

This Learning Path offers a comprehensive journey through data visualization and analysis techniques, with a special emphasis on Power BI.

This Learning Path provides a deep dive into Power BI and DAX, focusing on data analysis techniques and visualization. It equips learners with skills to craft dynamic visualizations.

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

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

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

Create advanced analytical models by learning how to harness the power of DAX calculations for use within Power BI

Expand Power BI's capabilities in accessing a wide range of data using APIs

Improve the overall performance of your DAX measures using the DAX Studio

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

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

Dynamic data labels at the end of the line

Learn how simple resources can generate amazing results in the charts, applicable to any analysis.

In this presentation, you will learn the new LAMBDA function in Excel. How to use this to simplify functions that do not currently exist. 

Data story telling is an important part of the report development process. It changes the way the audience views reports.

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

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

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

On this session, Cristiano Galvao MVP will cover the impact of recent changes in Excel that unleash the power of formulas. 

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 in creating an analysis report on substance

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

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

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

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

Use the data documenter tool to create an effective report template 

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

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