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

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 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 data analysis techniques, focusing on Power BI functions. It guides learners to enhance their data insight extraction skills.

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 delves into data manipulation and analysis using SQL and DAX. It covers techniques and practical code examples.

Create comprehensive financial reports in Power BI that represent key insights in a compelling and dynamic way

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

Learn the basics of SharePoint to increase productivity and collaboration, organize your data, and automate business processes

Disclose the unexpected' by expertly incorporating geospatial data into your analyses and visualizations

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

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

A detailed step-by-step process of creating high-quality Power BI reports that satisfy the requirements of real-world scenarios

Learn how to predict and optimize for results in the future, by utilizing 'what if' parameters and scenario analysis techniques

Sam McKay talks to Paul Lucassen, one of our Enterprise DNA experts, about the role of geospatial data analytics in the transportation and logistics industry

Discover sample DAX techniques that enhance business insights and explore DAX formulas to leverage conditional formatting options

An overview on Azure ML and how to incorporate it with Power BI

The different admin roles related to Power BI

Develop advanced Power BI analytical techniques

Discover how to visualize, debug, validate and solve complex DAX problems using Excel

Build a comprehensive and compelling Power BI report within an hour from scratch!

Learn advanced scenario analysis techniques and enhance your related distinct counts

Show off your impressive financial report! We are confident that your financial report is a testament to your skills and expertise. We would love to see how you've structured it and how you've made it visually appealing.

Challenge yourself to produce a report which gives HR insight into the consultation process. 

Analyze the data of a large insurance company who are due to undergo an internal audit with regard to its complaint’s procedure

Create a summary report, a task that for many data analysts will always find its way across the desk every so often

Practice your data skills and learn from what is a typical scenario faced by many businesses in various industries

An opportunity to design and build a report that gives insights into customer behavior

Enhance your development skills by creating a supplier insights report

Showcase a report that compares the trends of two different sets of data over time. The report will specifically highlight any divergences in the trends, allowing the reader to easily see any discrepancies in the data.