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 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 path is focused on developing expert level skills in data cleaning, data transformation and data modeling. You will learn to maximize the capabilities of the Power Query UI, and also write M code.

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 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 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).

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

Learn how to develop complete Power BI solutions that look compelling and deeply engage your consumers in your insights

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

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

Learn how to transfer your knowledge of SQL to DAX and vice versa

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

Become a better data storyteller by learning techniques to create reports that inspire and have an impact.

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

Incorporate multiple variables within function using List.Generate

Develop advanced Power BI analytical techniques

Focus on financial reporting techniques in Power BI. We will be building a PnL statement from scratch, utilizing all the key features of Power BI.

Learn how to swap or rotate fields around in a visual and how to implement complex slicer interactions using field parameters

Learn how to clean, optimize and model data tables to develop effective, insightful and actionable Power BI reports

Power BI Freestyle Session w/ Sam McKay

Provide a business solution by creating an intelligence tool to use by large opticians

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.

Use the data documenter tool to create an effective report template 

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

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

Analyze data from marketing campaigns and initiatives, using visualization tools and statistical analysis techniques to identify trends and patterns, and use these insights to inform marketing strategy and decision-making.

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.

Identify trends and patterns in a variety of factors that influence the cost of living in different regions around the world by using statistical analysis techniques and visualization tools.