Data Visualization

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.

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 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 designed to help you become an expert in data visualization, data storytelling, and report design. You will learn how to create advanced custom visualizations using bespoke visualization languages.

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 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 provide you the necessary skills to build full enterprise apps by integrating Power BI , Power Automate and Power Apps. 

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).

Create different types of reports within the report builder, Paginated Report

Deep dive into creating your own reusable custom visuals using Microsoft's Charticulator tool

Unlock the power of data analysis and visualization with PandasAI, and transform raw data into actionable insights that drive decision-making and growth.

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

Discover the key to unlocking insights and making informed decisions through data.

An in depth overview of the entire Power BI suite, with a focus on using Power BI to extract compelling insights from your own data.

Create stunning visualizations without advanced DAX knowledge

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

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

Advanced Tooltip Techniques

Discover various techniques to enhance and upgrade native visuals in Power BI

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

Review a number of techniques specifically around dashboarding in Power BI.

Showcase how to implement an SCD Type 2 using Power Query to allow a full historical analysis of a specific dimension

Learn how to add images to your maps, draw lines and create choropleth maps

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

Analyze Enterprise DNA's Youtube Channel Data to understand its audience and create a strategy to drive more channel engagement.

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

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

Implement your analytical skills in creating a report of the entire business operation from production to forecasting.

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

Challenge your data skills by producing a report that gives the user the ability to select a currency and see the associated sales and cost

Take on the challenge of creating an analysis report on hotels revenue management data.

A “cheat sheet” can be useful. We hereby present a “cheat sheet” for Deneb and Vega-Lite that contains several small sections with context and code snippets