Data Visualization

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

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 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 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 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.

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.

Discover how to utilize ChatGPT within Power BI for enhanced data analysis, reporting, and interactive dashboards. Learn how to integrate ChatGPT into Power BI to create dynamic and conversational visualizations.

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

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

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

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

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

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

Explore possibilities for supercharging Power BI with R’s modeling and visualization capabilities.

In this session, we'll look at easy techniques to make your charts more effective and easier to understand, no matter if they are in Excel or PowerPoint.

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

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

Find out why pattern recognition results in faster and better understanding

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

Join a casual conversation with eDNA Expert team. They will review the technical aspects of the COVID dashboard.

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

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

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

Create a report or dashboard to help management visualize what is happening on the new app

Create a report summary of the overall services provided by a Call Centre for its management

Produce insights for management level that can highlight any issues and prepare them for the audit

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

Analyze the data of a medical emergency response service and discover opportunities for improvement on their process

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