Business Analytics

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

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

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.

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

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

This module discusses the different features of the Analyst Hub platform and the tips to maximize the use of tools to enhance Power BI development.

Build a strong foundation on your MS Excel skills as you progress to advanced level

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

Master the ultimate tool for executing and analyzing DAX queries against various sources including Power BI and SSAS

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

Review some of the best practices to refine your Power BI development skills

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

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

Solve advanced analytical questions using Power BI

Learn necessary elements to resolve granularities mismatches in different ways

Use Power Query/ M effectively to prepare data for analysis

Learn a range of advanced techniques in Power BI using DAX

Extracting Records has always been an important task for Excel users. In this session, you will learn how this task evolved

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

Use the data documenter tool to create an effective report template 

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

Enhance your development skills by creating a supplier insights report

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

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.

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.

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.