Advanced Analytics

This Learning Path offers a comprehensive journey through advanced data analysis and modeling techniques all illustrated through practical scenarios.

This Learning Path offers a comprehensive journey through data visualization and analysis techniques, with a special emphasis on Power BI.

This learning path provides a thorough understanding of SQL, emphasizing key commands for data manipulation and querying. 

This Learning Path delves into data analysis and visualization using both R and Python, covering data cleaning, data frames, and the use of packages like dplyr, tidyverse, skim R, and seaborn. It offers hands-on examples, such as creating various plots, performing group-based operations, and utilizing descriptive statistics for effective data interpretation.

This Learning Path delves into data analysis techniques, focusing on Power BI functions. It guides learners to enhance their data insight extraction skills.

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 offers a deep dive into data management and analysis, emphasizing the hands-on use of Python and Scala languages for manipulating CSV and JSON files, and the application of SQL for data querying. 

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.

Dramatically enhance Power BI's capabilities by incorporating Python's flexible and powerful data wrangling, data analysis and data visualization functionality

Enhance your Power BI reports and analysis with R's visualization, text analysis and statistical modeling capabilities.

Expand Power BI's capabilities in accessing a wide range of data using APIs

A practical guide to recognizing, understanding, and managing uncertainty in data 

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

Amplify your Power BI visualizations with R's comprehensive statistical analysis and graphics language

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

Learn valid inference techniques for two-sample and two-variable data questions.

Relationship best practices in Power BI

In this presentation, we would be developing a solution a simple solution to bulk rename files and folders in a folder.

In this sessions we will start from what you need to know about Azure AD in relation to Azure data services.

This session will cover which Python and R packages and examples can facilitate functionalities found in Power BI

Learn beginner to advanced DAX function techniques

The session include function Let and how to declare and using parameters in Power Query and DAX

Covers the use of quick measures and the features

Use the data documenter tool to create an effective report template 

An excellent opportunity for you to create a one-page data report for Covid-19 analysis

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

Challenge your data skills by creating a report on transport and shipping data 

Enhance your development skills by creating a supplier insights report

Develop an analysis report about the Football/Soccer Players Summer Transfers Season 2022-23

Jump into this twitter related dataset and showcase some interesting insights based on the text of the tweet and the stock reference or tagged within the tweet itself.

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

This Excel formulas cheat sheet covers advanced forecasting formulas, statistical analysis, data manipulation functions, error handling, and more.