You do not rise to the level of your goals, you fall to the level of your systems. In this session, you'll get hands-on methods for making documentation a natural part of your Power BI workflow. We'll explore Power Query metadata, Table Groups and scripting in Tabular Editor, INFO.VIEW DAX functions, external tools, model layout views, VertiPaq Analyzer in DAX Query views, Semantic Link Labs, and JSON theme documentation. Everything is tied together in a user-friendly, accessible app – where the end user meets the documentation directly. This isn’t just inspiration – it’s a system you can take home and apply. A Power BI documentation system – not just an afterthought.

This will be a 15 minute demo of a Personal Spending Dashboard using dummy data based on Monzo's Bank Statement in CSV format. This dashboard gamifies personal spending habits and acts as an alternative to the cumbersome process of handling monthly household budgets. The talk will outline visuals, key DAX measures and Power Query connections to the data model.

This session demonstrates how Python integrates with Excel to analyze data directly inside spreadsheets. What you will learn: Python libraries available in Excel; Different ways to insert Python codes in Excel; Advanced charts for Data Science in Excel.

In this session, Reza shares tips, tricks, and techniques for capturing errors in Power Query and using them to present exception reporting in Power BI. Expect to learn techniques using Power Query and M in Power BI and Dataflow.

During this meetup, we'll explore the practical applications of Power Query M. You will see how leveraging the power of lists can enhance your ability to manage extensive columnar data-sets. We'll also discuss their role in streamlining time-related operations.