Renato Lira
Petrobras, Senior Data Analyst
Rio de Janeiro, Brazil
Renato is a data analyst based in Brazil that is fascinated with DAX and M.
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Power Query Custom Functions 101
Power Query is a great ETL tool that meets most business user needs with an intuitive user interface.
It introduces the concept of custom functions, which you can use to reuse your code multiple times, making your applied steps clearer and easier to maintain and understand.
We will explore two approaches: editing M from the advanced editor or using the Power Query UI.
By the end of this session, you will fully comprehend when, how, and why you should use custom Power Query functions.
Descobrindo o DirectLake: A Nova Era do Power BI
Nesta apresentação, mergulharemos na mais recente inovação da Microsoft Fabric: o DirectLake. Enquanto o Power BI já é amplamente reconhecido por seus modos tradicionais de armazenamento de dados, como Import e Direct Query (seja com SQL ou Analysis Services), o DirectLake promete revolucionar a forma como interagimos com grandes conjuntos de dados.
Vamos explorar o OneLake, uma solução integrada que utiliza arquivos Parquet no formato Delta. Esta inovação não só otimiza o armazenamento e a consulta de dados, mas também combina os benefícios do Direct Query com a potência do DAX, proporcionando uma experiência de análise de dados sem precedentes.
Junte-se a nós para entender como o DirectLake está definindo o futuro da análise de dados com o Power BI.
CALCULATE evaluation order
CALCULATE is the most important DAX function, yet its usage is still a challenge even for the most seasoned DAX developers.
In this session I’ll show you a practical, visual and less verbose steps that are performed to evaluate the CALCULATE expression that has multiple filters/modifiers.
To do so I’ll do a quick recap of CALCULATE filters/modifiers, evaluation order and precedence within nested CALCULATEs so we can deep dive into the multiple filters/modifiers within the same CALCULATE.
Migrate your ETL to Dataflows
Power BI Dataflows are great: fast and reusable! But who tried to implement some of the best practices described in the documentation might have lost some hair due to non-trivial error messages.
There are some hidden traps that you might fall if you try to implement a chain of Dataflows in the same workspace or replicate the incremental refresh that works on the dataset but not in Dataflows.
In this session we'll move ETL steps created in a Power BI Desktop to an architecture using a chain of Dataflows.
We'll discuss pros and cons of different architectures of the chain of Dataflows depending on its sources or update frequency.
In the end, we'll learn how to successfully set up incremental refresh to a table that doesn't have a datetime column.
Data Saturday Vitória 2023 (#1065) Sessionize Event
Renato Lira
Petrobras, Senior Data Analyst
Rio de Janeiro, Brazil
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