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  Last week was the 5th online edition of my 𝗥 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 workshop. And I experienced such a proud teacher moment when one participant showed me this plot at the end of the fourth day. It might not look like much, but it truly is. I was really excited for them. Let me explain why. Four days prior, my student knew nothing about coding in R or any other language. A proper rookie.

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  In the past months, I've thought a lot about data science, its current ecosystem, and how much more efficient learning has become in recent years. (Without even talking about AI doing your mundane tasks.) There are so many great tools that let you bypass technical bottlenecks and focus on the core task of making sense of your data. So the big challenges are still here, but at least you have fewer distractions. 😅 https://manuelchevalier.com/

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  🚨 Last days before the workshop. 50% discount if you contact me here or by email. Among other things, we will cover: - Data types and structures - Loading your data in R - Organising your workflow for reproducibility - Master pipelines to connect your work - Data wrangling (cleaning data, aggregating fields, merging datasets) - Data visualisation with ggplot2 Take control of your data journey. Today. 📆 August 3-7, 2026 📍 Live & interactive, online 🎟️ https://datasharpacademy.com/workshop-...

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  I’ve politely ignored the dbplyr R package for years. I simply didn’t think I needed it. I had never had issues with databasing from R or Python. What could it bring me? Once I understood its real value, I felt a bit stupid. I never had any issues because I already knew SQL (i.e., the language for talking to most relational databases). https://manuelchevalier.com/running-extracting-data-dbplyr/

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  I've often been lured by the word "database". For me, it means clean, structured data, formal relationships between tables, no (or limited) duplicate rows, etc. When someone tells me they have a database, I instinctively picture a relational database. It turns out that the perception of what a database is *really* depends on who you are talking to. For some, a "database" may well be a folder with a collection of CSV files with different data structures. For me, that&#...

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  Properly loading real-life data in R is hard. And a skill to learn before anything else. Because being able to run sophisticated models won't matter if you can't load your data. 📆 August 3-7, 2026 📍 Live & interactive, online 🎟️ https://datasharpacademy.com/shop/r-fundamentals-workshop/

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  Have you ever wondered what these strange-looking symbols |> or %>% AI keeps spitting really mean? They are actually beautiful things that make your data processing sooo much easier once you get the logic. These pipe operators ( |> or %>% ) can be interpreted as follows: "take the result of the transformation on the left-hand side of the operator and use it as input to the transformation on the right-hand side". Nothing less, nothing more. Elegant and efficient.

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  Recently, I got really fed up with the constant AI noise. Every week seems to bring another tool that promises to revolutionise data science. Another model. Another workflow. Another miracle. 😮‍💨 Yet most of the data science I actually do still looks remarkably ordinary. https://manuelchevalier.com