One of the most valuable things that you can do to accelerate your learning and career right now with AI & agents is to stop thinking in terms of tools and platforms. Don't box yourself in; do the opposite.
For instance, don't think only about Power BI if you're a "power bi" person; likewise for Tableau, Qlik, etc. You don't have to be the <tool> person anymore and I don't think it's helpful to think that way right now, at all.
Zoom out. Focus on the actual business problems and agnostic theory in your professional or interest space - both horizontally and vertically. Consider in that problem space what useful, effective (in cost and results) solutions actually look like. Be as much as possible solution and value-driven.
Step outside your comfort zone and your stack / vendor bubble and look broadly at what's happening in your market. Experiment and think outside the box; flex your brain and try things that seems outlandishly outside of your expertise area. You will experience some helpful friction and learn a lot.
If you are continuously focusing on using AI and agents with one specific tool or platform it's a bit the equivalent of using a power drill to make a better screwdriver. It might be the easiest and most immediately helpful in your job, but i don't think it's the most effective path forward for personal development (it might even be dangerous or counter productive). I don't think it's the best way to prepare for what this next "era" is shaping out to be.
The DAX Columns debate is happening.
On April 10th, I’m going live with @Datatouille to debate one of the most controversial topics in the Microsoft Fabric world right now: DAX Columns.
Some people believe they unlock new modeling flexibility.
Others believe they introduce performance and design problems that modern Fabric architectures should avoid.
So instead of arguing in comment threads… we’re doing it live.
Expect:
Real architectural discussion
Strong opinions from both sides
Practical use cases and counterarguments
Audience questions during the stream
If you care about semantic models, Fabric architecture, or Power BI performance, this one should be fun.
Join the debate here:
https://t.co/k8Kvbq43TY
April 10th — bring your opinions.
#MicrosoftFabric #PowerBI #DAX #DataModeling #Analytics
@_so_bored D'ailleurs, OpenAI & Mistral utilisent des consultants (internes ou partenaires) pour faciliter le déploiement et l'adoption de leur IA dans les entreprises.
Ne soyons pas binaires. Tout est toujours dans la nuance.
(2/2)
@_so_bored Certaines* pas tout
Et leurs missions correspondaient plus à de l'intérim qu'à du vrai conseil à forte valeur ajoutée.
Fort heureusement, il existe encore des boîtes de conseil qui ont une vraie expertise et apportent de la valeur
(1/2)
In this blog post I do a direct comparison between a Lakehouse (Python) and a Warehouse (SQL) to which one is faster and cheaper in #MicrosoftFabric https://t.co/Xc7Xdi1TN8
@GuillaumeRozier@cbatdm@EquipeFRA Complètement illisible oui. J'en parlais dans mon précédent tweet.
Tu peux t'appuyer sur l'IA pour te générer une palette de couleurs adaptées et accessibles en 5 secondes: https://t.co/gfAMC5qELj
@_Re_@StephaneMallard Plus sérieusement, mon ton sarcastique est surtout pour tourner en dérision ces prédictions qui me semblent totalement invraisemblables.
Je ne crois pas à ce scénario, encore moins dans cette temporalité (12-18 mois)...