P3 Adaptive
In this episode, we unpack the ‘Faucets First’ philosophy, a cornerstone of how we approach data projects at P3 Adaptive. Imagine bypassing complex infrastructures and instead, using a straightforward method that brings immediate results and clarity. It’s about being agile, practical, and impactful right from the start.
Rob is solo casting this week – discussing the growth eras over the years at P3 Adaptive, has a bit of a Mea Culpa regarding the Parquet file format and Direct Lake vs Import Mode in PBI, and shares some thoughts about the recent FTC ruling on non-compete clauses.
Dive into this episode where we’re unraveling the threads of data analytics like never before. This week, we’re zeroing in on the seismic shifts in technology that are reshaping our understanding and use of data. Imagine stepping into a world where data isn’t just numbers, but the lifeblood that pushes businesses forward.
This week we’re diving into the heart of Microsoft Fabric, armed with fresh insights from our team of experts — Will Gillingham, Mark Beedle, and Chris Haas who’ve just returned from the conference. These veterans in SQL and Power BI share their firsthand experiences and dissect the potential of Microsoft’s evolving data architecture.
Navigating the world of AI can sometimes feel like you’re trying to solve a puzzle with half the pieces missing.
Dive into the depths of AI with Rob and Justin in our latest episode where we peel back the layers of AI’s current facade. In this compelling discussion, we take a critical look at the hyped-up narratives surrounding artificial intelligence, focusing on a crucial issue at its core: the “hallucination problem.”
Everyone talks about digital transformation, but it seems like no one really explains what it means… until now. In today’s episode, Rob and Justin dive deep to cut through the buzzwords and lay out the reality. They’re tackling why digital transformation isn’t about making huge, instant changes but rather about the smart, subtle tweaks in areas that usually get ignored but badly need a digital lift.
It’s a return appearance for our good friend Matt Allington! He’s retiring this year, and we’ve invited him back to discuss this retirement (if that’s truly what it is), the semantics of the Semantic Model, the Power Platform of the Future, and so much more!
This week, Rob takes the mic solo to dive into a riveting topic, sparked by Zach from our LinkedIn Steering Committee. The question at hand is a pivotal one in the rapidly evolving realms of analytics and AI: How essential is deep industry or domain knowledge in this tech-forward era? As we race through technological advancements, is there a shift in focus from the deep-rooted sector-specific expertise to a broader emphasis on adaptability and mastering new tech tools on the fly?
Welcome to this week’s edition of Raw Data, where we’re diving into a timely discussion on the evolution of AI and its comparison with revolutionary technologies of the past, like Power BI. This episode features host Rob Collie and co-host Justin Mannhardt engaging in a deep dive into the hype cycles that have surrounded transformative tech over the years.
Daniel Harley is a prime example of the superhero type of data professional who works at P3. Coming from a rich and deep financial background – Daniel happened upon Power Query randomly several years back, and that changed the trajectory of his career greatly! Of course, the main focus of the conversation is how much the Finance and Accounting realm can be improved greatly with the help of the Power Platform. Also, quite a bit of the discussion around the 3 core financial reports – P & L, balance sheet, and cash flow and the enormous potential Power BI has to give actionable business insights that are limitless!
In this episode, Rob and Justin offer insightful methods for assessing if your organization is truly harnessing the full potential of the platform. They outline specific “symptoms” to diagnose limited impact – like lack of stakeholder excitement, delays in answering new questions, and overreliance on Excel exports.
