NEW EPISODES EVERY OTHER THURSDAY!!! The Dashboard Effect Podcast: Simplifying Data for Smarter Business Decisions Welcome to The Dashboard Effect , the go-to podcast for mid-market businesses and private equity-backed companies looking to harness the power of data. Hosted by Brick Thompson from Blue Margin, we demystify data analytics and business intelligence, offering practical insights and actionable strategies that drive accountability, performance, and growth. From breaking down complex data concepts to sharing real-world success stories, we cover topics like Power BI, data lakes, dashboards, automation, and the latest trends shaping the future of business intelligence. Whether you're a CEO, operator, or BI professional, we’ll help you unlock the potential of your data for smarter, faster decisions. Tune in to The Dashboard Effect and discover how the right data, at the right time, can transform
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The Dashboard Effect is a business podcast hosted by Unknown Host, with 174 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.
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Unknown Host hosts The Dashboard Effect, a business show with 174 episodes published.
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Episode #173
The Platinum Layer: Getting Your Data Ready for AI
Aug 5, 20269 min
The platinum layer sits on top of the standard medallion architecture, built specifically to get data ready for LLMs. In this episode, Brick and Landon break down what it takes to build one well. Landon walks through the two foundations that make a platinum layer work: markdown files that give the LLM business context and call out data gotchas, and a modeling approach that goes further than typical BI denormalization. They discuss why AI models need a single grain of data to avoid summing errors, why report-specific columns need to be stripped out, and why the platinum layer gets materialized nightly instead of served through views. They also cover the role of MCP servers in this setup, including why Blue Margin builds tightly scoped servers for business users asking direct questions and more open ones for analysts building queries. If you've been wondering what actually separates a working AI data layer from a frustrating one, this episode covers the fundamentals. Key Moments: 1:00 — Markdown Files & Context 2:05 — What Happens Without Context 2:58 — Fabric Data Agent Test 3:19 — Modeling for AI 4:25 — The Grain Problem 5:11 — Extreme Denormalization 5:28 — Cleaning Columns & Tables 6:37 — Nightly Materialization 7:43 — Why You Need an MCP Server 8:22 — Two Types of MCP Access About Blue Margin Blue Margin is a Microsoft Fabric and Power BI consultancy based in Fort Collins, Colorado. We help mid-market and private equity-backed companies build data platforms that hold up: clean architecture, trustworthy reporting, and dashboards teams actually use. The Dashboard Effect is where we talk through the technical decisions behind that work. Learn more: https://bluemargin.com
The gold layer is where cleaned, validated data lives in a medallion architecture, ready for reporting and analysis. In this episode, Brick and Landon break down what actually makes a gold layer good. Landon covers what "good" means in practice: deduplicated data, validated numbers, and a structure business users can trust without checking behind the curtain. They discuss why star schema still holds up as the standard modeling approach, how to handle naming conventions that make sense to analysts instead of source systems, and what happens when six different systems all claim to have "the customer table." They also get into the messier parts of building a gold layer: matching source system reports to catch hidden filters, deciding how to relate keys across systems without collapsing records that only look the same, and building exception reports to flag duplicates back to the business instead of quietly fixing them downstream. If you've ever wondered what separates a gold layer that works from one that just exists, this episode covers the fundamentals. Key Moments: 0:36 — What is the gold layer? 1:00 — Combining data silos 2:01 — Modeling the gold layer 2:22 — A preview of the platinum layer 2:30 — Naming conventions 3:39 — D_ and F_ naming standards 4:08 — Validating the gold layer 4:36 — Hidden filters and reporting errors 5:13 — Relating fact tables 5:57 — Handling duplicates 6:52 — Exception reports About Blue Margin Blue Margin is a Microsoft Fabric and Power BI consultancy based in Fort Collins, Colorado. We help mid-market and private equity-backed companies build data platforms that hold up: clean architecture, trustworthy reporting, and dashboards teams actually use. The Dashboard Effect is where we talk through the technical decisions behind that work. Learn more: https://bluemargin.com
Bronze, Silver, Gold: A Practical Guide to Medallion Architecture
Jul 9, 20266 min
How does raw data from a system like Salesforce become a dashboard your team can actually trust? On this episode of the Dashboard Effect, Brick and Landon walk through medallion architecture and the three stages data moves through on its way to becoming useful. They keep it simple: the first stage holds an exact copy of your source data, the middle stage cleans it up and combines data from different systems, and the final stage delivers a polished, analytics-ready view for tools like Power BI and Tableau. Landon also makes the case for keeping things lean rather than forcing every dataset through every step, and shares where speed and scale change the approach. If you're building or refining how your data flows, this is a clear, approachable starting point. About Blue Margin - Blue Margin is a fractional data and analytics team for mid-market and PE-backed companies. Acting as an extension of your team, they build and manage your data platform, shape your data strategy, and deliver Power BI dashboards that give leaders a clear, real-time view of what's driving the business. The goal is simple: turn scattered data into decisions and build a culture of accountability and growth along the way.
Everyone's asking the same question: why can't I just run all my business intelligence through AI? In this episode of The Dashboard Effect, Brick and Landon break down the real answer. You probably can, but only if your data foundation is built for it. They cover where AI analytics fit alongside traditional Power BI, why a strong medallion architecture is the difference between reliable answers and confident wrong ones, and the practical engineering that makes natural language query trustworthy. They also dig into rising token costs, vendor lock-in, and how to decide what belongs in a dashboard versus a chat window. If you run a data-driven business and you're weighing how far to push AI into your reporting stack, this one is for you. Subscribe for more conversations on data, dashboards, and getting real value from your BI. About Blue Margin - We build and manage the data foundation that turns scattered systems into reliable, AI-ready reporting, so your team gets trustworthy answers without the overhead of an internal data team. Learn more: https://www.bluemargin.com/
In this episode, the team gets hands-on with vibe coding and what it actually looks like inside real data work. From building API connections to generating synthetic datasets, they walk through where AI is genuinely speeding things up and where it still runs into friction. The big takeaway: writing code might be faster, but everything around the data still matters just as much. Blue Margin helps growing companies make better decisions with their data. From building data pipelines to creating reporting and dashboards, we handle the technical side so teams can focus on using their data—not chasing it.
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