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Data Talk Episodes

Data Talk is where we slow down and unpack the entire Microsoft data stack — from self-service to enterprise, from Excel users to lakehouse architects.
This is Power BI, Microsoft Fabric, SQL Server, Synapse-DNA lineage, Dataverse, Lakehouse, Warehouse, Real-Time Analytics, semantic models, data governance, DAX patterns, dataflows, pipelines — and the craft of turning raw data into actual intelligence that impacts business decisions.

We talk about how the pieces fit — not just the tool buttons.
Data modelling logic, semantic modeling best practices, enterprise data product thinking, proper star schema design, delta table decisions, Power BI report performance tuning, how to operationalise Fabric workloads, how to treat Power BI as a “first-class” enterprise platform and not a wild west of “dashboard in five minutes” chaos.

We cover governance deeply: capacity planning, workspaces strategy, managed vs unmanaged lakes, sensitivity labels, lineage, data mesh vs data swamp, self-service enablement frameworks, adoption and literacy programs, federated ownership, and the “balance of freedom vs control” that every organisation struggles with.

We also talk human business dynamics — because data is ultimately not a tech project. It is a decision-making multiplier.
We are here to surface the patterns that create trusted, reliable, explainable, well-governed analytic landscapes — not one-off Power BI hero dashboards.

If it moves data, visualises data, secures data, or makes data make sense — it belongs in Data Talk.
Sept. 18, 2025

Domains in Fabric: Easier Than It Looks? (Spoiler: No)

Microsoft Fabric domains are quickly becoming one of the most important pillars of governance and organization inside the Fabric ecosystem, and in this episode we break down exactly how they work and why they matter. You’ll learn how domains create logical groupings of workspaces and data assets, h…
Sept. 18, 2025

LINQ to SQL: Magic or Mayhem?

LINQ to SQL remains one of the most approachable ways to query and manipulate relational data in .NET, and in this episode we break down exactly how it works, why it’s so powerful, and how it simplifies database interaction compared to traditional SQL and ADO.NET patterns. You’ll learn how LINQ to …
Sept. 11, 2025

Microsoft Fabric Changes Everything for BI Pros

This episode explains how Microsoft Fabric can significantly elevate the work of Power BI professionals by unifying data engineering, governance, storage, and analytics into one platform. It shows how Fabric enhances existing Power BI workflows without forcing teams to redo their reports or models.…
Aug. 17, 2025

Fabric Dataflows Gen2: The Future of ETL in Microsoft Fabric

Fabric Dataflows Gen2 turns scattered Power Query/ADF jobs into a single, reusable ETL asset that feeds Lakehouse, Warehouse, and Power BI—backed by separate, elastic compute and managed staging. Translation: faster refreshes, zero zombie temp tables, consistent logic everywhere, and Git-native col…
Aug. 16, 2025

Dynamics 365 Embedded Analytics with Fabric & Power BI

Stop exporting Dynamics 365 data to Excel. Connect Dataverse to Microsoft Fabric, build an analytics model once, and embed Power BI directly inside Dynamics 365 (CRM/ERP) screens. With live, role-aware metrics (RLS), sales and ops teams act on fresh data without tab-switching, stale snapshots, or v…
Aug. 16, 2025

Fabric Lakehouse Governance & Data Lineage

Stop guessing where your data went. In Microsoft Fabric, automatic lineage, workspace-based permissions, and Purview’s enterprise catalog turn opaque pipelines into auditable, end-to-end flows—from ingestion to transformation to the report. Fabric captures every hop (Data Factory, Lakehouse, notebo…
Aug. 15, 2025

Fabric Data Activator for Real-Time AI Insights

Stop waiting on dashboards. Fabric Data Activator turns live signals into instant actions—pausing bad pipelines, placing purchase orders, opening D365 work orders, or triggering API calls the moment thresholds hit. Because it’s native to Microsoft Fabric, it listens to streams and models from Power…
Aug. 14, 2025

Using Microsoft Fabric Notebooks for AI Model Training

Stop torturing your laptop. Train models where the data lives. With Microsoft Fabric notebooks running on Spark next to your Lakehouse, you skip CSV exports, move terabytes at query speed, and iterate in Python or R without memory crashes. Push transforms to the data, engineer features at scale, mo…
Aug. 14, 2025

Dataverse Deep Dive: Designing Scalable Data Models

Dataverse “slowness” is often schema, not size. Fix table bloat, simplify relationships, and add the right indexes to turn crawling forms and timing-out flows into crisp responses. Design for performance from day one—balance normalization, limit cascades, and index what you filter on.
Aug. 13, 2025

Integrating Dynamics 365 Sales Data into Microsoft Teams

Stop context-switching. Embed Dynamics 365 Sales directly into Microsoft Teams so reps update opportunities, trigger approvals, and log notes where they already work. Layer Power Automate and Adaptive Cards to turn chats into actions (create/update/approve) and keep CRM as the single source of trut…
Aug. 12, 2025

Building Reusable Semantic Models with Microsoft Fabric

Most Power BI environments start fast and stall under copy-paste sprawl: duplicated PBIX files, conflicting measures, and “spreadmart” dashboards that nobody fully trusts. The fix isn’t another naming convention—it’s a model-first architecture. Microsoft Fabric elevates the semantic model to an ent…
Aug. 12, 2025

Optimizing Lakehouse Performance in Microsoft Fabric

When Fabric queries crawl and cloud costs spike, the fix usually isn’t more compute—it’s better Lakehouse design. This episode shows how three practical levers deliver immediate wins. First, partitioning: stop defaulting to “date” and align keys to real filter patterns to avoid wide scans or metada…
Aug. 10, 2025

Securing Data Pipelines in Microsoft Fabric

Microsoft Fabric pipelines often feel “secure by default,” but silent data exposure usually comes from misconfigured permissions, hardcoded secrets, and overbroad workspace roles. This episode shows how to harden end-to-end pipelines with managed identities (kill passwords), Azure Key Vault (centra…
Aug. 10, 2025

Automated Testing for Power Apps and Dataverse

Low-code does not mean low risk. Power Apps and Dataverse sit at the center of many business-critical processes, so skipped testing leads to silent data loss, broken approvals, and security leaks. This episode shows how to build a real testing strategy for the Power Platform: automate end-to-end sc…
Aug. 10, 2025

Managing Git Integration with Microsoft Fabric Notebooks

Microsoft Fabric’s Git integration isn’t a backup—it’s the backbone of safe, scalable collaboration on notebooks, pipelines, and models. This guide explains why merge chaos happens, what actually syncs to Git (code/metadata) vs. what doesn’t (Lakehouse data), and the one switch that saves teams: ad…
Aug. 9, 2025

Fabric Notebooks for Data Transformation and ML

Stop wrestling Power BI with endless clicks. Microsoft Fabric Notebooks let you prep, model, and feature-engineer data end-to-end—in Python or R—right inside your Lakehouse with Spark scale and Git governance. This guide shows a proven workflow: ingest to Bronze, clean and join to Silver, feature-e…
Aug. 8, 2025

Extending Microsoft Fabric with Custom APIs and Power BI Models

Fabric’s UI is great for quick wins—but it hits limits with niche data sources, complex business logic, and real-time automation. The way through is building custom API integrations (secure, least-privilege, monitored) and surfacing them with Power BI semantic models (single source of truth, govern…
Aug. 8, 2025

Building Customer Portals with Power Pages + Dataverse

Stop emailing Dataverse exports. Build a branded, secure, customer-ready portal with Power Pages that shows the right records to the right people—nothing more. This guide gives you a step-by-step build, least-privilege web roles/table permissions, and a go-live checklist (auth, data scope, branding…
Aug. 8, 2025

Building Machine Learning Models in Microsoft Fabric

Ship ML faster on Microsoft Fabric. This guide shows how to go from Lakehouse data to production models—without the spreadsheet chaos. You’ll get a practical blueprint for curated data layers, reproducible notebooks, MLflow tracking, governed model registry, and one-click batch/real-time serving. I…
Aug. 7, 2025

Using Copilot in Microsoft Fabric to Build Data Models

This episode breaks down where Microsoft Copilot truly speeds up data work in Microsoft Fabric—and where you still need a human in the loop. You’ll see how Copilot catches schema issues at ingestion, suggests fixes (naming, types, dates, partitions) before pipelines break, and then accelerates tran…
Aug. 6, 2025

Implementing Row-Level Security in Power BI with Fabric

This episode shows why Row-Level Security (RLS) in Power BI isn’t a checkbox—it’s a living system. We unpack the parts that actually decide who sees what: model relationships, role design, DAX filters (static vs dynamic), Azure AD group assignments, and the identity shifts that happen when you publ…
Aug. 5, 2025

Monitoring Data Pipelines in Microsoft Fabric

This episode shows you how to stop flying blind in Microsoft Fabric by designing a proactive, system-level monitoring strategy. We break monitoring into four pillars—performance metrics, error logging, data lineage, and automated recovery—then wire them together so issues surface early, route to th…
Aug. 5, 2025

Customizing Dataverse for Complex Business Apps

Tired of Dataverse apps that fly with 10 users and crumble at 100? This episode shows how to design for scale by treating relationships, logic, calculated fields, and alternate keys as first-class citizens—not afterthoughts. You’ll learn how to keep performance predictable, automation consistent, i…
Aug. 5, 2025

Building Ingest Pipelines in Microsoft Fabric for Enterprise Data

If your Microsoft Fabric ingest “works” until a random Monday dashboard explodes, this episode is your wake-up call. We tear down the real difference between Dataflows Gen2 and direct Pipeline copy—and why picking wrong quietly injects duplicates, truncations, and schema-drift chaos into your lakeh…