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  <title>Figuring Out Fabric: Learn Fabric in 30 minutes.</title>

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  <itunes:author>Eugene Meidinger</itunes:author>
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  <description><![CDATA[<p>Each week I’ll be interviewing experts and users alike on their experience with Fabric, warts and all. I can guarantee that we’ll have voices you aren’t used to and perspectives you won’t expect.<br><br></p><p>Each episode will be 30 minutes long with a single topic, so you can listen during your commute or while you exercise. Skip the topics you aren’t interested in. This will be a podcast that respects your time and your intelligence. No 2 hour BS sessions.</p>]]></description>
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    <itunes:title>Ep. 28 Getting the Badge vs. Actually Learning Fabric </itunes:title>
    <title>Ep. 28 Getting the Badge vs. Actually Learning Fabric </title>
    <itunes:summary><![CDATA[In this episode Aleksi Partanen about certifications, learning Fabric, and community. We talk about the Fabric certs and how much value they do or do not provide. We talk about community and motivations for being involved and cultivating communities.  YouTube: Aleksi Partanen – Master Microsoft Fabric Fabric Forge: skool.com/fabricforge CertiAce: certiace.com Subreddit mentioned in the episode: r/MicrosoftFabric ]]></itunes:summary>
    <description><![CDATA[<p>In this episode Aleksi Partanen about certifications, learning Fabric, and community. We talk about the Fabric certs and how much value they do or do not provide. We talk about community and motivations for being involved and cultivating communities.<br/><br/>YouTube: <a href='https://youtube.com/@AleksiPartanenTech'>Aleksi Partanen – Master Microsoft Fabric</a><br/>Fabric Forge: <a href='https://skool.com/fabricforge'>skool.com/fabricforge<br/></a>CertiAce: <a href='https://certiace.com/'>certiace.com</a><br/>Subreddit mentioned in the episode: <a href='https://reddit.com/r/MicrosoftFabric'>r/MicrosoftFabric</a></p>]]></description>
    <content:encoded><![CDATA[<p>In this episode Aleksi Partanen about certifications, learning Fabric, and community. We talk about the Fabric certs and how much value they do or do not provide. We talk about community and motivations for being involved and cultivating communities.<br/><br/>YouTube: <a href='https://youtube.com/@AleksiPartanenTech'>Aleksi Partanen – Master Microsoft Fabric</a><br/>Fabric Forge: <a href='https://skool.com/fabricforge'>skool.com/fabricforge<br/></a>CertiAce: <a href='https://certiace.com/'>certiace.com</a><br/>Subreddit mentioned in the episode: <a href='https://reddit.com/r/MicrosoftFabric'>r/MicrosoftFabric</a></p>]]></content:encoded>
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    <pubDate>Mon, 17 Aug 2026 06:00:00 -0400</pubDate>
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    <itunes:duration>1586</itunes:duration>
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    <itunes:season>1</itunes:season>
    <itunes:episode>28</itunes:episode>
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    <itunes:title>Ep. 27 Fabric Pipelines vs. Dataflows vs. Notebooks</itunes:title>
    <title>Ep. 27 Fabric Pipelines vs. Dataflows vs. Notebooks</title>
    <itunes:summary><![CDATA[Fatima Jallow, a data consultant based in Stockholm, helps us understand data movement in Fabric and when to use pipelines and dataflows. We talk about how pipelines specialize in orchestration. She shares with us her journey from executive assistant to data architect. Finally she talks about some challenges building a metadata-driven pipeline in Fabric from scratch. Resources FeedlyFatima Jallow on LinkedInSwedish Power BI &amp; Fabric User GroupData Saturday Stockholm]]></itunes:summary>
    <description><![CDATA[<p>Fatima Jallow, a data consultant based in Stockholm, helps us understand data movement in Fabric and when to use pipelines and dataflows. We talk about how pipelines specialize in orchestration. She shares with us her journey from executive assistant to data architect. Finally she talks about some challenges building a metadata-driven pipeline in Fabric from scratch.</p><p><b>Resources</b></p><ul><li><a href='https://feedly.com'>Feedly</a></li><li><a href='https://se.linkedin.com/in/fatima-jallow-47298919'>Fatima Jallow on LinkedIn</a></li><li><a href='https://www.meetup.com/swedish-power-bi-user-group/'>Swedish Power BI &amp; Fabric User Group</a></li><li><a href='https://datasatsto.se/'>Data Saturday Stockholm</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>Fatima Jallow, a data consultant based in Stockholm, helps us understand data movement in Fabric and when to use pipelines and dataflows. We talk about how pipelines specialize in orchestration. She shares with us her journey from executive assistant to data architect. Finally she talks about some challenges building a metadata-driven pipeline in Fabric from scratch.</p><p><b>Resources</b></p><ul><li><a href='https://feedly.com'>Feedly</a></li><li><a href='https://se.linkedin.com/in/fatima-jallow-47298919'>Fatima Jallow on LinkedIn</a></li><li><a href='https://www.meetup.com/swedish-power-bi-user-group/'>Swedish Power BI &amp; Fabric User Group</a></li><li><a href='https://datasatsto.se/'>Data Saturday Stockholm</a></li></ul>]]></content:encoded>
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    <pubDate>Tue, 04 Aug 2026 16:00:00 -0400</pubDate>
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  <psc:chapter start="2:13" title="When to use pipelines" />
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    <itunes:title>Ep 26. - Balancing keeping up with old and new tech</itunes:title>
    <title>Ep 26. - Balancing keeping up with old and new tech</title>
    <itunes:summary><![CDATA[Simon Sabin talks about how SQL Bits picks sessions when the data world keeps splintering into more tools. We talk about the tension between Fabric and the older stack people still use at work, and why session selection has to cover both. We also talk about why discernment is the skill you need with AI, since the model is an "automated idiot" and you have to catch when it's wrong. Power Query's declarative engine comes up too, along with the pub quizzes and board game nights SQL Bits runs so ...]]></itunes:summary>
    <description><![CDATA[<p>Simon Sabin talks about how SQL Bits picks sessions when the data world keeps splintering into more tools. We talk about the tension between Fabric and the older stack people still use at work, and why session selection has to cover both. We also talk about why discernment is the skill you need with AI, since the model is an &quot;automated idiot&quot; and you have to catch when it&apos;s wrong. Power Query&apos;s declarative engine comes up too, along with the pub quizzes and board game nights SQL Bits runs so introverts can actually meet people.</p><p><b>Resources</b></p><ul><li><a href='https://sqlbits.com/'>SQLBits</a></li><li><a href='https://feedly.com'>Feedly</a></li><li><a href='https://learn.microsoft.com/en-us/power-bi/developer/mcp/mcp-servers-overview'>Power BI MCP server</a></li><li><a href='https://bengribaudo.com/courses/mastering-m'>Ben Gribaudo&apos;s Power Query training</a></li><li><a href='https://fabriccon.com/'>FabCon Vienna</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>Simon Sabin talks about how SQL Bits picks sessions when the data world keeps splintering into more tools. We talk about the tension between Fabric and the older stack people still use at work, and why session selection has to cover both. We also talk about why discernment is the skill you need with AI, since the model is an &quot;automated idiot&quot; and you have to catch when it&apos;s wrong. Power Query&apos;s declarative engine comes up too, along with the pub quizzes and board game nights SQL Bits runs so introverts can actually meet people.</p><p><b>Resources</b></p><ul><li><a href='https://sqlbits.com/'>SQLBits</a></li><li><a href='https://feedly.com'>Feedly</a></li><li><a href='https://learn.microsoft.com/en-us/power-bi/developer/mcp/mcp-servers-overview'>Power BI MCP server</a></li><li><a href='https://bengribaudo.com/courses/mastering-m'>Ben Gribaudo&apos;s Power Query training</a></li><li><a href='https://fabriccon.com/'>FabCon Vienna</a></li></ul>]]></content:encoded>
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    <pubDate>Wed, 03 Jun 2026 17:00:00 -0400</pubDate>
    <itunes:duration>2000</itunes:duration>
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    <itunes:title>Ep. 25 - Python Notebooks</itunes:title>
    <title>Ep. 25 - Python Notebooks</title>
    <itunes:summary><![CDATA[Sandeep Pawar talks about Python notebooks in Microsoft Fabric and why Power BI developers should learn them. We talk about semantic link as the entry point for Power BI developers into Python, and how notebooks open up solutions for orchestration, monitoring, and administration that are hard to do any other way. We also talk about PySpark, and why understanding Spark internals matters just as much as writing the code. Links Semantic link (Microsoft Fabric Python library)Dunder Data (Python a...]]></itunes:summary>
    <description><![CDATA[<p>Sandeep Pawar talks about Python notebooks in Microsoft Fabric and why Power BI developers should learn them. We talk about semantic link as the entry point for Power BI developers into Python, and how notebooks open up solutions for orchestration, monitoring, and administration that are hard to do any other way. We also talk about PySpark, and why understanding Spark internals matters just as much as writing the code.</p><p><b>Links</b></p><ul><li><a href='https://learn.microsoft.com/en-us/fabric/data-science/semantic-link-overview'>Semantic link (Microsoft Fabric Python library)</a></li><li><a href='https://www.dunderdata.com/'>Dunder Data (Python and Pandas tutorials)</a></li><li><a href='https://www.oreilly.com/library/view/delta-lake-up/9781098139711/'>Delta Lake: Up and Running (O&apos;Reilly)</a></li><li><a href='https://fabric.guru/'>fabric.guru (Sandeep Pawar&apos;s blog)</a></li><li><a href='https://streamlit.io/'>Streamlit</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>Sandeep Pawar talks about Python notebooks in Microsoft Fabric and why Power BI developers should learn them. We talk about semantic link as the entry point for Power BI developers into Python, and how notebooks open up solutions for orchestration, monitoring, and administration that are hard to do any other way. We also talk about PySpark, and why understanding Spark internals matters just as much as writing the code.</p><p><b>Links</b></p><ul><li><a href='https://learn.microsoft.com/en-us/fabric/data-science/semantic-link-overview'>Semantic link (Microsoft Fabric Python library)</a></li><li><a href='https://www.dunderdata.com/'>Dunder Data (Python and Pandas tutorials)</a></li><li><a href='https://www.oreilly.com/library/view/delta-lake-up/9781098139711/'>Delta Lake: Up and Running (O&apos;Reilly)</a></li><li><a href='https://fabric.guru/'>fabric.guru (Sandeep Pawar&apos;s blog)</a></li><li><a href='https://streamlit.io/'>Streamlit</a></li></ul>]]></content:encoded>
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    <itunes:author>Eugene Meidinger</itunes:author>
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    <pubDate>Wed, 25 Mar 2026 10:00:00 -0400</pubDate>
    <itunes:duration>2058</itunes:duration>
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    <itunes:title>Ep. 24 Fabric Community</itunes:title>
    <title>Ep. 24 Fabric Community</title>
    <itunes:summary><![CDATA[In this episode, Shannon Lindsay from the Microsoft Community team joins me to talk about, well, community! We talk about her trajectory from non-profit space, to Power BI developer, to Microsoft employee. We go over how social media is fragmented and the joy of finding your friends. Dunbar's numberUnderstand translytical task flowsData WitchesMicrosoft Fabric Community]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Shannon Lindsay from the Microsoft Community team joins me to talk about, well, community! We talk about her trajectory from non-profit space, to Power BI developer, to Microsoft employee. We go over how social media is fragmented and the joy of finding your friends.</p><ul><li><a href='https://en.wikipedia.org/wiki/Dunbar%27s_number'>Dunbar&apos;s number</a></li><li><a href='https://learn.microsoft.com/en-us/power-bi/create-reports/translytical-task-flow-overview'>Understand translytical task flows</a></li><li><a href='https://data-witches.com/'>Data Witches</a></li><li><a href='https://community.fabric.microsoft.com/'>Microsoft Fabric Community</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Shannon Lindsay from the Microsoft Community team joins me to talk about, well, community! We talk about her trajectory from non-profit space, to Power BI developer, to Microsoft employee. We go over how social media is fragmented and the joy of finding your friends.</p><ul><li><a href='https://en.wikipedia.org/wiki/Dunbar%27s_number'>Dunbar&apos;s number</a></li><li><a href='https://learn.microsoft.com/en-us/power-bi/create-reports/translytical-task-flow-overview'>Understand translytical task flows</a></li><li><a href='https://data-witches.com/'>Data Witches</a></li><li><a href='https://community.fabric.microsoft.com/'>Microsoft Fabric Community</a></li></ul>]]></content:encoded>
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    <pubDate>Wed, 03 Dec 2025 10:00:00 -0500</pubDate>
    <itunes:duration>1914</itunes:duration>
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    <itunes:title>Ep. 23. Dealing with Fabric Overwhelm</itunes:title>
    <title>Ep. 23. Dealing with Fabric Overwhelm</title>
    <itunes:summary><![CDATA[In this episode, Shabnam Watson talks about dealing with Fabric overwhelm and how her bureaucratic experiences with Azure and Synapse motivated her to learn Fabric. She talks about how it's important to focus on finding a way that works with the tool instead of finding the "best" way. In general, the best lesson is to find ways to tie your new learning. We also touch on the DP-600/DP-700 certifications. Analytics Engineering with Microsoft Fabric and Power BI (O'Reilly, early release)The Anal...]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Shabnam Watson talks about dealing with Fabric overwhelm and how her bureaucratic experiences with Azure and Synapse motivated her to learn Fabric. She talks about how it&apos;s important to focus on finding a way that works with the tool instead of finding the &quot;best&quot; way. In general, the best lesson is to find ways to tie your new learning. We also touch on the DP-600/DP-700 certifications.</p><ul><li><a href='https://www.oreilly.com/library/view/analytics-engineering-with/9798341645868/'>Analytics Engineering with Microsoft Fabric and Power BI</a> (O&apos;Reilly, early release)</li><li><a href='https://roundup.getdbt.com/s/the-analytics-engineering-podcast'>The Analytics Engineering Podcast</a> (dbt Labs)</li><li><a href='https://www.amazon.com/Design-People-Learn-Voices-Matter/dp/0134211286'>Design for How People Learn by Julie Dirksen</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-factory/what-is-copy-job'>What is Copy Job in Data Factory</a></li><li><a href='https://learn.microsoft.com/en-us/credentials/certifications/deals'>Microsoft Exam Replay</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Shabnam Watson talks about dealing with Fabric overwhelm and how her bureaucratic experiences with Azure and Synapse motivated her to learn Fabric. She talks about how it&apos;s important to focus on finding a way that works with the tool instead of finding the &quot;best&quot; way. In general, the best lesson is to find ways to tie your new learning. We also touch on the DP-600/DP-700 certifications.</p><ul><li><a href='https://www.oreilly.com/library/view/analytics-engineering-with/9798341645868/'>Analytics Engineering with Microsoft Fabric and Power BI</a> (O&apos;Reilly, early release)</li><li><a href='https://roundup.getdbt.com/s/the-analytics-engineering-podcast'>The Analytics Engineering Podcast</a> (dbt Labs)</li><li><a href='https://www.amazon.com/Design-People-Learn-Voices-Matter/dp/0134211286'>Design for How People Learn by Julie Dirksen</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-factory/what-is-copy-job'>What is Copy Job in Data Factory</a></li><li><a href='https://learn.microsoft.com/en-us/credentials/certifications/deals'>Microsoft Exam Replay</a></li></ul>]]></content:encoded>
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    <pubDate>Mon, 01 Dec 2025 06:00:00 -0500</pubDate>
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    <itunes:title>Ep. 22 Making Fabric Feel Like Home</itunes:title>
    <title>Ep. 22 Making Fabric Feel Like Home</title>
    <itunes:summary><![CDATA[In this episode, Microsoft MVP Prathy K talks about her journey into Microsoft Fabric from her MSBI background. She explains how Fabric felt like "coming home" since she could map SSIS, SSRS, and SSAS concepts to new tools. We discuss how medallion architecture is really just rebranded data warehousing layers and why Fabric can feel overwhelming if you haven't kept up with the big data world. Microsoft documentation on medallion architectureWhat is a lakehouse? (Databricks, 2020)Big Data or P...]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Microsoft MVP Prathy K talks about her journey into Microsoft Fabric from her MSBI background. She explains how Fabric felt like &quot;coming home&quot; since she could map SSIS, SSRS, and SSAS concepts to new tools. We discuss how medallion architecture is really just rebranded data warehousing layers and why Fabric can feel overwhelming if you haven&apos;t kept up with the big data world.</p><ul><li><a href='https://learn.microsoft.com/en-us/fabric/onelake/onelake-medallion-lakehouse-architecture'>Microsoft documentation on medallion architecture</a></li><li><a href='https://www.databricks.com/blog/2020/01/30/what-is-a-data-lakehouse.html'>What is a lakehouse</a>? (Databricks, 2020)</li><li><a href='https://pixelastic.github.io/pokemonorbigdata/'>Big Data or Pokemon</a>? (circa 2013)</li><li><a href='https://learn.microsoft.com/en-us/fabric/enterprise/metrics-app-install?tabs=1st'>Fabric Capacity Metrics app</a></li><li><a href='https://www.sqlgene.com/2024/12/15/fabric-benchmarking-part-1-copying-csv-files-to-onelake/'>Fabric benchmarking loading CSV</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Microsoft MVP Prathy K talks about her journey into Microsoft Fabric from her MSBI background. She explains how Fabric felt like &quot;coming home&quot; since she could map SSIS, SSRS, and SSAS concepts to new tools. We discuss how medallion architecture is really just rebranded data warehousing layers and why Fabric can feel overwhelming if you haven&apos;t kept up with the big data world.</p><ul><li><a href='https://learn.microsoft.com/en-us/fabric/onelake/onelake-medallion-lakehouse-architecture'>Microsoft documentation on medallion architecture</a></li><li><a href='https://www.databricks.com/blog/2020/01/30/what-is-a-data-lakehouse.html'>What is a lakehouse</a>? (Databricks, 2020)</li><li><a href='https://pixelastic.github.io/pokemonorbigdata/'>Big Data or Pokemon</a>? (circa 2013)</li><li><a href='https://learn.microsoft.com/en-us/fabric/enterprise/metrics-app-install?tabs=1st'>Fabric Capacity Metrics app</a></li><li><a href='https://www.sqlgene.com/2024/12/15/fabric-benchmarking-part-1-copying-csv-files-to-onelake/'>Fabric benchmarking loading CSV</a></li></ul>]]></content:encoded>
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    <itunes:author>Eugene Meidinger</itunes:author>
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    <pubDate>Wed, 05 Nov 2025 10:00:00 -0500</pubDate>
    <itunes:duration>1817</itunes:duration>
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    <itunes:season>1</itunes:season>
    <itunes:episode>22</itunes:episode>
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  <item>
    <itunes:title>Ep. 21 - Reverse interview, should you switch to Microsoft Fabric?</itunes:title>
    <title>Ep. 21 - Reverse interview, should you switch to Microsoft Fabric?</title>
    <itunes:summary><![CDATA[In this episode, Microsoft MVP Angela Henry asks me questions about Microsoft Fabric. We compare the current Fabric development timeline to the old Power BI development timeline. I talk about when Fabric makes the most sense, in my personal opinion. It was a surprise this episode to hear about SSRS. https://en.wikipedia.org/wiki/Horseshoe_crabSVG images in Power BI (2018)Fabric Roadmap]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Microsoft MVP Angela Henry asks me questions about Microsoft Fabric. We compare the current Fabric development timeline to the old Power BI development timeline. I talk about when Fabric makes the most sense, in my personal opinion. It was a surprise this episode to hear about SSRS.</p><ul><li>https://en.wikipedia.org/wiki/Horseshoe_crab</li><li><a href='https://dataveld.com/2018/07/16/use-svg-images-in-power-bi-part-3/'>SVG images in Power BI</a> (2018)</li><li><a href='https://blog.fabric.microsoft.com/en-us/blog/announcing-the-fabric-roadmap?ft=All'>Fabric Roadmap</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Microsoft MVP Angela Henry asks me questions about Microsoft Fabric. We compare the current Fabric development timeline to the old Power BI development timeline. I talk about when Fabric makes the most sense, in my personal opinion. It was a surprise this episode to hear about SSRS.</p><ul><li>https://en.wikipedia.org/wiki/Horseshoe_crab</li><li><a href='https://dataveld.com/2018/07/16/use-svg-images-in-power-bi-part-3/'>SVG images in Power BI</a> (2018)</li><li><a href='https://blog.fabric.microsoft.com/en-us/blog/announcing-the-fabric-roadmap?ft=All'>Fabric Roadmap</a></li></ul>]]></content:encoded>
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    <itunes:image href="https://storage.buzzsprout.com/p94pddzqp4u36r1eh5g9kjtq9zt9?.jpg" />
    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-17781559</guid>
    <pubDate>Wed, 03 Sep 2025 10:00:00 -0400</pubDate>
    <itunes:duration>1833</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 20 - Power BI Accessibility</itunes:title>
    <title>Ep. 20 - Power BI Accessibility</title>
    <itunes:summary><![CDATA[In this episode, Juliana Smith talks about accessibility in Power BI. She talks about starting out as a data scientist and moving to Power BI. We talk about how impairments can be temporary or varied and how accessibility helps everyone. We discuss simple, low-effort changes like font sizes, labels, and color contrast. Megean Longoria on accessibilityInclusive Design ToolkitAccessibility Insights for WindowsAccessibility documentation for Microsof Power BIJuliana’s YouTubeJuliana’s Blog]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Juliana Smith talks about accessibility in Power BI. She talks about starting out as a data scientist and moving to Power BI. We talk about how impairments can be temporary or varied and how accessibility helps everyone. We discuss simple, low-effort changes like font sizes, labels, and color contrast.</p><ul><li><a href='https://datasavvy.me/category/accessibility/'>Megean Longoria on accessibility</a></li><li><a href='https://inclusive.microsoft.design/'>Inclusive Design Toolkit</a></li><li><a href='https://accessibilityinsights.io/docs/windows/overview/'>Accessibility Insights for Windows</a></li><li><a href='https://learn.microsoft.com/en-us/power-bi/create-reports/desktop-accessibility-creating-reports'>Accessibility documentation for Microsof Power BI</a></li><li><a href='https://www.youtube.com/@AccessibleBI'>Juliana’s YouTube</a></li><li><a href='https://smart-frames.co.uk/'>Juliana’s Blog</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Juliana Smith talks about accessibility in Power BI. She talks about starting out as a data scientist and moving to Power BI. We talk about how impairments can be temporary or varied and how accessibility helps everyone. We discuss simple, low-effort changes like font sizes, labels, and color contrast.</p><ul><li><a href='https://datasavvy.me/category/accessibility/'>Megean Longoria on accessibility</a></li><li><a href='https://inclusive.microsoft.design/'>Inclusive Design Toolkit</a></li><li><a href='https://accessibilityinsights.io/docs/windows/overview/'>Accessibility Insights for Windows</a></li><li><a href='https://learn.microsoft.com/en-us/power-bi/create-reports/desktop-accessibility-creating-reports'>Accessibility documentation for Microsof Power BI</a></li><li><a href='https://www.youtube.com/@AccessibleBI'>Juliana’s YouTube</a></li><li><a href='https://smart-frames.co.uk/'>Juliana’s Blog</a></li></ul>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2432490/episodes/17703844-ep-20-power-bi-accessibility.mp3" length="19583087" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/jpgvcgu0sb8kxgdmiakua7uem8n4?.jpg" />
    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-17703844</guid>
    <pubDate>Wed, 20 Aug 2025 10:00:00 -0400</pubDate>
    <itunes:duration>1629</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>20</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 19 - Getting into Microsoft Fabric</itunes:title>
    <title>Ep. 19 - Getting into Microsoft Fabric</title>
    <itunes:summary><![CDATA[In this episode, Heidi Hastings joins to discuss the practical realities of adopting Microsoft Fabric. We cover her early exposure to Fabric through the MVP preview, the challenges of understanding and implementing it across real-world projects, and the often-overlooked learning curve for newcomers.  Heidi shares insights into common misconceptions driven by marketing materials, gaps in documentation, and the difficulty of navigating architectural decisions like Lakehouse vs. Warehouse.&...]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Heidi Hastings joins to discuss the practical realities of adopting Microsoft Fabric. We cover her early exposure to Fabric through the MVP preview, the challenges of understanding and implementing it across real-world projects, and the often-overlooked learning curve for newcomers. </p><p>Heidi shares insights into common misconceptions driven by marketing materials, gaps in documentation, and the difficulty of navigating architectural decisions like Lakehouse vs. Warehouse. </p><p><b>Links</b></p><ul><li><a href='https://www.youtube.com/watch?v=lklfynbTlc8'>You could have invented Microsoft Fabric</a></li><li><a href='https://www.youtube.com/@GuyInACube'>Guy in a Cube</a></li><li><a href='https://www.linkedin.com/in/ruiromano/'>Rui Romano</a></li><li><a href='https://workout-wednesday.com/category/powerbi/'>Workout Wednesday</a></li><li><a href='https://kerrykolosko.com/'>Kerry Kolosko</a></li><li><a href='https://datasavvy.me/'>Megean Longoria</a></li><li><a href='https://data-witches.com/'>Data witches</a></li><li><a href='https://www.youtube.com/playlist?list=PLzUAjXZBFU9O2FimP0AUqHliCsKFsOLLv'>Synapse Espresso</a></li><li><a href='https://www.sqlbi.com/tools/contoso-data-generator/'>Contoso generated dataset</a></li><li><a href='https://en.wikipedia.org/wiki/Time_in_Australia'>Australia timezones</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Heidi Hastings joins to discuss the practical realities of adopting Microsoft Fabric. We cover her early exposure to Fabric through the MVP preview, the challenges of understanding and implementing it across real-world projects, and the often-overlooked learning curve for newcomers. </p><p>Heidi shares insights into common misconceptions driven by marketing materials, gaps in documentation, and the difficulty of navigating architectural decisions like Lakehouse vs. Warehouse. </p><p><b>Links</b></p><ul><li><a href='https://www.youtube.com/watch?v=lklfynbTlc8'>You could have invented Microsoft Fabric</a></li><li><a href='https://www.youtube.com/@GuyInACube'>Guy in a Cube</a></li><li><a href='https://www.linkedin.com/in/ruiromano/'>Rui Romano</a></li><li><a href='https://workout-wednesday.com/category/powerbi/'>Workout Wednesday</a></li><li><a href='https://kerrykolosko.com/'>Kerry Kolosko</a></li><li><a href='https://datasavvy.me/'>Megean Longoria</a></li><li><a href='https://data-witches.com/'>Data witches</a></li><li><a href='https://www.youtube.com/playlist?list=PLzUAjXZBFU9O2FimP0AUqHliCsKFsOLLv'>Synapse Espresso</a></li><li><a href='https://www.sqlbi.com/tools/contoso-data-generator/'>Contoso generated dataset</a></li><li><a href='https://en.wikipedia.org/wiki/Time_in_Australia'>Australia timezones</a></li></ul>]]></content:encoded>
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    <itunes:image href="https://storage.buzzsprout.com/yol86y4amaqjxrhq25r50cklpuep?.jpg" />
    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-17624296</guid>
    <pubDate>Wed, 06 Aug 2025 09:00:00 -0400</pubDate>
    <itunes:duration>2141</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>19</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 18 - SQL DB on Fabric</itunes:title>
    <title>Ep. 18 - SQL DB on Fabric</title>
    <itunes:summary><![CDATA[In this episode, Sukhwant Kaur the PM for SQL DBs in Fabric, talks about the new feature. She talks about how management is much easier, which is great for experimentation. SQL DBs are very popular for metadata pipelines and similar. It’s exciting as a way to enable writeback and curated data storage for Power BI. We also talked about AI features and workload management. Links Vector support for in Azure GASurge protection in Fabric]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Sukhwant Kaur the PM for SQL DBs in Fabric, talks about the new feature. She talks about how management is much easier, which is great for experimentation. SQL DBs are very popular for metadata pipelines and similar. It’s exciting as a way to enable writeback and curated data storage for Power BI. We also talked about AI features and workload management.</p><p><b>Links</b></p><ul><li><a href='https://devblogs.microsoft.com/azure-sql/announcing-general-availability-of-native-vector-type-functions-in-azure-sql/'>Vector support for in Azure GA</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/enterprise/surge-protection'>Surge protection in Fabric</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Sukhwant Kaur the PM for SQL DBs in Fabric, talks about the new feature. She talks about how management is much easier, which is great for experimentation. SQL DBs are very popular for metadata pipelines and similar. It’s exciting as a way to enable writeback and curated data storage for Power BI. We also talked about AI features and workload management.</p><p><b>Links</b></p><ul><li><a href='https://devblogs.microsoft.com/azure-sql/announcing-general-availability-of-native-vector-type-functions-in-azure-sql/'>Vector support for in Azure GA</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/enterprise/surge-protection'>Surge protection in Fabric</a></li></ul>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2432490/episodes/17587644-ep-18-sql-db-on-fabric.mp3" length="15616471" type="audio/mpeg" />
    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-17587644</guid>
    <pubDate>Wed, 30 Jul 2025 10:00:00 -0400</pubDate>
    <itunes:duration>1948</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 17 - Fabric Notebooks</itunes:title>
    <title>Ep. 17 - Fabric Notebooks</title>
    <itunes:summary><![CDATA[In this episode, we talk with Emilie Rønning about notebooks. We talk about how notebooks can be used for data engineering and when to get started with them. One of the nice things about notebooks is that you can easily debug individual steps instead of having to search a whole script for an error. We also discuss when to learn notebooks. Near the end we talk about how exporting notebooks risks exfiltrating data. Links ROC in statisticsREPL LoopLiterate programmingU-SQL languageFabric Februar...]]></itunes:summary>
    <description><![CDATA[<p>In this episode, we talk with Emilie Rønning about notebooks. We talk about how notebooks can be used for data engineering and when to get started with them. One of the nice things about notebooks is that you can easily debug individual steps instead of having to search a whole script for an error. We also discuss when to learn notebooks. Near the end we talk about how exporting notebooks risks exfiltrating data.</p><p><b>Links</b></p><ul><li><a href='https://en.wikipedia.org/wiki/Receiver_operating_characteristic'>ROC in statistics</a></li><li><a href='https://en.wikipedia.org/wiki/Read%E2%80%93eval%E2%80%93print_loop'>REPL Loop</a></li><li><a href='https://en.wikipedia.org/wiki/Literate_programming'>Literate programming</a></li><li><a href='https://devblogs.microsoft.com/visualstudio/introducing-u-sql-a-language-that-makes-big-data-processing-easy/'>U-SQL language</a></li><li><a href='https://www.fabricfebruary.com/'>Fabric February</a></li><li><a href='https://github.com/Lucid-Will/Fabric-Capacity-Monitoring/blob/main/README.md'>Lucid Will capacity tracking</a></li><li><a href='https://www.kevinrchant.com/2025/02/17/happy-together-paths-to-test-semantic-models-in-microsoft-fabric-feature-workspaces-with-bpa/'>Semantic link BPA</a></li><li><a href='https://www.youtube.com/watch?v=_uJWPjFM7BU'>Best Practices aren&apos;t always helpful</a></li><li><a href='https://data-marc.com/2025/04/09/the-hidden-risk-in-fabric-notebook-exports-your-data-travels-too/'>The hidden risk in Fabric notebook exports</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, we talk with Emilie Rønning about notebooks. We talk about how notebooks can be used for data engineering and when to get started with them. One of the nice things about notebooks is that you can easily debug individual steps instead of having to search a whole script for an error. We also discuss when to learn notebooks. Near the end we talk about how exporting notebooks risks exfiltrating data.</p><p><b>Links</b></p><ul><li><a href='https://en.wikipedia.org/wiki/Receiver_operating_characteristic'>ROC in statistics</a></li><li><a href='https://en.wikipedia.org/wiki/Read%E2%80%93eval%E2%80%93print_loop'>REPL Loop</a></li><li><a href='https://en.wikipedia.org/wiki/Literate_programming'>Literate programming</a></li><li><a href='https://devblogs.microsoft.com/visualstudio/introducing-u-sql-a-language-that-makes-big-data-processing-easy/'>U-SQL language</a></li><li><a href='https://www.fabricfebruary.com/'>Fabric February</a></li><li><a href='https://github.com/Lucid-Will/Fabric-Capacity-Monitoring/blob/main/README.md'>Lucid Will capacity tracking</a></li><li><a href='https://www.kevinrchant.com/2025/02/17/happy-together-paths-to-test-semantic-models-in-microsoft-fabric-feature-workspaces-with-bpa/'>Semantic link BPA</a></li><li><a href='https://www.youtube.com/watch?v=_uJWPjFM7BU'>Best Practices aren&apos;t always helpful</a></li><li><a href='https://data-marc.com/2025/04/09/the-hidden-risk-in-fabric-notebook-exports-your-data-travels-too/'>The hidden risk in Fabric notebook exports</a></li></ul>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2432490/episodes/17551305-ep-17-fabric-notebooks.mp3" length="21196767" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/fhxsa2tk9y1l34d29dexla5a2oz3?.jpg" />
    <itunes:author>Eugene Meidinger</itunes:author>
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    <pubDate>Wed, 23 Jul 2025 10:00:00 -0400</pubDate>
    <itunes:duration>1763</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>17</itunes:episode>
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    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 16 - Administering Fabric</itunes:title>
    <title>Ep. 16 - Administering Fabric</title>
    <itunes:summary><![CDATA[In this episode, Elayne Jones talks about being an expert reference for the IT Center of Excellence and about administering Fabric. We talk about the types of things that can be administered and some of the challenges. Deploy Power BI from OneDriveMatthew Roche: problem domain and solution domainPublish to web turned off by default now1,000 item limit in Fabric workspaces]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Elayne Jones talks about being an expert reference for the IT Center of Excellence and about administering Fabric. We talk about the types of things that can be administered and some of the challenges.</p><ul><li><a href='https://learn.microsoft.com/en-us/power-bi/create-reports/desktop-sharepoint-save-share#background-upload-for-existing-power-bi-files-in-onedrive-and-sharepoint-preview'>Deploy Power BI from OneDrive</a></li><li><a href='https://ssbipolar.com/2021/12/31/between-the-problem-domain-and-the-solution/'>Matthew Roche: problem domain and solution domain</a></li><li><a href='https://databear.com/power-bi-publish-to-web-security-update/'>Publish to web turned off by default now</a></li><li><a href='https://blog.fabric.microsoft.com/en-us/blog/introduction-of-item-limits-in-a-fabric-workspace/'>1,000 item limit in Fabric workspaces</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Elayne Jones talks about being an expert reference for the IT Center of Excellence and about administering Fabric. We talk about the types of things that can be administered and some of the challenges.</p><ul><li><a href='https://learn.microsoft.com/en-us/power-bi/create-reports/desktop-sharepoint-save-share#background-upload-for-existing-power-bi-files-in-onedrive-and-sharepoint-preview'>Deploy Power BI from OneDrive</a></li><li><a href='https://ssbipolar.com/2021/12/31/between-the-problem-domain-and-the-solution/'>Matthew Roche: problem domain and solution domain</a></li><li><a href='https://databear.com/power-bi-publish-to-web-security-update/'>Publish to web turned off by default now</a></li><li><a href='https://blog.fabric.microsoft.com/en-us/blog/introduction-of-item-limits-in-a-fabric-workspace/'>1,000 item limit in Fabric workspaces</a></li></ul>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2432490/episodes/17514804-ep-16-administering-fabric.mp3" length="12430462" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/qdf0vt5v3aqq201m6hfy1spod22u?.jpg" />
    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-17514804</guid>
    <pubDate>Wed, 16 Jul 2025 10:00:00 -0400</pubDate>
    <itunes:duration>1549</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>16</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 15 - Fabric or Databricks</itunes:title>
    <title>Ep. 15 - Fabric or Databricks</title>
    <itunes:summary><![CDATA[In this episode, Meagan Longoria talks about Databricks and helps us compare it to Fabric. The general conclusions is Databricks is still the mature tool, but Fabric is making improvements.  In reality, there is space for a hybrid approach and if you have to start somewhere with Fabric, it likely makes sense to start with Power BI and work your way back, where this value. We also talk about how the way Fabric is structured can sometimes lead to messy workspaces. Links Items limitations i...]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Meagan Longoria talks about Databricks and helps us compare it to Fabric. The general conclusions is Databricks is still the mature tool, but Fabric is making improvements. </p><p>In reality, there is space for a hybrid approach and if you have to start somewhere with Fabric, it likely makes sense to start with Power BI and work your way back, where this value. We also talk about how the way Fabric is structured can sometimes lead to messy workspaces.</p><p><b>Links</b></p><ul><li><a href='https://blog.fabric.microsoft.com/en-us/blog/introduction-of-item-limits-in-a-fabric-workspace/'>Items limitations in workspaces</a></li><li><a href='https://en.wikipedia.org/wiki/Conway%27s_law'>Conway&apos;s law (you ship your org chart)</a></li><li><a href='https://www.sqlgene.com/2025/01/26/microsoft-fabric-guidance-for-small-businesses/'>Fabric Guidance for Small Businesses (from Eugene)</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/database/mirrored-database/azure-databricks'>Fabric mirroring for Azure Databricks</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-factory/semantic-model-refresh-activity'>Semantic model refresh activity</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Meagan Longoria talks about Databricks and helps us compare it to Fabric. The general conclusions is Databricks is still the mature tool, but Fabric is making improvements. </p><p>In reality, there is space for a hybrid approach and if you have to start somewhere with Fabric, it likely makes sense to start with Power BI and work your way back, where this value. We also talk about how the way Fabric is structured can sometimes lead to messy workspaces.</p><p><b>Links</b></p><ul><li><a href='https://blog.fabric.microsoft.com/en-us/blog/introduction-of-item-limits-in-a-fabric-workspace/'>Items limitations in workspaces</a></li><li><a href='https://en.wikipedia.org/wiki/Conway%27s_law'>Conway&apos;s law (you ship your org chart)</a></li><li><a href='https://www.sqlgene.com/2025/01/26/microsoft-fabric-guidance-for-small-businesses/'>Fabric Guidance for Small Businesses (from Eugene)</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/database/mirrored-database/azure-databricks'>Fabric mirroring for Azure Databricks</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-factory/semantic-model-refresh-activity'>Semantic model refresh activity</a></li></ul>]]></content:encoded>
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    <itunes:image href="https://storage.buzzsprout.com/rpjpd7144dffk4jgysomg5t3j9p8?.jpg" />
    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-17476921</guid>
    <pubDate>Wed, 09 Jul 2025 09:00:00 -0400</pubDate>
    <itunes:duration>2112</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>15</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 14 Changing Data Culture</itunes:title>
    <title>Ep. 14 Changing Data Culture</title>
    <itunes:summary><![CDATA[In this episode, Ewa Hutmacher talks about driving change and changing cultures in a organization. I think it’s fair to say that adjusting to Fabric and centralizing your data is a big organizational change. It was new to me to hear there are ways to track and monitor organizational change. Crucial ConversationsMedallion architectureRussian nail factoryPerverse incentivesWho Moved My Cheese?“We need this report in Power BI”]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Ewa Hutmacher talks about driving change and changing cultures in a organization. I think it’s fair to say that adjusting to Fabric and centralizing your data is a big organizational change. It was new to me to hear there are ways to track and monitor organizational change.</p><ul><li><a href='https://www.amazon.com/Crucial-Conversations-Third-Talking-Stakes/dp/B09MV3818X/'>Crucial Conversations</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/onelake/onelake-medallion-lakehouse-architecture'>Medallion architecture</a></li><li><a href='https://skeptics.stackexchange.com/questions/22375/did-a-soviet-nail-factory-produce-useless-nails-to-improve-metrics'>Russian nail factory</a></li><li><a href='https://en.wikipedia.org/wiki/Perverse_incentive'>Perverse incentives</a></li><li><a href='https://en.wikipedia.org/wiki/Who_Moved_My_Cheese%3F'>Who Moved My Cheese?</a></li><li><a href='https://data-goblins.com/power-bi/report-requirements'>“We need this report in Power BI”</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Ewa Hutmacher talks about driving change and changing cultures in a organization. I think it’s fair to say that adjusting to Fabric and centralizing your data is a big organizational change. It was new to me to hear there are ways to track and monitor organizational change.</p><ul><li><a href='https://www.amazon.com/Crucial-Conversations-Third-Talking-Stakes/dp/B09MV3818X/'>Crucial Conversations</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/onelake/onelake-medallion-lakehouse-architecture'>Medallion architecture</a></li><li><a href='https://skeptics.stackexchange.com/questions/22375/did-a-soviet-nail-factory-produce-useless-nails-to-improve-metrics'>Russian nail factory</a></li><li><a href='https://en.wikipedia.org/wiki/Perverse_incentive'>Perverse incentives</a></li><li><a href='https://en.wikipedia.org/wiki/Who_Moved_My_Cheese%3F'>Who Moved My Cheese?</a></li><li><a href='https://data-goblins.com/power-bi/report-requirements'>“We need this report in Power BI”</a></li></ul>]]></content:encoded>
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    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-17369143</guid>
    <pubDate>Wed, 02 Jul 2025 10:00:00 -0400</pubDate>
    <itunes:duration>2413</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>14</itunes:episode>
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    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep 13. Power BI, Your First Job, and the PL-300</itunes:title>
    <title>Ep 13. Power BI, Your First Job, and the PL-300</title>
    <itunes:summary><![CDATA[In this episode, Evelyn talks about getting certified in the Tableau and Power BI. We talk a little a bit about how each is different. For her, BI was an ideal career because it was in the middle of her two passions: art and IT. We also discuss getting her first job and studying for the PL-300. Ggplot2Kind and Wicked learning environments (regarding delayed feedback)Column profiler]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Evelyn talks about getting certified in the Tableau and Power BI. We talk a little a bit about how each is different. For her, BI was an ideal career because it was in the middle of her two passions: art and IT. We also discuss getting her first job and studying for the PL-300.</p><ul><li><a href='https://ggplot2.tidyverse.org/'>Ggplot2</a></li><li><a href='https://www.driverlesscrocodile.com/books-and-recommendations/david-epstein-on-kind-and-wicked-learning-environments/'>Kind and Wicked learning environments</a> (regarding delayed feedback)</li><li><a href='https://learn.microsoft.com/en-us/power-query/data-profiling-tools'>Column profiler</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Evelyn talks about getting certified in the Tableau and Power BI. We talk a little a bit about how each is different. For her, BI was an ideal career because it was in the middle of her two passions: art and IT. We also discuss getting her first job and studying for the PL-300.</p><ul><li><a href='https://ggplot2.tidyverse.org/'>Ggplot2</a></li><li><a href='https://www.driverlesscrocodile.com/books-and-recommendations/david-epstein-on-kind-and-wicked-learning-environments/'>Kind and Wicked learning environments</a> (regarding delayed feedback)</li><li><a href='https://learn.microsoft.com/en-us/power-query/data-profiling-tools'>Column profiler</a></li></ul>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2432490/episodes/17023651-ep-13-power-bi-your-first-job-and-the-pl-300.mp3" length="23182057" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/ms4wr724kdrd9d39um7z0nwizdn3?.jpg" />
    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-17023651</guid>
    <pubDate>Wed, 25 Jun 2025 10:00:00 -0400</pubDate>
    <itunes:duration>1929</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>13</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 12 - Power BI, Data Viz, and Solving the Right Problem</itunes:title>
    <title>Ep. 12 - Power BI, Data Viz, and Solving the Right Problem</title>
    <itunes:summary><![CDATA[T. from Data Rocks talks about how data viz is a tiny subset of information design. The key is to focus less on just charts, but more about how the data is communicated and received. We talk about how what the user does with it separates a pile of charts from a successful design flow. I found this conversation helpful to understand it means to be good at data viz. Links Stop SolutioneeringFinancial Intelligence for IT PeopleSolving the Right Problems by Kurt BuhlerDon't Make Me ThinkThe Pepsi...]]></itunes:summary>
    <description><![CDATA[<p>T. from Data Rocks talks about how data viz is a tiny subset of information design. The key is to focus less on just charts, but more about how the data is communicated and received. We talk about how what the user does with it separates a pile of charts from a successful design flow. I found this conversation helpful to understand it means to be good at data viz.</p><p><b>Links</b></p><ul><li><a href='https://www.nngroup.com/videos/stop-solutioneering/'>Stop Solutioneering</a></li><li><a href='https://www.amazon.com/Financial-Intelligence-Professionals-Really-Numbers/dp/1422119149'>Financial Intelligence for IT People</a></li><li><a href='https://data-goblins.com/power-bi/solving-problems'>Solving the Right Problems by Kurt Buhler</a></li><li><a href='https://www.amazon.com/Dont-Make-Think-Revisited-Usability/dp/0321965515'>Don&apos;t Make Me Think</a></li><li><a href='https://slate.com/business/2013/08/pepsi-paradox-why-people-prefer-coke-even-though-pepsi-wins-in-taste-tests.html'>The Pepsi Paradox</a></li><li><a href='https://www.datarocks.co.nz/'>www.datarocks.co.nz</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>T. from Data Rocks talks about how data viz is a tiny subset of information design. The key is to focus less on just charts, but more about how the data is communicated and received. We talk about how what the user does with it separates a pile of charts from a successful design flow. I found this conversation helpful to understand it means to be good at data viz.</p><p><b>Links</b></p><ul><li><a href='https://www.nngroup.com/videos/stop-solutioneering/'>Stop Solutioneering</a></li><li><a href='https://www.amazon.com/Financial-Intelligence-Professionals-Really-Numbers/dp/1422119149'>Financial Intelligence for IT People</a></li><li><a href='https://data-goblins.com/power-bi/solving-problems'>Solving the Right Problems by Kurt Buhler</a></li><li><a href='https://www.amazon.com/Dont-Make-Think-Revisited-Usability/dp/0321965515'>Don&apos;t Make Me Think</a></li><li><a href='https://slate.com/business/2013/08/pepsi-paradox-why-people-prefer-coke-even-though-pepsi-wins-in-taste-tests.html'>The Pepsi Paradox</a></li><li><a href='https://www.datarocks.co.nz/'>www.datarocks.co.nz</a></li></ul>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2432490/episodes/16979780-ep-12-power-bi-data-viz-and-solving-the-right-problem.mp3" length="21838244" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/kw2cdhl1jk6xc7mb9zeeztz7j5it?.jpg" />
    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-16979780</guid>
    <pubDate>Mon, 14 Apr 2025 22:00:00 -0400</pubDate>
    <itunes:duration>1817</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>12</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 11 - Data Science, Career Paths, Learning Fabric</itunes:title>
    <title>Ep. 11 - Data Science, Career Paths, Learning Fabric</title>
    <itunes:summary><![CDATA[In this episode, Steph Locke covers a wild career from data science consultant to startup owner to Microsoft manager. We talk about what’s required to work in data science. We also talk about the interaction of large language models and coding. Finally, we talk about adjusting to Power BI and Fabric. Links Statistical t-testStatistical r-correlationBase rate fallacyROC (statistical test)Roc (mythical bird)Why your AI abstract was rejectedAgainst Power BI dogma  ]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Steph Locke covers a wild career from data science consultant to startup owner to Microsoft manager. We talk about what’s required to work in data science. We also talk about the interaction of large language models and coding. Finally, we talk about adjusting to Power BI and Fabric.</p><p><b>Links</b></p><ul><li><a href='https://en.wikipedia.org/wiki/Student%27s_t-test'>Statistical t-test</a></li><li><a href='https://en.wikipedia.org/wiki/Pearson_correlation_coefficient'>Statistical r-correlation</a></li><li><a href='https://en.wikipedia.org/wiki/Base_rate_fallacy'>Base rate fallacy</a></li><li><a href='https://en.wikipedia.org/wiki/Receiver_operating_characteristic'>ROC (statistical test)</a></li><li><a href='https://en.wikipedia.org/wiki/Roc_(mythology)'>Roc (mythical bird)</a></li><li><a href='https://www.youtube.com/watch?v=XhKcelV7DBo'>Why your AI abstract was rejected</a></li><li><a href='https://www.sqlgene.com/2025/01/11/how-power-bi-dogma-leads-to-a-lack-of-understanding/'>Against Power BI dogma</a></li></ul><p><br/></p>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Steph Locke covers a wild career from data science consultant to startup owner to Microsoft manager. We talk about what’s required to work in data science. We also talk about the interaction of large language models and coding. Finally, we talk about adjusting to Power BI and Fabric.</p><p><b>Links</b></p><ul><li><a href='https://en.wikipedia.org/wiki/Student%27s_t-test'>Statistical t-test</a></li><li><a href='https://en.wikipedia.org/wiki/Pearson_correlation_coefficient'>Statistical r-correlation</a></li><li><a href='https://en.wikipedia.org/wiki/Base_rate_fallacy'>Base rate fallacy</a></li><li><a href='https://en.wikipedia.org/wiki/Receiver_operating_characteristic'>ROC (statistical test)</a></li><li><a href='https://en.wikipedia.org/wiki/Roc_(mythology)'>Roc (mythical bird)</a></li><li><a href='https://www.youtube.com/watch?v=XhKcelV7DBo'>Why your AI abstract was rejected</a></li><li><a href='https://www.sqlgene.com/2025/01/11/how-power-bi-dogma-leads-to-a-lack-of-understanding/'>Against Power BI dogma</a></li></ul><p><br/></p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2432490/episodes/16934401-ep-11-data-science-career-paths-learning-fabric.mp3" length="27879306" type="audio/mpeg" />
    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-16934401</guid>
    <pubDate>Mon, 07 Apr 2025 18:00:00 -0400</pubDate>
    <itunes:duration>2319</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 10: Fabric and Instructional Design</itunes:title>
    <title>Ep. 10: Fabric and Instructional Design</title>
    <itunes:summary><![CDATA[In this episode with Ellen Burns-Johnson, we talk about when we worked on a cloud game for Azure Synapse, ADF, Power BI. A big lesson learned from that is a big challenge today for Fabric is getting different teams and personas to communicate with each other; it's not just about the technology. Ellen's first impression is "it seems like Microsoft is trying to 'product away' the communication layer".  Links Scott Hanselman and AbstractionsHenry Forde never said anything about faster horse...]]></itunes:summary>
    <description><![CDATA[<p>In this episode with Ellen Burns-Johnson, we talk about when we worked on a cloud game for Azure Synapse, ADF, Power BI. A big lesson learned from that is a big challenge today for Fabric is getting different teams and personas to communicate with each other; it&apos;s not just about the technology. Ellen&apos;s first impression is &quot;it seems like Microsoft is trying to &apos;product away&apos; the communication layer&quot;. </p><p><b>Links</b></p><ul><li><a href='https://www.hanselman.com/blog/please-learn-to-think-about-abstractions'>Scott Hanselman and Abstractions</a></li><li><a href='https://hbr.org/2011/08/henry-ford-never-said-the-fast'>Henry Forde never said anything about faster horses</a></li><li><a href='https://motherduck.com/blog/big-data-is-dead/'>Big data is dead</a></li><li><a href='https://www.reddit.com/r/PowerBI/comments/1i1bhut/power_bi_january_2025_feature_summary/'>January 2025 update on Reddit</a></li><li><a href='https://www.msn.com/en-us/news/world/mayor-mocked-for-using-deeply-disturbing-ai-images-of-dead-bodies-to-promote-plans-for-new-public-parks/ar-AA1r3u8j'>Mayor uses deeply disturbing AI image</a></li><li><a href='https://www.sqlgene.com/2025/01/01/the-fraught-ethics-around-ai-chatgpt-and-power-bi/'>Power BI, AI, and Ethics</a></li><li><a href='https://techcrunch.com/2024/12/27/why-deepseeks-new-ai-model-thinks-its-chatgpt/'>Deepseek thinks it is ChatGPT</a></li><li><a href='https://www.driverlesscrocodile.com/books-and-recommendations/david-epstein-on-kind-and-wicked-learning-environments/'>Kind and wicked learning environments</a></li><li><a href='https://en.wikipedia.org/wiki/Body_doubling'>Body Doubling</a></li><li><a href='https://en.wikipedia.org/wiki/Parallel_play'>Parallel Play</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode with Ellen Burns-Johnson, we talk about when we worked on a cloud game for Azure Synapse, ADF, Power BI. A big lesson learned from that is a big challenge today for Fabric is getting different teams and personas to communicate with each other; it&apos;s not just about the technology. Ellen&apos;s first impression is &quot;it seems like Microsoft is trying to &apos;product away&apos; the communication layer&quot;. </p><p><b>Links</b></p><ul><li><a href='https://www.hanselman.com/blog/please-learn-to-think-about-abstractions'>Scott Hanselman and Abstractions</a></li><li><a href='https://hbr.org/2011/08/henry-ford-never-said-the-fast'>Henry Forde never said anything about faster horses</a></li><li><a href='https://motherduck.com/blog/big-data-is-dead/'>Big data is dead</a></li><li><a href='https://www.reddit.com/r/PowerBI/comments/1i1bhut/power_bi_january_2025_feature_summary/'>January 2025 update on Reddit</a></li><li><a href='https://www.msn.com/en-us/news/world/mayor-mocked-for-using-deeply-disturbing-ai-images-of-dead-bodies-to-promote-plans-for-new-public-parks/ar-AA1r3u8j'>Mayor uses deeply disturbing AI image</a></li><li><a href='https://www.sqlgene.com/2025/01/01/the-fraught-ethics-around-ai-chatgpt-and-power-bi/'>Power BI, AI, and Ethics</a></li><li><a href='https://techcrunch.com/2024/12/27/why-deepseeks-new-ai-model-thinks-its-chatgpt/'>Deepseek thinks it is ChatGPT</a></li><li><a href='https://www.driverlesscrocodile.com/books-and-recommendations/david-epstein-on-kind-and-wicked-learning-environments/'>Kind and wicked learning environments</a></li><li><a href='https://en.wikipedia.org/wiki/Body_doubling'>Body Doubling</a></li><li><a href='https://en.wikipedia.org/wiki/Parallel_play'>Parallel Play</a></li></ul>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2432490/episodes/16877352-ep-10-fabric-and-instructional-design.mp3" length="27084964" type="audio/mpeg" />
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    <itunes:author>Eugene Meidinger</itunes:author>
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    <pubDate>Mon, 31 Mar 2025 12:00:00 -0400</pubDate>
    <itunes:duration>2254</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>10</itunes:episode>
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  <item>
    <itunes:title>Ep. 9 - Fabric in Government</itunes:title>
    <title>Ep. 9 - Fabric in Government</title>
    <itunes:summary><![CDATA[In this Episode Els Van Vessem talks about the challenges of implementing Fabric in the government. In it they talk about doing proof of concepts with Fabric and the limitations when your data is confidential, protected and on-premises. Data sovereignty often means sticking to a hybrid approach. We also discuss the challenges of similarly named products with slight differences. Links Veteran's affairs hackPolice force hackFabric MirroringFabric Warehouse T-sql surface areaFreedom of Informati...]]></itunes:summary>
    <description><![CDATA[<p>In this Episode Els Van Vessem talks about the challenges of implementing Fabric in the government. In it they talk about doing proof of concepts with Fabric and the limitations when your data is confidential, protected and on-premises. Data sovereignty often means sticking to a hybrid approach. We also discuss the challenges of similarly named products with slight differences.</p><p><b>Links</b></p><ul><li><a href='https://www.stripes.com/veterans/2024-04-25/veterans-health-care-cyberattack-leak-13659271.html'>Veteran&apos;s affairs hack</a></li><li><a href='https://www.dutchnews.nl/2024/09/police-leak-leaves-data-of-62000-officers-in-hands-of-hackers/'>Police force hack</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/database/mirrored-database/overview'>Fabric Mirroring</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-warehouse/tsql-surface-area'>Fabric Warehouse T-sql surface area</a></li><li><a href='https://en.wikipedia.org/wiki/Freedom_of_Information_Act_(United_States)'>Freedom of Information Act</a><br/><br/></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this Episode Els Van Vessem talks about the challenges of implementing Fabric in the government. In it they talk about doing proof of concepts with Fabric and the limitations when your data is confidential, protected and on-premises. Data sovereignty often means sticking to a hybrid approach. We also discuss the challenges of similarly named products with slight differences.</p><p><b>Links</b></p><ul><li><a href='https://www.stripes.com/veterans/2024-04-25/veterans-health-care-cyberattack-leak-13659271.html'>Veteran&apos;s affairs hack</a></li><li><a href='https://www.dutchnews.nl/2024/09/police-leak-leaves-data-of-62000-officers-in-hands-of-hackers/'>Police force hack</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/database/mirrored-database/overview'>Fabric Mirroring</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-warehouse/tsql-surface-area'>Fabric Warehouse T-sql surface area</a></li><li><a href='https://en.wikipedia.org/wiki/Freedom_of_Information_Act_(United_States)'>Freedom of Information Act</a><br/><br/></li></ul>]]></content:encoded>
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    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-16855124</guid>
    <pubDate>Tue, 25 Mar 2025 01:00:00 -0400</pubDate>
    <itunes:duration>2108</itunes:duration>
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    <itunes:season>1</itunes:season>
    <itunes:episode>9</itunes:episode>
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    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep 8. CI/CD in Fabric</itunes:title>
    <title>Ep 8. CI/CD in Fabric</title>
    <itunes:summary><![CDATA[Apologies for the audio; I stupidly forgot to double check my mic this episode. In this episode, Erin Dempster gives us an outside view of fabric focused on CI/CD. We talk about both deployment pipelines and devops pipelines and how she uses both tools in concert. This episode is interesting because it touches on the challenges of integrating a variety of data sources for an insurance company and using CI/Cd to keep everything in sync. PBIP file formatPBIR file formatDeployment PipelinesDevop...]]></itunes:summary>
    <description><![CDATA[<p><b>Apologies for the audio</b>; I stupidly forgot to double check my mic this episode.</p><p>In this episode, Erin Dempster gives us an outside view of fabric focused on CI/CD. We talk about both deployment pipelines and devops pipelines and how she uses both tools in concert. This episode is interesting because it touches on the challenges of integrating a variety of data sources for an insurance company and using CI/Cd to keep everything in sync.</p><ul><li><a href='https://learn.microsoft.com/en-us/power-bi/developer/projects/projects-overview'>PBIP file format</a></li><li><a href='https://learn.microsoft.com/en-us/power-bi/developer/embedded/projects-enhanced-report-format'>PBIR file format</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/cicd/deployment-pipelines/get-started-with-deployment-pipelines?tabs=from-fabric%2Cnew-ui'>Deployment Pipelines</a></li><li><a href='https://learn.microsoft.com/en-us/power-bi/developer/projects/projects-build-pipelines'>Devops Pipelines</a></li><li><a href='https://www.kerski.tech/bringing-dataops-to-power-bi-part43/'>Automating tests for broken visuals</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p><b>Apologies for the audio</b>; I stupidly forgot to double check my mic this episode.</p><p>In this episode, Erin Dempster gives us an outside view of fabric focused on CI/CD. We talk about both deployment pipelines and devops pipelines and how she uses both tools in concert. This episode is interesting because it touches on the challenges of integrating a variety of data sources for an insurance company and using CI/Cd to keep everything in sync.</p><ul><li><a href='https://learn.microsoft.com/en-us/power-bi/developer/projects/projects-overview'>PBIP file format</a></li><li><a href='https://learn.microsoft.com/en-us/power-bi/developer/embedded/projects-enhanced-report-format'>PBIR file format</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/cicd/deployment-pipelines/get-started-with-deployment-pipelines?tabs=from-fabric%2Cnew-ui'>Deployment Pipelines</a></li><li><a href='https://learn.microsoft.com/en-us/power-bi/developer/projects/projects-build-pipelines'>Devops Pipelines</a></li><li><a href='https://www.kerski.tech/bringing-dataops-to-power-bi-part43/'>Automating tests for broken visuals</a></li></ul>]]></content:encoded>
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    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-16806883</guid>
    <pubDate>Mon, 17 Mar 2025 12:00:00 -0400</pubDate>
    <itunes:duration>1773</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>8</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 7 - Semantic Link and Semantic Link Labs</itunes:title>
    <title>Ep. 7 - Semantic Link and Semantic Link Labs</title>
    <itunes:summary><![CDATA[In this episode, Stephanie Bruno talks about semantic link and semantic link labs, which allow you to better manage your Power BI resources with Fabric notebooks. Semantic allows you to query and work directly with your semantic model. Semantic Link Labs allows you to automate running the best practices analyzer against your model. I've heard nothing but great things about it. Links Semantic LinkSemantic Link LabsFabric.guru by Sandeep PawarFabric Notebook UtilsSemantic best practicesReport A...]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Stephanie Bruno talks about semantic link and semantic link labs, which allow you to better manage your Power BI resources with Fabric notebooks. Semantic allows you to query and work directly with your semantic model. Semantic Link Labs allows you to automate running the best practices analyzer against your model. I&apos;ve heard nothing but great things about it.</p><p><b>Links</b></p><ul><li><a href='https://learn.microsoft.com/en-us/fabric/data-science/semantic-link-overview'>Semantic Link</a></li><li><a href='https://github.com/microsoft/semantic-link-labs'>Semantic Link Labs</a></li><li><a href='https://fabric.guru/'>Fabric.guru</a> by Sandeep Pawar</li><li><a href='https://learn.microsoft.com/en-us/fabric/data-engineering/notebook-utilities'>Fabric Notebook Utils</a></li><li><a href='https://docs.tabulareditor.com/te2/Best-Practice-Analyzer.html'>Semantic best practices</a></li><li><a href='https://www.elegantbi.com/post/reportanalyzer'>Report Analyzer</a></li><li><a href='https://youtu.be/wPO8PqHGWFU'>SNL Shimmer skit</a></li><li><a href='https://darren.gosbell.com/2023/02/automatically-generating-measure-descriptions-for-power-bi-and-analysis-services-with-chatgpt-and-tabular-editor/'>ChatGPT to document measures</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Stephanie Bruno talks about semantic link and semantic link labs, which allow you to better manage your Power BI resources with Fabric notebooks. Semantic allows you to query and work directly with your semantic model. Semantic Link Labs allows you to automate running the best practices analyzer against your model. I&apos;ve heard nothing but great things about it.</p><p><b>Links</b></p><ul><li><a href='https://learn.microsoft.com/en-us/fabric/data-science/semantic-link-overview'>Semantic Link</a></li><li><a href='https://github.com/microsoft/semantic-link-labs'>Semantic Link Labs</a></li><li><a href='https://fabric.guru/'>Fabric.guru</a> by Sandeep Pawar</li><li><a href='https://learn.microsoft.com/en-us/fabric/data-engineering/notebook-utilities'>Fabric Notebook Utils</a></li><li><a href='https://docs.tabulareditor.com/te2/Best-Practice-Analyzer.html'>Semantic best practices</a></li><li><a href='https://www.elegantbi.com/post/reportanalyzer'>Report Analyzer</a></li><li><a href='https://youtu.be/wPO8PqHGWFU'>SNL Shimmer skit</a></li><li><a href='https://darren.gosbell.com/2023/02/automatically-generating-measure-descriptions-for-power-bi-and-analysis-services-with-chatgpt-and-tabular-editor/'>ChatGPT to document measures</a></li></ul>]]></content:encoded>
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    <itunes:author>Eugene Meidinger</itunes:author>
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    <pubDate>Mon, 03 Mar 2025 10:00:00 -0500</pubDate>
    <itunes:duration>1733</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep 6. Scouting out Fabric</itunes:title>
    <title>Ep 6. Scouting out Fabric</title>
    <itunes:summary><![CDATA[In this episode, Krystina Mishra talks about being an accidental Fabric admin. She talks about the challenges of being part of a centralized IT team that operational and business teams. She talks about the challenges of how everything with Dynamics 365 is slightly different than every other data source and how everything is convoluted with Synapse. She also talks about how there are nuanced differences between a P1 and an F64. Links Dynamics Great Plains schemaHow to Have Confidence and Power...]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Krystina Mishra talks about being an accidental Fabric admin. She talks about the challenges of being part of a centralized IT team that operational and business teams. She talks about the challenges of how everything with Dynamics 365 is slightly different than every other data source and how everything is convoluted with Synapse. She also talks about how there are nuanced differences between a P1 and an F64.</p><p><b>Links</b></p><ul><li><a href='http://dyndeveloper.com/DynTable.aspx?ModuleID=RM'>Dynamics Great Plains schema</a></li><li><a href='https://www.amazon.com/Have-Confidence-Power-Dealing-People/dp/0988727536'>How to Have Confidence and Power in Dealing with People</a></li><li><a href='https://en.wikipedia.org/wiki/Thermocline'>What is a thermocline</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/enterprise/surge-protection'>Fabric surge protection</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/enterprise/metrics-app'>Fabric capacity metrics app</a></li><li><a href='https://www.satisfactorygame.com/'>Satisfactory video game</a></li><li><a href='https://en.wikipedia.org/wiki/Brownian_motion'>What is Brownian Motion</a></li><li><a href='https://learning.oreilly.com/library/view/fundamentals-of-microsoft/9781098172916/'>Fundamentals of Microsoft Fabric</a></li><li><a href='https://www.meetup.com/kansas-city-sql-server-users-group/'>Kansas City SQL User Group</a></li></ul><p><br/></p><p><br/></p>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Krystina Mishra talks about being an accidental Fabric admin. She talks about the challenges of being part of a centralized IT team that operational and business teams. She talks about the challenges of how everything with Dynamics 365 is slightly different than every other data source and how everything is convoluted with Synapse. She also talks about how there are nuanced differences between a P1 and an F64.</p><p><b>Links</b></p><ul><li><a href='http://dyndeveloper.com/DynTable.aspx?ModuleID=RM'>Dynamics Great Plains schema</a></li><li><a href='https://www.amazon.com/Have-Confidence-Power-Dealing-People/dp/0988727536'>How to Have Confidence and Power in Dealing with People</a></li><li><a href='https://en.wikipedia.org/wiki/Thermocline'>What is a thermocline</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/enterprise/surge-protection'>Fabric surge protection</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/enterprise/metrics-app'>Fabric capacity metrics app</a></li><li><a href='https://www.satisfactorygame.com/'>Satisfactory video game</a></li><li><a href='https://en.wikipedia.org/wiki/Brownian_motion'>What is Brownian Motion</a></li><li><a href='https://learning.oreilly.com/library/view/fundamentals-of-microsoft/9781098172916/'>Fundamentals of Microsoft Fabric</a></li><li><a href='https://www.meetup.com/kansas-city-sql-server-users-group/'>Kansas City SQL User Group</a></li></ul><p><br/></p><p><br/></p>]]></content:encoded>
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    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-16682462</guid>
    <pubDate>Mon, 24 Feb 2025 08:00:00 -0500</pubDate>
    <itunes:duration>2149</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>6</itunes:episode>
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  </item>
  <item>
    <itunes:title>Ep. 5 - Realtime Intelligence</itunes:title>
    <title>Ep. 5 - Realtime Intelligence</title>
    <itunes:summary><![CDATA[In this Episode, Frank Geisler explains Realtime Intelligence in Microsoft Fabric. We learn how RTI is its own thing in Fabric and is not directly backed by Parquet like a Lakehouse is. We also dig into the distinction between real-time analytics and real-time intelligence. The latter is not just reporting but being able to trigger activity based on it. Links Fabric Realtime IntelligenceKQL languageKusto DetectiveRealtime DashboardData ActivatorFrank's TutorialsMicrosoft Sentinel and KQL]]></itunes:summary>
    <description><![CDATA[<p>In this Episode, Frank Geisler explains Realtime Intelligence in Microsoft Fabric. We learn how RTI is its own thing in Fabric and is not directly backed by Parquet like a Lakehouse is. We also dig into the distinction between real-time analytics and real-time intelligence. The latter is not just reporting but being able to trigger activity based on it.</p><p><b>Links</b></p><ul><li><a href='https://learn.microsoft.com/en-us/fabric/real-time-intelligence/overview'>Fabric Realtime Intelligence</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/real-time-intelligence/create-query-set'>KQL language</a></li><li><a href='https://detective.kusto.io/'>Kusto Detective</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/real-time-intelligence/dashboard-real-time-create'>Realtime Dashboard</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/real-time-intelligence/data-activator/activator-introduction'>Data Activator</a></li><li><a href='https://github.com/Frank-Geisler/FabConRTITutorial'>Frank&apos;s Tutorials</a></li><li><a href='https://learn.microsoft.com/en-us/kusto/query/kusto-sentinel-overview?view=microsoft-sentinel'>Microsoft Sentinel and KQL</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this Episode, Frank Geisler explains Realtime Intelligence in Microsoft Fabric. We learn how RTI is its own thing in Fabric and is not directly backed by Parquet like a Lakehouse is. We also dig into the distinction between real-time analytics and real-time intelligence. The latter is not just reporting but being able to trigger activity based on it.</p><p><b>Links</b></p><ul><li><a href='https://learn.microsoft.com/en-us/fabric/real-time-intelligence/overview'>Fabric Realtime Intelligence</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/real-time-intelligence/create-query-set'>KQL language</a></li><li><a href='https://detective.kusto.io/'>Kusto Detective</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/real-time-intelligence/dashboard-real-time-create'>Realtime Dashboard</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/real-time-intelligence/data-activator/activator-introduction'>Data Activator</a></li><li><a href='https://github.com/Frank-Geisler/FabConRTITutorial'>Frank&apos;s Tutorials</a></li><li><a href='https://learn.microsoft.com/en-us/kusto/query/kusto-sentinel-overview?view=microsoft-sentinel'>Microsoft Sentinel and KQL</a></li></ul>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2432490/episodes/16642110-ep-5-realtime-intelligence.mp3" length="24157349" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/x975knp31nvjfziil0v0dikaqila?.jpg" />
    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-16642110</guid>
    <pubDate>Mon, 17 Feb 2025 19:00:00 -0500</pubDate>
    <itunes:duration>2010</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>5</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep 4. Fabric Lakehouse versus Warehouse</itunes:title>
    <title>Ep 4. Fabric Lakehouse versus Warehouse</title>
    <itunes:summary><![CDATA[In this episode, Ginger Grant talks about the differences between warehouse and lakehouses in Fabric. We talk about how Warehouses make more sense if you are doing a lot of ad-hoc querying. In most other cases, Lakehouse will be easier and fewer steps. Links Lakehouse versus Warehouse decision guideDelta lake vacuumPolaris engine behind Fabric WarehouseLakehouse versus Warehouse (Advancing Analytics)Fabric surge protection (preview)]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Ginger Grant talks about the differences between warehouse and lakehouses in Fabric. We talk about how Warehouses make more sense if you are doing a lot of ad-hoc querying. In most other cases, Lakehouse will be easier and fewer steps.</p><p><b>Links</b></p><ul><li><a href='https://learn.microsoft.com/en-us/fabric/data-warehouse/get-started-lakehouse-sql-analytics-endpoint'>Lakehouse versus Warehouse decision guide</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-engineering/lakehouse-table-maintenance'>Delta lake vacuum</a></li><li><a href='https://www.youtube.com/watch?v=IqjVZexHCcE'>Polaris engine</a> behind Fabric Warehouse</li><li><a href='https://www.youtube.com/watch?v=cmQ9hs8DdR0'>Lakehouse versus Warehouse</a> (Advancing Analytics)</li><li><a href='https://blog.fabric.microsoft.com/en-us/blog/announcing-surge-protection-public-preview'>Fabric surge protection (preview)</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Ginger Grant talks about the differences between warehouse and lakehouses in Fabric. We talk about how Warehouses make more sense if you are doing a lot of ad-hoc querying. In most other cases, Lakehouse will be easier and fewer steps.</p><p><b>Links</b></p><ul><li><a href='https://learn.microsoft.com/en-us/fabric/data-warehouse/get-started-lakehouse-sql-analytics-endpoint'>Lakehouse versus Warehouse decision guide</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-engineering/lakehouse-table-maintenance'>Delta lake vacuum</a></li><li><a href='https://www.youtube.com/watch?v=IqjVZexHCcE'>Polaris engine</a> behind Fabric Warehouse</li><li><a href='https://www.youtube.com/watch?v=cmQ9hs8DdR0'>Lakehouse versus Warehouse</a> (Advancing Analytics)</li><li><a href='https://blog.fabric.microsoft.com/en-us/blog/announcing-surge-protection-public-preview'>Fabric surge protection (preview)</a></li></ul>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2432490/episodes/16595463-ep-4-fabric-lakehouse-versus-warehouse.mp3" length="22921781" type="audio/mpeg" />
    <itunes:author>Eugene Meidinger</itunes:author>
    <guid isPermaLink="false">Buzzsprout-16595463</guid>
    <pubDate>Mon, 10 Feb 2025 10:00:00 -0500</pubDate>
    <itunes:duration>1907</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>4</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep 3. Extracting Data from Legacy Systems</itunes:title>
    <title>Ep 3. Extracting Data from Legacy Systems</title>
    <itunes:summary><![CDATA[In this episode, Kellyn Gorman talks about the challenges of getting data out of legacy systems (i.e. relational data bases) into Fabric. She explains that whoever hosts the data wins. She talks about often content talks about the golden path or focuses on the marketing content, but it's much rarer to see content that deals with the difficult edge cases. We talk about how despite being Software as a Service, in order to learn Fabric you will need to learn networking, authentication, and infra...]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Kellyn Gorman talks about the challenges of getting data out of legacy systems (i.e. relational data bases) into Fabric. She explains that whoever hosts the data wins. She talks about often content talks about the golden path or focuses on the marketing content, but it&apos;s much rarer to see content that deals with the difficult edge cases.</p><p>We talk about how despite being Software as a Service, in order to learn Fabric you will need to learn networking, authentication, and infrastructure more broadly. We talk about how it&apos;s impossible to completely get away from hardware and infrastructure.</p><ul><li><a href='https://www.reuters.com/article/technology/former-microsoft-ceo-ballmer-does-about-face-on-linux-technology-idUSKCN0WC2RP/'>Ballmer does an about face on Linux</a></li><li><a href='https://en.wikipedia.org/wiki/LAMP_(software_bundle)'>Lamp stack</a></li><li><a href='https://www.jamesserra.com/archive/2024/12/ways-to-land-data-into-fabric-onelake/'>James Serra on ways to load data into Fabric</a></li><li><a href='https://www.sqlgene.com/2024/12/15/fabric-benchmarking-part-1-copying-csv-files-to-onelake/'>Eugene&apos;s benchmarking post</a>, inspired by Jame&apos;s post</li><li><a href='https://learn.microsoft.com/en-us/azure/storage/common/storage-use-azcopy-v10?tabs=dnf'>AzCopy tool</a></li><li><a href='https://www.hanselman.com/blog/please-learn-to-think-about-abstractions'>Scott Hanselman on abstractions</a></li><li><a href='https://en.wikipedia.org/wiki/Debugging#Techniques'>Wolf fence algorithm of troubleshooting</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Kellyn Gorman talks about the challenges of getting data out of legacy systems (i.e. relational data bases) into Fabric. She explains that whoever hosts the data wins. She talks about often content talks about the golden path or focuses on the marketing content, but it&apos;s much rarer to see content that deals with the difficult edge cases.</p><p>We talk about how despite being Software as a Service, in order to learn Fabric you will need to learn networking, authentication, and infrastructure more broadly. We talk about how it&apos;s impossible to completely get away from hardware and infrastructure.</p><ul><li><a href='https://www.reuters.com/article/technology/former-microsoft-ceo-ballmer-does-about-face-on-linux-technology-idUSKCN0WC2RP/'>Ballmer does an about face on Linux</a></li><li><a href='https://en.wikipedia.org/wiki/LAMP_(software_bundle)'>Lamp stack</a></li><li><a href='https://www.jamesserra.com/archive/2024/12/ways-to-land-data-into-fabric-onelake/'>James Serra on ways to load data into Fabric</a></li><li><a href='https://www.sqlgene.com/2024/12/15/fabric-benchmarking-part-1-copying-csv-files-to-onelake/'>Eugene&apos;s benchmarking post</a>, inspired by Jame&apos;s post</li><li><a href='https://learn.microsoft.com/en-us/azure/storage/common/storage-use-azcopy-v10?tabs=dnf'>AzCopy tool</a></li><li><a href='https://www.hanselman.com/blog/please-learn-to-think-about-abstractions'>Scott Hanselman on abstractions</a></li><li><a href='https://en.wikipedia.org/wiki/Debugging#Techniques'>Wolf fence algorithm of troubleshooting</a></li></ul>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/2432490/episodes/16553224-ep-3-extracting-data-from-legacy-systems.mp3" length="25690974" type="audio/mpeg" />
    <itunes:author>Eugene Meidinger</itunes:author>
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    <pubDate>Mon, 03 Feb 2025 10:00:00 -0500</pubDate>
    <podcast:transcript url="https://www.buzzsprout.com/2432490/16553224/transcript" type="text/html" />
    <itunes:duration>2138</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>3</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>Ep. 2 Medallion Architecture with Cathrine Wilhelmsen</itunes:title>
    <title>Ep. 2 Medallion Architecture with Cathrine Wilhelmsen</title>
    <itunes:summary><![CDATA[Cathrine explains how there isn't a single solution for architecting your data lake with Microsoft Fabric. We walk through all the different moving pieces of getting started with Fabric and lakehouses. Catherine touches on some different ways of implementing medallion in Fabric. She also makes the point Medallion is not the same as Dev / QA / Prod. Lastly, we talk about source control and branching workspaces in Fabric.  Links Fabric FebruaryMedallion architecture (Microsoft)Medallion Archite...]]></itunes:summary>
    <description><![CDATA[<p>Cathrine explains how there isn&apos;t a single solution for architecting your data lake with Microsoft Fabric. We walk through all the different moving pieces of getting started with Fabric and lakehouses. Catherine touches on some different ways of implementing medallion in Fabric. She also makes the point Medallion is not the same as Dev / QA / Prod. Lastly, we talk about source control and branching workspaces in Fabric.<br/><br/><b>Links</b></p><ul><li><a href='https://www.fabricfebruary.com/'>Fabric February</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/onelake/onelake-medallion-lakehouse-architecture'>Medallion architecture (Microsoft)</a></li><li><a href='https://www.databricks.com/glossary/medallion-architecture'>Medallion Architecture (Databricks)</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/enterprise/licenses'>Fabric concepts</a> (capacity, workspaces, licensing)</li><li><a href='https://en.wikipedia.org/wiki/Ouroboros'>Ouroboros</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>Cathrine explains how there isn&apos;t a single solution for architecting your data lake with Microsoft Fabric. We walk through all the different moving pieces of getting started with Fabric and lakehouses. Catherine touches on some different ways of implementing medallion in Fabric. She also makes the point Medallion is not the same as Dev / QA / Prod. Lastly, we talk about source control and branching workspaces in Fabric.<br/><br/><b>Links</b></p><ul><li><a href='https://www.fabricfebruary.com/'>Fabric February</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/onelake/onelake-medallion-lakehouse-architecture'>Medallion architecture (Microsoft)</a></li><li><a href='https://www.databricks.com/glossary/medallion-architecture'>Medallion Architecture (Databricks)</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/enterprise/licenses'>Fabric concepts</a> (capacity, workspaces, licensing)</li><li><a href='https://en.wikipedia.org/wiki/Ouroboros'>Ouroboros</a></li></ul>]]></content:encoded>
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    <itunes:author>Eugene Meidinger</itunes:author>
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    <pubDate>Mon, 27 Jan 2025 07:00:00 -0500</pubDate>
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    <itunes:title>Ep 1. Data Movement with Kristyna Ferris</itunes:title>
    <title>Ep 1. Data Movement with Kristyna Ferris</title>
    <itunes:summary><![CDATA[In this Episode, I interview Kristyna Ferris about the different types of data Movement in Microsoft Fabric. Specifically, we talk about gen 2 dataflows, data pipelines, and Spark notebooks. We see how you start simple and work your way up. Kristyna shares the "faucets first" approach at P3 adaptive.  Links Yak shavingRapid developmentDatatypes in Fabric Data WarehouseVARCAHR(MAX) previewMicrosoft decision guideSemantic Link - SempyPower Bi file import benchmarksSemantic Link LabsData on Whee...]]></itunes:summary>
    <description><![CDATA[<p>In this Episode, I interview Kristyna Ferris about the different types of data Movement in Microsoft Fabric. Specifically, we talk about gen 2 dataflows, data pipelines, and Spark notebooks. We see how you start simple and work your way up. Kristyna shares the &quot;faucets first&quot; approach at P3 adaptive.<br/><br/>Links</p><ul><li><a href='https://www.hanselman.com/blog/yak-shaving-defined-ill-get-that-done-as-soon-as-i-shave-this-yak'>Yak shaving</a></li><li><a href='https://amzn.to/4hoMGk2'>Rapid development</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-warehouse/data-types'>Datatypes in Fabric Data Warehouse</a></li><li><a href='https://blog.fabric.microsoft.com/en-us/blog/working-with-large-data-types-in-fabric-warehouse/'>VARCAHR(MAX) preview</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/get-started/decision-guide-pipeline-dataflow-spark'>Microsoft decision guide</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-science/semantic-link-overview'>Semantic Link - Sempy</a></li><li><a href='https://www.sqlgene.com/2024/11/28/benchmarking-power-bi-import-speed-for-local-data-sources/'>Power Bi file import benchmarks</a></li><li><a href='https://github.com/microsoft/semantic-link-labs'>Semantic Link Labs</a></li><li><a href='https://dataonwheels.wordpress.com/'>Data on Wheels blog</a></li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this Episode, I interview Kristyna Ferris about the different types of data Movement in Microsoft Fabric. Specifically, we talk about gen 2 dataflows, data pipelines, and Spark notebooks. We see how you start simple and work your way up. Kristyna shares the &quot;faucets first&quot; approach at P3 adaptive.<br/><br/>Links</p><ul><li><a href='https://www.hanselman.com/blog/yak-shaving-defined-ill-get-that-done-as-soon-as-i-shave-this-yak'>Yak shaving</a></li><li><a href='https://amzn.to/4hoMGk2'>Rapid development</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-warehouse/data-types'>Datatypes in Fabric Data Warehouse</a></li><li><a href='https://blog.fabric.microsoft.com/en-us/blog/working-with-large-data-types-in-fabric-warehouse/'>VARCAHR(MAX) preview</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/get-started/decision-guide-pipeline-dataflow-spark'>Microsoft decision guide</a></li><li><a href='https://learn.microsoft.com/en-us/fabric/data-science/semantic-link-overview'>Semantic Link - Sempy</a></li><li><a href='https://www.sqlgene.com/2024/11/28/benchmarking-power-bi-import-speed-for-local-data-sources/'>Power Bi file import benchmarks</a></li><li><a href='https://github.com/microsoft/semantic-link-labs'>Semantic Link Labs</a></li><li><a href='https://dataonwheels.wordpress.com/'>Data on Wheels blog</a></li></ul>]]></content:encoded>
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    <itunes:author>Eugene Meidinger</itunes:author>
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    <pubDate>Mon, 20 Jan 2025 12:00:00 -0500</pubDate>
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    <itunes:duration>1972</itunes:duration>
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    <itunes:season>1</itunes:season>
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