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Everyone wants AI. But many organisations still haven’t built the foundations required to make AI successful. Before AI adoption, businesses need: ✔ Trusted data ✔ Scalable architecture ✔ Governa
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4 stages of real-world data engineering 😅 1. Fix a pipeline 2. Another one breaks 3. Reporting deadlines arrive 4. Repeat Not every day looks like this… …but data professionals know the feeling 😂
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The question shouldn’t be: “Which platform is better?” The better question is: “Which platform fits your business needs?” Microsoft Fabric simplifies analytics through a unified ecosystem. Azure
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Modern data platforms are evolving fast. New tools. New AI capabilities. New expectations from businesses. But the fundamentals still matter. At TPF Analytics, we believe strong data platforms shou
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One of the biggest Microsoft Fabric questions: When should you use Dataflow Gen2, Pipelines or Notebooks? They all move/transform data—but they solve very different problems. * Dataflow Gen2 → low-
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AI conversations are everywhere right now. But many businesses are still dealing with: * fragmented systems * weak governance * inconsistent reporting * low trust in data And that becomes a bigger
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One of the most common Microsoft Fabric questions: Lakehouse or Warehouse? The answer is usually: it depends on the workload. Lakehouse gives flexibility for engineering-heavy workloads. Warehouse
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A lot of data conversations focus on tools. But many challenges start much earlier. Things like: * fragmented systems * inconsistent reporting * governance gaps * tool sprawl And these issues ofte
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The conversation around data is changing. It’s no longer just about dashboards or reporting. More organisations are now focused on platform architecture, governance, scalability and building stronge
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Modern data teams often spend as much time managing integrations between tools as they do delivering actual value. Traditional stacks can work well — but they often come with: * multiple integration
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Microsoft Fabric brings powerful capabilities into one platform. But the real value comes when those capabilities align with a clear data strategy. That means understanding: * business priorities *
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Microsoft Fabric is often discussed as a set of tools. A more useful lens is to see it as a unified data platform supporting modern data strategy. Its value isn’t just in individual capabilities — d
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About @tpf.analytics

TPF Analytics | Microsoft Fabric • Power BI • Data Engineering is a Instagram growing creator. With 277 followers and 12 posts, tpf.analytics's account shows a follower-to-following ratio of 19.8:1. View all content anonymously on Pictame - no login required.

tpf.analytics's engagement rate sits at 0.66%. For accounts with 1K-10K followers, the average is around 5%, so there's some room to grow — though every community is unique.

Out of the last 12 posts, 8% are videos and 92% are photos. Notably, photos tend to get 1.9x more engagement than videos. New content goes up pretty much every day — a very consistent posting habit. Captions lean detailed, averaging 642 characters.

0.66% engagement rate — room to grow compared to average for 1K-10K follower accounts.
8% videos, 92% photos. Photos get 1.9x more engagement here.
Posts every day — very consistent.
19.8:1 follower-to-following ratio.

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@tpf.analytics

TPF Analytics | Microsoft Fabric • Power BI • Data Engineering

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Top Hashtags
#MicrosoftFabric#DataPlatform#DataArchitecture#DataEngineering#DataStrategy#DataGovernance#AIReadiness#TechHumor

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