Feb 16 · 14 min read · Date: February 16, 2026Module: Data Engineering Zoomcamp - Module 4Topic: Analytics Engineering with dbt Introduction Just completed Module 4 of the Data Engineering Zoomcamp - Analytics Engineering with dbt (data build tool)! This module was transf...
Join discussionFeb 15 · 1 min read · Week 4 of Data Engineering Zoomcamp by @DataTalksClub complete Just finished Module 4 - Analytics Engineering with dbt. Learned how to: ✅ Build transformation models with dbt ✅ Create staging, intermediate, and fact tables ✅ Write tests to ensure dat...
Join discussionFeb 8 · 3 min read · Modern data platforms promise scale, speed, and flexibility — yet they often feel overly complex.Data lakes, warehouses, pipelines, BI layers, governance tools — instead of simplifying analytics, many platforms seem to add more moving parts. This com...
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Jan 31 · 10 min read · Why your "Sales by Region" keeps lying to you If a "simple" KPI like Sales by Region keeps changing every time someone moves house or changes team, that's not your dashboard being flaky. That's your data model telling you it only remembers the latest...
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Jan 27 · 4 min read · The real problem (not the surface-level one) Power BI connecting directly to Google Sheets looks simple — until it isn’t. In real usage, stakeholders started facing: 429: Too Many Requests errors Random refresh failures Slow preview and load behav...
Join discussionDec 22, 2025 · 3 min read · 📜 What Is the Modern Data Stack? The Modern Data Stack (MDS) is a cloud-native approach to building data platforms using specialised, best-in-class tools instead of monolithic systems. Rather than relying on a single vendor for everything, modern te...
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Dec 20, 2025 · 3 min read · 📜 What Is the Data Quality Crisis? As data pipelines grow more complex, organisations face a critical challenge:Can we trust our data? Despite advanced tools and cloud platforms, many teams struggle with: Conflicting metrics across dashboards Brok...
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Dec 18, 2025 · 3 min read · 📜 What Is the ETL/ELT Evolution? For decades, ETL (Extract, Transform, Load) was the standard approach to building data pipelines.Data was extracted from source systems, transformed in intermediate servers, and then loaded into warehouses. With clou...
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Dec 17, 2025 · 3 min read · 📜 What Is “Storage Wars”? As data volumes grow, organisations face a fundamental question:Where should data live once it’s ingested and prepared? Over time, three major storage architectures have emerged: Data Lakes for raw, large-scale data storag...
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Dec 16, 2025 · 3 min read · 📜 What Does “Raw to Ready” Mean? Every data journey begins with raw data — logs, events, transactions, files, APIs, sensors, and user interactions.Raw data is often incomplete, inconsistent, duplicated, or unstructured. Before it can be analysed, it...
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