--- title: "#data-warehousing articles | Hashnode" description: "Explore 64 articles tagged #data-warehousing on Hashnode. Tutorials, guides, and how-tos from the community." url: "https://hashnode.com/tag/data-warehousing" --- Tag # #data-warehousing 64 posts · 10 followers [Soham Gaichor](https://hashnode.com/@soham111) · [Nov 4](https://hashnode.com/posts/how-modern-business-intelligence-architecture-works-from-raw-data-to-dashboards/6aeb87fee777b8d261fe93ed) ### [How Modern Business Intelligence Architecture Works: From Raw Data to Dashboards](https://soham111.hashnode.dev/how-modern-business-intelligence-architecture-works-from-raw-data-to-dashboards?utm_source=hashnode&utm_medium=feed) Learn how modern BI architecture works, from data to dashboards 7 min read · [soham111.hashnode.dev](https://soham111.hashnode.dev/how-modern-business-intelligence-architecture-works-from-raw-data-to-dashboards?utm_source=hashnode&utm_medium=feed) [srkhan2809](https://hashnode.com/@shahida-khan) · [Oct 17](https://hashnode.com/posts/crypto-finance-data-modeling/6ad5fbd143247129ad7ddec7) ### [Crypto Finance Data Modeling: A Staff Engineer's Field Guide](https://core-de-platform.hashnode.dev/crypto-finance-data-modeling?utm_source=hashnode&utm_medium=feed) Your data model isn't just a way to organize tables. In a financial system, it is part of how you prove what happened to someone's money. A badly designed model can make a successful trade look like a failed one, turn a refund into revenue, double-count trading volume, or report a wallet balance that never actually existed. And the most dangerous part? The dashboard can still look beautiful. I've seen teams spend weeks optimizing Spark jobs, partitioning Delta tables, tuning joins, and reducing query latency. All useful work. But before touching any of that, there's a more fundamental question worth asking: Are we even representing the business correctly? Because a query that returns the wrong answer in 200 milliseconds is not an optimization. It's a faster way to lose trust. Let's take a practical look at data modeling through the lens of a crypto trading platform. We'll examine the business requirements, the modeling choices, the architecture, the trade-offs, and the decisions a Staff Engineer should be making before the first production table is created. 29 min read · [core-de-platform.hashnode.dev](https://core-de-platform.hashnode.dev/crypto-finance-data-modeling?utm_source=hashnode&utm_medium=feed) [Dipak Mali](https://hashnode.com/@malidipak) · [Sep 26](https://hashnode.com/posts/slowly-changing-dimensions-scd-in-data-engineering/6ab830c84a9c6292b152a099) ### [Slowly Changing Dimensions (SCD) in Data Engineering](https://malidipak.hashnode.dev/slowly-changing-dimensions-scd-in-data-engineering?utm_source=hashnode&utm_medium=feed) While working with data warehouses, one common challenge is handling changes in dimension data while maintaining data accuracy and historical information. For example, consider a customer dimension: 8 min read · [malidipak.hashnode.dev](https://malidipak.hashnode.dev/slowly-changing-dimensions-scd-in-data-engineering?utm_source=hashnode&utm_medium=feed) [Aniruddha Banerjee](https://hashnode.com/@aniruddhawrites) · [Jul 17](https://hashnode.com/posts/the-post-acquisition-assumption-gap/6a5a830280634967a3771545) ### [The Post-Acquisition Assumption Gap](https://aniruddhawrites.hashnode.dev/the-post-acquisition-assumption-gap?utm_source=hashnode&utm_medium=feed) Why a single Product Master change exposed the hidden assumptions behind CDC, SCD, intent capture, and enterprise governance. 11 min read · [aniruddhawrites.hashnode.dev](https://aniruddhawrites.hashnode.dev/the-post-acquisition-assumption-gap?utm_source=hashnode&utm_medium=feed) [PRECIOUS ADEPOJU](https://hashnode.com/@techofficial26) · [Jul 7](https://hashnode.com/posts/the-invisible-engine-nobody-talks-about/6a4c4a964e9e4263d4f3d743) ### [THE INVISIBLE ENGINE NOBODY TALKS ABOUT.](https://from-fun-to-data.hashnode.dev/the-invisible-engine-nobody-talks-about?utm_source=hashnode&utm_medium=feed) I build the invisible data infrastructure enterprises need and trust. Exploring data engineering history, the big-data shift, and how to design cost effective scalable system for Africa. 3 min read · [from-fun-to-data.hashnode.dev](https://from-fun-to-data.hashnode.dev/the-invisible-engine-nobody-talks-about?utm_source=hashnode&utm_medium=feed) [Ricky Suhanry](https://hashnode.com/@datarunner01) · [Jun 3](https://hashnode.com/posts/demystifying-data-warehouses/6a1f6e97e536f18a602a05d7) ### [Demystifying Data Warehouses](https://datarunner01.hashnode.dev/demystifying-data-warehouses?utm_source=hashnode&utm_medium=feed) Introduction Before getting into the concept of data warehouses, it is important to understand data modeling for data warehouses. There are two main methodologies for developing a data warehouse. You 10 min read · [datarunner01.hashnode.dev](https://datarunner01.hashnode.dev/demystifying-data-warehouses?utm_source=hashnode&utm_medium=feed) [Vishnu D](https://hashnode.com/@vishd) · [May 15](https://hashnode.com/posts/oltp-vs-olap/6a0694c69c794cb653dbf87d) ### [OLTP vs OLAP: The Difference Every Data Engineer Should Know](https://thedatatrench.hashnode.dev/oltp-vs-olap?utm_source=hashnode&utm_medium=feed) The foundation beneath every data pipeline — and why it matters more than people think 10 min read · [thedatatrench.hashnode.dev](https://thedatatrench.hashnode.dev/oltp-vs-olap?utm_source=hashnode&utm_medium=feed) [Tech Insights Hub](https://hashnode.com/@JohnMikes) · [Feb 13](https://hashnode.com/posts/how-to-implement-real-time-analytics-with-clickhouse-1-1/698f0451a0f7e20edcec590c) ### [How to Implement Real-Time Analytics with ClickHouse](https://topperblog.hashnode.dev/how-to-implement-real-time-analytics-with-clickhouse-1-1?utm_source=hashnode&utm_medium=feed) How to Implement Real-Time Analytics with ClickHouse ClickHouse has emerged as one of the most powerful open-source columnar database management systems for real-time analytics. Developed by Yandex, it's designed to handle massive volumes of data wit... 6 min read · [topperblog.hashnode.dev](https://topperblog.hashnode.dev/how-to-implement-real-time-analytics-with-clickhouse-1-1?utm_source=hashnode&utm_medium=feed) [Ahmed Ghannam](https://hashnode.com/@ahmad-ghannam) · [Feb 9](https://hashnode.com/posts/mastering-data-warehousing-my-journey-with-bigquery-and-nyc-taxi-data/698a326523fa174ab8d0911d) ### [Mastering Data Warehousing: My Journey with BigQuery and NYC Taxi Data](https://ahmps.hashnode.dev/mastering-data-warehousing-my-journey-with-bigquery-and-nyc-taxi-data?utm_source=hashnode&utm_medium=feed) Date: February 9, 2026Module: Data Engineering Zoomcamp - Module 3Topic: Data Warehousing & BigQuery Introduction Just completed Module 3 of the Data Engineering Zoomcamp - Data Warehousing with BigQuery! This module was all about understanding mode... 13 min read · [ahmps.hashnode.dev](https://ahmps.hashnode.dev/mastering-data-warehousing-my-journey-with-bigquery-and-nyc-taxi-data?utm_source=hashnode&utm_medium=feed) [Maanvi Alung](https://hashnode.com/@Maanvi21) · [Feb 8](https://hashnode.com/posts/the-evolution-of-data-platforms-how-complexity-crept-in/698857da3b55ced9b6fb5f69) ### [The Evolution of Data Platforms: How Complexity Crept In](https://maanvi21.hashnode.dev/the-evolution-of-data-platforms-how-complexity-crept-in?utm_source=hashnode&utm_medium=feed) 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... 3 min read · [maanvi21.hashnode.dev](https://maanvi21.hashnode.dev/the-evolution-of-data-platforms-how-complexity-crept-in?utm_source=hashnode&utm_medium=feed)