Medallion (Pull) vs Data Product (Push) architectures
This article summarizes the core arguments from Modern Data 101‘s piece: Data Products: A Case Against Medallion Architecture. The original […]
Data Infrastructure
Exploring Idempotency in Data Modelling: Why Pipelines Fail
What is an Idempotent Pipeline? An idempotent pipeline produces the same results : This means that both production runs and
Slowly Changing Dimensions (SCDs) in Data Warehousing
SCD Definition: Change of dimension over a course of time rather changing on regular scheduled time. Why do dimensions change?
The impact of escaping Referential Integrity on building Wide Facts in Data Warehouse – Data Orphanage
What is Wide-Facts, why we need it? “Wide-Fact” is a fact table that contains a high number of columns and
Fixing Many-to-Many Relationships in Power BI with Link or Join Tables
The Simple.. Imagine trying to organize a party where every guest is talking to every other guest at the same
Designing Health and Safety Dashboard — Step-by-Step Process
As a data analyst, I’ve always been driven by the thrill of transforming raw data into actionable insights. But when
Difference between Conceptual, Logical and Physical Data Model
Have you ever wondered how the data in a database is structured and organized? From the books you borrow at
Python+Batch Script for Data Dictionary(.XLSX) validation with Postgres Data Warehouse
Are you facing challenges related to discrepancies and validation in your Analytics team? Explore these situations: If you are facing
Top 6 Techniques for Identifying and Resolving Database Differences (Postgres)
In the complex world of database management, ensuring consistency between databases, schemas, and tables is crucial for seamless data operations.