Introduction Data transformation is a critical step in modern data analytics, and dbt (Data Build Tool) has emerged as a leading solution for transforming raw data into actionable insights. But what exactly is dbt, and how does it work? In…
The harsh truth about the analytics industry is that “simple doesn’t sell”. It’s challenging to advocate for simplicity in data architecture because simple solutions often appear effortless, and who wants to invest in something that looks easy? While everyone claims…
🚀 My personal Hall of Fame of tools and technologies 🛠️ (Python ecosystem edition) These tools and technologies have served me well over the years, so I thought I’d share them: 🔵 Click, Loguru: Creating command line interfaces🔵 dotenv, pyyaml:…
Relying solely on the outputs of machine learning (ML) models without a thorough verification can lead to unexpected results. Continuing from my previous DevLog, I embarked on a project to analyze car prices across various brands using data from AutoScout24.…
In Snowflake, databases are similar to virtual hard drives where you store data, while warehouses are the virtual compute resources you use to run analytical queries. In today’s data-driven world, having a robust and efficient data management system is crucial…
Overview: What is dbt and what can it do for your data pipeline? One tool that we recommend and often use is dbt (data build tool), which focuses on simplifying and accelerating the process of data transformation. In this blog,…
Most businesses today are data-driven, and to make sound decisions, they need access to accurate and timely data. However, setting up and maintaining a data warehouse can be costly and time-consuming. Apache Superset is an open-source tool that makes it…
Building a data warehouse can be a costly endeavor, with several factors impacting the final price tag. Factors such as the size and complexity of the data, the tools and technologies used, the number of users, and the level of…
In today’s data-driven world, companies are constantly on the lookout for new and innovative ways to extract value from the vast amounts of data they generate and collect. To meet this demand, there are three key approaches that have emerged…
As a data engineer, you know that the field is full of challenges. From data quality to data transformation, there are always issues to be addressed and problems to be solved. In this post, we’ll take a look at some…