data engineering

Over the past two decades, many organizations have focused on creating data warehouses and business intelligence (BI) solutions using relational databases. However, these solutions often struggle to handle unstructured data…

Let's start by answering a fundamental question: Why is Docker important? Think about a situation that every developer can relate to — when you install a new tool on your…

Have you ever wondered why we don’t use Apache Airflow to process data directly? Why is it necessary to integrate Apache Spark with Apache Airflow? Take a moment to think…

The Data Engineer Roadmap helps you become a data engineer in the easiest way. As organizations work with large amounts of data, they need skilled professionals who can create and…

Graph databases are useful for complex queries, like social network analysis, product recommendations, and fraud detection. They can help us discover new insights, solve problems, and uncover fraud. It is…

Apache Airflow and Apache NiFi stand out as two powerful open-source tools. Both are designed to streamline data workflows, they address different aspects of the data processing pipeline. This article…