Data analysis skills are one of the hottest skills that have been in high demand on the job market for the past few years. A "data analyst" job title is not new to the market, however, due to the growth of data generation and the facilitation of data storage provided by cloud computing, many companies have now the capabilities to store their big data and to derive insights and value from it. Data analysis has been and will stay a fundamental skill to have for most jobs. In the following, I will discuss how to start a career as a data analyst and how I was able to secure a job as a data analyst at a reputable company. Disclaimer Prepare yourself for the worse; learn more about that here . You should read it if You are looking for an internship or a junior opportunity as a Data Analyst. Data Analyst Trends A simple search of the term " Data Analyst " on google trends can show us a graph with a positive trend of the frequency of searches. We can observe that from 2
Understanding the Modern Data Engineering Stack The Modern Data Engineering Stack In the ever-evolving landscape of data management and analysis, data engineering has undergone a significant transformation in recent years. The advent of big data and the need for scalable, real-time data processing have given rise to a modern data engineering stack that leverages a combination of technologies and architectural patterns to meet the demands of today's data-driven world. At the heart of this transformation, three fundamental data storage and processing approaches have emerged as key players: Data Lake, Data Warehouse, and the hybrid concept known as Data Lakehouse. Each of these plays a crucial role in handling the vast and diverse data sources that organizations encounter in their quest for actionable insights. Now, let's delve into these three data storage and processing paradigms and explore the differences, strengths, and best-use cases for Data Lak