How Data Engineering Supports Financial Analysis: A Practical Guide

<h1>The Soft Skills Behind the Code</h1> <p>Beyond the technical aspects, teamwork and communication are critical in data engineering, especially in an agile setting. Being able to clearly define requirements, manage expectations, and keep stakeholders informed are skills just as crucial as writing the perfect code. To ensure alignment between development progress and business expectations, a regular cadence of weekly check-ins with business stakeholders is maintained. These touchpoints serve as an opportunity to review progress, clarify any ambiguities, and adjust the course as needed. This project is not just a demonstration of technical expertise but also an exercise in effective communication and collaboration.</p> <h1>Data Fetching and Initial Validation</h1> <p>We used Python, Pandas, and the IEX Cloud API to fetch historical stock data for FAANG companies. The code includes logging and basic error handling.</p> <p><a href="https://python.plainenglish.io/how-data-engineering-supports-financial-analysis-a-practical-guide-bc78cfa47e40"><strong>Click Here</strong></a></p>