Hello everyone! Welcome to another Interesting Tech Update on Analytics! Recently, I came across an interesting update about  chDB in the  TDLR Newsletter, which motivated me to explore it further. Until now, I’ve mostly worked with server‑based  SQL engines such as  PostgreSQL, MySQL, and SQL Server. I’ve also used serverless  SQL engines on many challenge platforms like DataLemur, LeetCode, and HackerRank. These platforms typically use in‑process  SQL engines, which don’t

Healthcare organizations generate huge amounts of patient and provider data daily. In this blog, we use Python to analyze the HC Dataset from Kaggle, focusing on patient discharge trends, provider specialties, and ambulatory visit patterns. Key insights include variations in length of stay (LOS), discharge dispositions, and visit volumes, which help hospitals optimize staffing, improve operational efficiency, and improve patient care.

Python makes data analysis simple and complete. You can clean data, merge files and databases, run statistical tests, and even prepare it for charts and models—all in one tool, for free.

Hi team! Check out my latest blog on why data cleaning is critical for accurate visualizations and better business decisions. I also show a real-world COVID-19 dataset case study using Python.