Startups need lean data science stacks that scale fast without upfront infrastructure costs..Python and SQL remain core languages for analytics machine learning and production pipelines..Cloud platforms let startups deploy models store data and scale compute on demand..Spark and data engines handle large datasets batch processing and real time streams..TensorFlow PyTorch and Scikit learn help teams build train and refine models efficiently..MLOps tools enable experiment tracking deployment monitoring and reproducibility across environments teams easily..Jupyter notebooks accelerate exploration collaboration and faster iteration during early product development cycles..BI and visualisation tools translate complex data into insights founders can act on..A smart data stack turns startup data into competitive advantage not technical overhead..Read More Stories.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp