Data Engineering vs. Data Science

What’s the Difference?

🔍 What They Do

– Data Engineers build systems to collect, store, and organize data. – Data Scientists analyze data to find patterns and make predictions.

– Data Engineers: Coding, databases, cloud computing. – Data Scientists: Statistics, machine learning, data visualization.

🛠 Key Skills

– Data Engineers: SQL, Python, Apache Spark, AWS. – Data Scientists: Python, R, TensorFlow, Jupyter Notebook

📌 Tools They Use

– Data Engineers make sure data is clean, structured, and accessible. – Data Scientists use data to answer questions and solve problems.

🎯 Main Focus

– Engineers prepare and manage the data. – Scientists use that data to create insights and predictions.

🤝 How They Work Together

– Data Engineers work in IT & data infrastructure teams. – Data Scientists work in analytics & business strategy teams.

🏢 Where They Work

Think of it like this: Data engineers build the pipeline, and data scientists turn the water into useful information.

Swipe up to learn more