Explore data management essentials for deep learning projects in this comprehensive lecture. Delve into data labeling, storage, versioning, and processing techniques. Learn about the data flywheel concept, annotator training, labor sources, and service comparisons. Discover database scalability, data lake organization, and versioning strategies. Examine task dependencies and workflow management tools like Luigi and Airflow. Gain practical insights for implementing efficient data pipelines in machine learning projects.