In recent years, DNA-based storage systems have emerged as promising solutions for long-term data archival due to their high data density and durability. This talk explores the intricacies of DNA storage, highlighting its advantages and challenges. DNA-based storage possesses distinct characteristics that distinguish it from conventional storage mediums. Synthesized DNA strands contain inherent redundancy due to replication during synthesis and sequencing processes, yet their unordered arrangement introduces complexity to data retrieval. Additionally, synthesis and sequencing introduce errors such as insertions, deletions, and substitutions, posing significant challenges to data integrity. This talk will begin with an examination of the background of DNA storage and the challenges posed by the DNA storage channel. Throughout the presentation, we will emphasize several open problems related to the channel, underscoring the need for innovative solutions to advance DNA storage technology. To bridge theory with application, we will discuss two recent research projects. The first focuses on the DNA coverage depth problem, which aims to reduce both, cost and latency in DNA storage. We will investigate how error-correcting codes and retrieval algorithms impact the sequencing coverage depth and explore how this coverage can be optimized. Additionally, we will explore a scalable end-to-end DNA storage pipeline, integrating deep neural networks and tensor-product based error-correcting codes, significantly improving speed, accuracy, and code rate. These insights contribute to advancing the efficiency and feasibility of DNA storage solutions, setting the stage for future advancements.