Data structures are the fundamental building blocks of computer science—organized formats for storing, accessing, and manipulating data in memory. From simple arrays to complex self-balancing trees, they determine how efficiently programs execute. The right structure can reduce an $O(n^2)$ algorithm to $O(\log n)$—turning a sluggish system into a responsive one. Understanding data structures is not just about memorization; it's about recognizing trade-offs between time, space, and complexity for the problem at hand. When you choose a hash table over a binary search tree, you're balancing constant-time lookups against memory overhead and lack of ordering.