In terms of importance and widespread usage, the following data structures are considered fundamental and essential to know:

1. Array: Arrays are widely used and provide a simple way to store and access elements. They are used in various algorithms and data storage scenarios.

2. Linked List: Linked lists are fundamental for dynamic data structures and provide efficient insertion and deletion at the expense of random access.

3. Stack: Stacks are essential for managing function calls, expression evaluation, and handling recursive algorithms.

4. Queue: Queues are crucial for managing processes, scheduling, and implementing algorithms like breadth-first search.

5. Hash Table: Hash tables offer efficient key-value pair storage and retrieval, making them widely used in many applications and algorithms.

6. Binary Tree: Binary trees are fundamental for hierarchical data representation and efficient search, traversal, and sorting operations.

7. Graph: Graphs are used to model relationships and solve problems like network analysis, shortest path algorithms, and social network analysis.

8. Heap: Heaps are vital for efficient priority queue operations and are used in algorithms like Dijkstra's algorithm and heap sort.

9. Binary Search Tree: Binary search trees enable efficient search, insertion, and deletion operations based on key values.

10. Trie: Tries are particularly useful for efficient prefix-based search operations, making them crucial for applications involving dictionaries and autocomplete.

These data structures provide a solid foundation for understanding and implementing various algorithms and solving a wide range of programming problems efficiently. While the other data structures in the list are also important in specific scenarios, mastering the ones mentioned above will give you a strong basis for data manipulation and algorithmic problem-solving.