Ranging from the business sector, to academics, to health sectors and even government, the importance of data cannot be overemphasized. As long as there are people or goods or valuables, there will always be an arising need for the compilation, processing and storage of data.
Data structures are the systematic format used to organize, process, retrieve and store data. For most complex applications to be successfully built, data structures serve as a building block. Building a data structure requires combining data elements to form a logical unit which represents an abstract data type that is relevant to the application or algorithm. Data Algorithm refers to the step-by-step procedure used to perform a data computation or to solve a data-related problem by analyzing, processing and extracting insights from large amounts of data.
IMPORTANCE OF DATA STRUCTURE
Ranging from the business sector, to academics, to health sectors and even government, the importance of data cannot be overemphasized. As long as there are people or goods or valuables, there will always be an arising need for the compilation, processing and storage of data.
Data structures are the systematic format used to organize, process, retrieve and store data. For most complex applications to be successfully built, data structures serve as a building block. Building a data structure requires combining data elements to form a logical unit which represents an abstract data type that is relevant to the application or algorithm. Data Algorithm refers to the step-by-step procedure used to perform a data computation or to solve a data-related problem by analyzing, processing and extracting insights from large amounts of data.
IMPORTANCE OF DATA STRUCTURE
What do I stand to get if I know data structure? Let me share a few relevance of data structure with you.
- For humans and computers to better understand a set of data, data structures frame the organization of the data. It is like trying to read a book from different chapters. It would be difficult to grasp the concept of the book. However, when the book is read chronologically from beginning to end, it would be understood better. Therefore, structuring data in an organized manner aids easy comprehension.
- Another benefit of choosing the proper data structure is that it enhances the performance of the software to ensure its operation is more scalable and faster.
- Data in itself occupies space, so when the proper data structure is used, the memory usage will be optimized, and optimal time complexity shall be achieved. It's just like when you refuse to fold your clothes properly before putting them in your box. It would occupy more space than it should. But notice that when the clothes are well otherwise, the box will close properly and there would be even some more space.
- It is also important to note that when there is no data structure, there may be no formal description for the organization of the model of the elements.
APPLICATIONS OF DATA STRUCTURE AND ALGORITHMS
There are various ways in which data structures and algorithms can be applied, some of which include;
Exchange of data: Data structures provide an adequate definition of how the information shared between applications, such as TCP/IP packets, should be organized.
Indexing: In situations where the objects are stored in a database, more complicated data structures such as B-Tree may be used for indexing.
- Searching: In order to enable specific rapid location of items from indexes that are created using binary or B-Tree and are commonly sought after.
- Data storage: For efficient data persistence, such as defining the collection of attributes and corresponding structures used to store records in DBMS, data structure plays a significant role.
- Scalability: In big applications that make use of large quantities of data, data structure and algorithm are required to manage and allocate data storage across distributed locations so as to ensure scalability and performance. However, there exist some data programming environments, such as Apache, which provide data structures that replicate the underlying structure of the database records so as to simplify querying.
FORMS OF DATA STRUCTURES
Data structures can come in different forms with varying characteristics, some of which include;
- Linear or Nonlinear: When a set of data is structured in such a manner that it is sequential, it can be described as linear, such as an array. On the other hand, if the data structure appears to be disorderly, it can be referred to as Non-linear, such as graphs.
- Homogeneous or heterogeneous: In a situation where all the repository data items are of the same type, the structure is described as homogeneous e.g. the collection of elements in an array. However if the data structures are of different types, then it is heterogeneous.
- Static or dynamic: Static structures have specific sizes, memory locations and structures. Dynamic structures are structures with sizes, memory locations and structures that shrink and expand depending on the use. What distinguishes static structures from dynamic structures is how they are compiled.
TYPES OF DATA STRUCTURE
Data may be classified as either Boolean, integer, floating-point, character, string, etc, just as was stated in our previous article on Database management. However, listed below are some of the data structures we have;
- Array: An array is a fundamental data structure that allows items of the same type to be stored in contiguous memory locations. It can also be used for tasks such as storing lists of items.
- Stack: A stack is used for the storage of the collection of items in the linear order in which they are applied. A stack can be in order of Last In and First Out (FILO) or vice versa.
- Queue: A queue is used for the storage of the collection of items like a stack, but it is First In and First Out (FIFO) in this case.
- Linked list: It is used to store a collection of items in a linear order, with each node/element containing a data item as well as a link connecting that item to the next item on that list.
- Tree: A tree is used for the storage of the collection of items in a way that all other elements are directly or indirectly connected to the root in a hierarchical form. Each node is either connected to a parent node or subnode, or both.
- Heap: A heap is a structure with parent nodes possessing values that are greater than the children nodes.
- Graph: A graph is a structure that is used for the storage of data in a form that is not orderly. It consists of vertices and lines used to connect them, which are known as edges. The nodes for graphs are finite.
- Trie: A trie is a data structure that is used for the storage of strings as data items so that it can be represented in a visual graph.
- Hash table: A hash table is a data structure that is used for the storage of a collection of data that a lots keys to values in an associative way.
HOW TO SELECT THE RIGHT DATA STRUCTURE AND ALGORITHMS
For you to choose the proper data structure and algorithm as a developer, you must know the supported operations and functions for the program - the functions that would make the structure operate as expected, the computational complexities of the program - the minimum acceptable performance for the data structures which could be in the form of speed, and the programming elegance - referring to how easy it is to navigate on the data structure.
NOW THAT YOU KNOW
Now that you know the relevance and importance of data structure and algorithm as a programming tool, you are one step ahead in your programming language. Do you know you can also join a host of others who started as learning developers yesterday but are now professional developers? Join us at Teners.net to get started. You also get the privilege of enjoying personalized mentorship. Don’t miss out on the opportunity to learn from the best. Start now!
