fbpx
Agile easy 10 points to remember

Agile easy 10 points to remember

 10 pointe to remember Agile

Agile is a project management methodology that emphasizes iterative and incremental development, flexibility, and customer collaboration.

Here are some key points to help you understand Agile:

  1. Agile values individuals and interactions over processes and tools.
  2. Agile encourages customer involvement and feedback throughout the development process.
  3. Agile emphasizes the delivery of working software in short iterations, usually 1-4 weeks long.
  4. Agile teams work collaboratively, with regular team meetings and continuous communication.
  5. Agile embraces change, with the ability to adapt to evolving requirements and priorities.
  6. Agile emphasizes the importance of delivering business value quickly and regularly.
  7. Agile relies on self-organizing teams that can adapt to changing requirements and circumstances.
  8. Agile uses a variety of tools and techniques, including user stories, daily stand-up meetings, and retrospectives.
  9. Agile focuses on creating a minimum viable product (MVP) that can be tested and validated with customers.
  10. Agile values quality and testing, with a focus on continuous integration and automated testing.
Data Structures and Algorithms

Data Structures and Algorithms

Data Structures and Algorithms

Data Structures and Algorithms

Data Structures

The programmatic way of storing data, so that it can be used efficiently. Almost every enterprise application uses various types of data structures in one or the other way.

Algorithms

    Algorithms is a step-by-step   e programmatic way of storing data, so that it can be used efficiently. Almost every enterprise application uses various types of data structures in one or the other way.

Why do we need to learn Data Structures and Algorithms?

    Every day the complexity of applications are increasing which result in more complex and rich sets of data, due to the complexity we generally face the following 3 types of problems every day.

Problems faced by the large enterprise or corporate (service and data):

  1. Data Searching: Consider users registered in social app is more than 1 million, if we want to search for one person in that 1 million, the search operation need to be performed on that 1 million user records. Thus the search operation slows down every time new user data is stored.
  2. Processor capacity/speed: Capacity of processor need to be very high to handle such large sets of data. Failing to do so will cause poor performance and bad experience to the users.
  3. Too-many requests: Everyone hold PC/Laptop, Mobile devices and IoT gadgets which connects to the service to perform some operation on the data. Thus the number of service request sent and received by the devices and the server are way many. Even the fastest server might fail to respond sometimes.

How to solve the above problems?

    To solve the above 3 problems (Data Searching, Processor capacity/speed & Too-many requests) we can use the Data Structures.

    Data can be organized in a way that data is categorized and sorted before searching, thus allowing us to search instantly.

Exactly what is that we are going to do with Data structures and algorithms?

    As we already know the Algorithms is step-by-step procedure for performing an operation. And that operations are used for manipulating the data. Let’s us see the operations or the categories of algorithms.

Categories of algorithms:

  • Search
  • Sort
  • Insert
  • Update
  • Delete
Data Structures and Algorithm - Categories

 

In the next article in details about the algorithms and the data structures implementation with example.

 

LIKE | SHARE | FOLLOW

WeCanCode-Author

WeCanCode-Author

January 08, 2022

Senior Developer | Java & C#.NET | 10++ years of IT experience.

Planning to learn ReactJS or Angular or Flutter.!

Pin It on Pinterest