Wednesday, March 9, 2022

Stacks And Queues

 Does this sound familiar? But we'll look into it more.

They are a group of items. The variation is between where to insert an item and which item to remove. Stacks operate on a last-in-first-out (LIFO) basis, whereas queues operate on a first-in-first-out (FIFO) basis.


Stacks

A stack's main operations are push, pop, and is Empty.

We use the terms push to insert an item on top of the stack and pop to remove the most recently inserted one.

(Source)

-Pop

Pop not only removes but also returns the most recently inserted item.

(Source)

Consideration Of Stack With Array Implementation

       Overflow: occurs when a user attempts to insert an item into a full-stack. So, either issue an exception or employ array resizing.

       Underflow: If a user attempts to delete from an empty stack, an exception is thrown.

       Null Items: Do we allow for the insertion of null items? Yes, we do in some circumstances.

       Loitering: is the act of retaining a reference to an object when it is no longer required. When we remove an item from the stack, we simply decrement N without assigning the item to null.

Stack Analysis - Linked List Vs Arrays

Time - Linked List techniques consume constant time, however, they are nonetheless inefficient owing to object definition and dealing with links. Accessing arrays is substantially faster; it takes O (1).

Memory - Because of the size of node objects, linked lists demand extra memory (see figure below). Arrays, on the other hand, demand less memory space.

(Source)

Stack Applications

       The web browser's back button

       Compiler

       Dijkstra’s two-stack algorithm

       …and the list continues on and on.

Queues

A queue's basic operations are enqueue, dequeue, and is Empty.

-Enqueue

(Source)

If the queue was empty before inserting an item, "first" should correspond to the newly generated node as well, and so "oldlast" will be null.

-Dequeue

Dequeue not only removes the initial item added but also returns it.

If the queue is empty after removing an item, "last" should be null as well.


(Source)

Consideration Of Queues With Array Implementation

It's the same consideration that was raised with Stack.

       Underflow & Overflow: We didn't think about what happens when we put an item into a full queue or delete an item from an empty queue.

       Null Items: we allow the user to enter null values.

       Loitering: We did not remove references to items that were no longer required.

Queue Analysis — Linked List Vs Arrays

       Time is the same as it is with Stack when utilizing Linked Lists and Arrays.

       Memory works in the same way as Stack, but with Linked Lists and Arrays. It just necessitates more memory for the two points.

Conclusion

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Saturday, March 5, 2022

What Are The Key Features Of Big Data?

Big Data is one of the world's fastest-growing industries. It refers to the collection and analysis of massive amounts of data in order to provide actionable insights that an organization may use to improve its many aspects. It's a broad notion with multiple benefits. This is why firms in a variety of industries are focusing on implementing this technology. 

What Exactly Is Big Data?

Big Data is the study and extraction of information from extraordinarily massive data sources. The word can also refer to vast amounts of data that rise exponentially over time. Such data is so massive and complicated that no conventional approach or standard data management tool can successfully process and store it. Organizations in numerous industries create and use data to improve their processes, from social media platforms to e-commerce businesses.

Benefits Of Big Data

1. Improved Decision-Making

Implementing big data can help businesses and organizations make more informed decisions in less time. It enables them to fine-tune their strategy by utilizing external intelligence such as search engines and social media platforms. Big data may detect trends and patterns that would otherwise be invisible, assisting businesses in avoiding blunders.

2. Customer Service Based On Data

Customer service is another area where big data may have a significant impact across all businesses. Companies are abandoning traditional consumer feedback systems in favor of data-driven solutions. Such technologies can help companies analyze customer feedback more efficiently and provide better customer care to their customers.

3. Enhancement Of Efficiency

Big data is used by organizations to discover the weak points in their systems. They then apply their findings to remedy those issues and significantly improve their operations. For example, Big Data has greatly facilitated the industrial sector's efficiency through IoT and robotics.

4. Decision Making In Real-Time


Big Data has revolutionized many industries by enabling real-time tracking, including inventory management, supply chain optimization, anti-money laundering, etc.

Some Key Big Data Insights Of 2022

  Every minute, 300 hours of video are posted to YouTube, resulting in more than 1 billion gigabytes of data on their servers. (Source)

  In India, the average income for a big data engineer is INR 7.88 lakh per year. It starts at INR 3.99 lakh per year and can reach INR 17 lakh per year depending on their talents and expertise. (Source)

  According to experts, big data analytics can significantly improve the healthcare industry. They believe that using big data can save this industry up to $300 billion every year. (Source)

  In 2018, the global revenue of business intelligence and analytics software solutions was an astounding $24 billion. (Source)

Conclusion

Big data analysis, also known as data mining, deals with massive amounts of data, whereas data science employs machine learning methods to construct and develop statistical models to generate knowledge from a mountain of big data. Big Data is simply a subset of data science in which the data sets are massive and require logistical solutions to cope with.

 As businesses begin to use more data, the demand for Big Data expertise will rise. This is why, since 2013, there has been a continuous increase in the need for numerous Big Data professionals. Check out our System Design Course and Data Science Coaching In Bangalore to get started in this promising area.

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