C Infix to Postfix Conversion and Evaluation

Posted by on Sep 21, 2025 in Information Technologies Engineering | 0 comments

This C program demonstrates the conversion of an infix mathematical expression to its postfix equivalent and subsequently evaluates the postfix expression. It utilizes stack data structures for efficient processing of operators and operands, providing a clear example of algorithm implementation in C.

Standard Library Includes

The necessary header files for input/output, memory allocation, string manipulation, character type checking, and mathematical operations.

#include <stdio.h>
#include <
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Big Data Analytics: Types, Tools, and Enterprise Solutions

Posted by on Aug 27, 2025 in Information Technologies Engineering | 0 comments

Understanding Big Data and Its Management

Every day, users generate 2.5 quintillion bytes of data. Statista predicts that by the end of 2021, the internet would generate 74 Zettabytes (74 trillion GBs) of data. Managing this vast and continuous data stream is increasingly difficult. Big data was introduced to manage such complex data, involving the extraction of large and complex datasets into meaningful information that traditional methods cannot analyze.

For example, Azure Cloud Services like Azure

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Big Data Fundamentals: Concepts, Technologies, & Use Cases

Posted by on Aug 20, 2025 in Information Technologies Engineering | 0 comments

What is Big Data?

Data that is very large in size is called Big Data. Normally, we work with data sizes in megabytes (MB) for documents like Word or Excel, or a maximum of gigabytes (GB) for files like movies or code. However, data in petabytes (PB), which is 1015 bytes, is considered Big Data. It is estimated that almost 90% of today’s data has been generated in the past three years.

Sources of Big Data

These data come from many sources, including:

  • Social Networking Sites: Facebook, Google, and LinkedIn
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Hadoop HDFS and MapReduce Core Concepts Explained

Posted by on Jul 2, 2025 in Information Technologies Engineering | 0 comments

HDFS NameNode vs. DataNode Differences

  • NameNode is the master node in HDFS, while DataNode is the slave node.
  • NameNode stores metadata like file names, directory structure, permissions, etc.
  • DataNode stores the actual data blocks of the files.
  • NameNode manages the namespace and regulates access to files.
  • DataNode performs read and write operations on HDFS blocks.
  • There is only one active NameNode (with a standby for high availability).
  • There are usually many DataNodes in a Hadoop cluster.
  • If NameNode fails,
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