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Nidhi Goswami

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Top 30 SQL Interview Questions and Answers

Are you seriously preparing for data related roles and wants to ace interview?. Then this blog really helps you to prepare highly asked Language...

SQL vs MySQL: Explained with Examples

We are already stepping in the world of data where to manage this, we generally require databases. As in this industry we have likely...

Top 10 Industrial Applications of Business Analytics in 2025

In this fast moving world data is often called the assets for various businesses. Every click, transaction, and interaction generates valuable information that businesses...

SQL Commands Cheat Sheet: 25 Most Popular Commands

Whether you are an experienced developer or a fresher it is very essential to learn SQL commands to work with databases easily. Structured Query...

Top 100 Data Science Interview Questions and Answers (2025)

Getting a data science job in 2025 can feel a bit scary and especially with so many topics to learn like Python, Machine Learning,...

Exploratory Data Analysis: A Complete Beginner’s Guide

What is Exploratory Data Analysis? Exploratory Data Analysis also commonly known as EDA which is the process of taking a first look at your data...

Why Python for Machine Learning is a Top Choice?

When starting out in machine learning, one of the first things people recommend is using Python. And honestly, it makes sense. Python is known...

Graph Coloring: Explained Simply with Examples & Python Code

Graph coloring is like playing with crayons but instead of coloring pictures you are coloring dots called nodes in a graph. The rule is...

Top Data Science Skills You Need to Succeed in 2025

Data is everywhere in this current era. From personalized recommendations on Netflix to real-time traffic updates on Google Maps, data is driving the world...

Data Normalization in Machine Learning: Techniques & Advantages

In the dynamic world of machine learning, the quality of your data often determines the effectiveness of your models. One crucial step in preprocessing...

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