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Introduction to SQL for Data Engineering

Analytics Vidhya

Introduction In this article, we will be looking for a very common yet very important topic i.e. SQL also pronounced as Ess-cue-ell. So this time I’ll be answering some of the factual questions about SQL which every beginner needs to know before getting […].

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5 SQL Visualization Tools for Data Engineers

KDnuggets

This article will discuss SQL visualization, its role in augmenting the modern-day data engineer, and five categories of SQL visualization tools.

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SQL vs NoSQL Databases – A Key Concept Every Data Engineer Should Know

Analytics Vidhya

Overview Understand what SQL and NoSQL databases are. Go through the prominent difference between SQL and No SQL Databases. The post SQL vs NoSQL Databases – A Key Concept Every Data Engineer Should Know appeared first on Analytics Vidhya. This is not an exhaustive.

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SQL and PL/SQL – An Unmissable Comparison

Analytics Vidhya

Data is getting significant and gaining more traction by the day. Hence it is required to store such a large amount of data carefully. This brings up databases, and SQL and PL/SQL stand […]. The post SQL and PL/SQL – An Unmissable Comparison appeared first on Analytics Vidhya.

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KDnuggets Top Posts for January 2023: SQL and Python Interview Questions for Data Analysts

KDnuggets

SQL and Python Interview Questions for Data Analysts • 5 SQL Visualization Tools for Data Engineers • 5 Free Tools For Detecting ChatGPT, GPT3, and GPT2 • Top Free Resources To Learn ChatGPT • Free TensorFlow 2.0

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Ultimate Collection of 50 Free Courses for Mastering Data Science

KDnuggets

The collection includes free courses on Python, SQL, Data Analytics, Business Intelligence, Data Engineering, Machine Learning, Deep Learning, Generative AI, and MLOps.

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Top Posts February 20-26: 5 SQL Visualization Tools for Data Engineers

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5 SQL Visualization Tools for Data Engineers • Free TensorFlow 2.0 Complete Course • The Importance of Probability in Data Science • 4 Ways to Rename Pandas Columns • 5 Statistical Paradoxes Data Scientists Should Know