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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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Guide for Interview Questions for SQL

Analytics Vidhya

Introduction on SQL Questions This blog consists of various topics of SQL and their explanation with answers. There are 12 theoretical questions that are frequently asked in interviews for freshers level and below, there are 15 MCQs related to SQL Questions for practice. […].

SQL 247
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Window Functions – A Must-Know Topic for Data Engineers and Data Scientists

Analytics Vidhya

Overview Get to know about the SQL Window Functions Understand what the Aggregate functions lack and why we need Window Functions in SQL. The post Window Functions – A Must-Know Topic for Data Engineers and Data Scientists appeared first on Analytics Vidhya.

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SQL in DjangoORM – With Example Code Implementation

Analytics Vidhya

The post SQL in DjangoORM – With Example Code Implementation appeared first on Analytics Vidhya.

SQL 212
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8 Best Books for SQL [Beginners and Advanced Learners]

Pickl AI

Structured Query Language, or SQL, is a programming language used to communicate with databases. It means that SQL is the language used for storing, retrieving and manipulating data from relational databases. If you’re an aspiring Data Scientist, you must know that SQL is one of the most crucial skills needed to become an expert.

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PostgreSQL 16 Bi-Directional Logical Replication

Hacker News

Introduction In this blog, we’ll be going over some more advanced topics new in Postgres 16. Having some experience with Linux, Postgres, and SQL is necessary as we’ll not only be going over these new features but also how to implement them. … Read more

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Real-Time Sentiment Analysis with Kafka and PySpark

Towards AI

Operating on a publish-subscribe messaging model, where producers are tasked with publishing data to topics while consumers subscribe to these topics to process the data. Let's take a better look at the key components: Producers: They publish/push records to Kafka topics. Next, we run an SQL query to extract the data.