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25 SQL tips to level up your data engineering skills

Start Data Engineering

Introduction Setup SQL tips 1. Handy functions for common data processing scenarios 1.1. STRUCT data types are sorted based on their keys from left to right 1.4. Need to filter on WINDOW function without CTE/Subquery use QUALIFY 1.2. Need the first/last row in a partition, use DISTINCT ON 1.3.

SQL 130
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Tackling Real Time Streaming Data With SQL Using RisingWave

Data Engineering Podcast

Summary Stream processing systems have long been built with a code-first design, adding SQL as a layer on top of the existing framework. RisingWave is a database engine that was created specifically for stream processing, with S3 as the storage layer. Want to see Starburst in action?

SQL 173
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Seamless SQL And Python Transformations For Data Engineers And Analysts With SQLMesh

Data Engineering Podcast

Summary Data transformation is a key activity for all of the organizational roles that interact with data. Because of its importance and outsized impact on what is possible for downstream data consumers it is critical that everyone is able to collaborate seamlessly. Can you describe what SQLMesh is and the story behind it?

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How to improve at SQL as a data engineer

Start Data Engineering

SQL skills 2.1. Data modeling 2.1.1. Data storage 2.2. Data transformation 2.2.1. Data pipeline 2.4. Data analytics 3. Introduction SQL is the bread and butter of data engineering. Introduction 2. Gathering requirements 2.1.2. Exploration 2.1.3. Modeling 2.1.4. Query planner 2.2.3.

SQL 130
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Data Engineering Weekly #181

Data Engineering Weekly

Editor’s Note: A New Series on Data Engineering Tools Evaluation There are plenty of data tools and vendors in the industry. Data Engineering Weekly is launching a new series on software evaluation focused on data engineering to better guide data engineering leaders in evaluating data tools.

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Data Engineering Weekly #182

Data Engineering Weekly

link] Chip Huyan: Building A Generative AI Platform We can’t deny that Gen-AI is becoming an integral part of product strategy, pushing the need for platform engineering. Switching from Apache Spark to Ray improves compact 12X larger datasets than Apache Spark, improves cost efficiency by 91%, and processes 13X more data per hour.

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Why Data Analysts And Engineers Make Great Consultants

Seattle Data Guy

Many data engineers and analysts don’t realize how valuable the knowledge they have is. They’ve spent hours upon hours learning SQL, Python, how to properly analyze data, build data warehouses, and understand the differences between eight different ETL solutions.