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Snowflake’s New Python API Empowers Data Engineers to Build Modern Data Pipelines with Ease

Snowflake

Yet while SQL applications have long served as the gateway to access and manage data, Python has become the language of choice for most data teams, creating a disconnect. Recognizing this shift, Snowflake is taking a Python-first approach to bridge the gap and help users leverage the power of both worlds.

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How to learn data engineering

Christophe Blefari

Learn data engineering, all the references ( credits ) This is a special edition of the Data News. But right now I'm in holidays finishing a hiking week in Corsica 🥾 So I wrote this special edition about: how to learn data engineering in 2024. Who are the data engineers?

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Data Engineering Weekly #173

Data Engineering Weekly

[link] Meta: Composable data management at Meta Meta writes about its transition to a composable data management system to improve interoperability, reusability, and engineering efficiency. It is a long standing question on people wondering In what situations should you use SQL instead of Pandas as a data scientist?

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Python for Data Engineering

Ascend.io

The rise of data-intensive operations has positioned data engineering at the core of today’s organizations. As the demand to efficiently collect, process, and store data increases, data engineers have started to rely on Python to meet this escalating demand. Why Python for Data Engineering?

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DuckDB vs Polars for Data Engineering.

Confessions of a Data Guy

I was wondering the other day … since Polars now has a SQL context and is getting more popular by the day, do I need DuckDB anymore? You might think […] The post DuckDB vs Polars for Data Engineering. appeared first on Confessions of a Data Guy. These two tools are hot.

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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.

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Brief History of Data Engineering

Jesse Anderson

They were the first companies to commercialize open source big data technologies and pushed the marketing and commercialization of Hadoop. Hadoop was hard to program, and Apache Hive came along in 2010 to add SQL. With an immutable file system like HDFS, we needed scalable databases to read and write data randomly.