Remove Data Engineer Remove Data Pipeline Remove ETL Tools
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Data Engineer vs Data Analyst: Key Differences and Similarities

Knowledge Hut

With companies increasingly relying on data-driven insights to make informed decisions, there has never been a greater need for skilled specialists who can manage and evaluate vast amounts of data. The roles of data analyst and data engineer have emerged as two of the most in-demand professions in today's job market.

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Data Scientist vs Data Engineer: Differences and Why You Need Both

AltexSoft

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

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A Notebook is all I want or Don't

Data Engineering Weekly

It is hard to build a data-driven culture across the organization if it takes months instead of hours to build data assets. The current mode of data pipeline development requires expert data engineers, whereas all citizen developers use notebook-style development. How are we trying to solve this problem?

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Data Pipeline vs. ETL: Which Delivers More Value?

Ascend.io

In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Fast forward to the present day, and we now have data pipelines. However, they are not just an upgraded version of ETL. Yet, the technical problem is the same.

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Data Engineering Weekly #153

Data Engineering Weekly

Lorin Hochstein: “Human error” means they don’t understand how the system worked The post is not directly related to Data Engineering but system operations in general. It is great to see an internal tech talk with a series focus on data engineering. Visit rudderstack.com to learn more.

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An Introduction To Data And Analytics Engineering For Non-Programmers

Data Engineering Podcast

In this episode Brian McMillan shares his work on the book "Building Data Products" and how he is working to educate business users and data professionals about the combination of technical, economical, and business considerations that need to be blended for these projects to succeed.

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Data Pipeline with Airflow and AWS Tools (S3, Lambda & Glue)

Towards Data Science

Today’s post follows the same philosophy: fitting local and cloud pieces together to build a data pipeline. And, when it comes to data engineering solutions, it’s no different: They have databases, ETL tools, streaming platforms, and so on — a set of tools that makes our life easier (as long as you pay for them).