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7 Steps to Mastering Data Engineering

KDnuggets

The only data engineering roadmap you need for an introduction to concepts, tools, and techniques to collect, store, transform, analyze, and model data.

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What Data Engineers Really Do?

Analytics Vidhya

In a data-driven world, behind-the-scenes heroes like data engineers play a crucial role in ensuring smooth data flow. A data engineer investigates the issue, identifies a glitch in the e-commerce platform’s data funnel, and swiftly implements seamless data pipelines.

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Top 20 Data Engineering Project Ideas [With Source Code]

Analytics Vidhya

Data engineering plays a pivotal role in the vast data ecosystem by collecting, transforming, and delivering data essential for analytics, reporting, and machine learning. Aspiring data engineers often seek real-world projects to gain hands-on experience and showcase their expertise.

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How To Hire Junior Data Engineers

Seattle Data Guy

With all the recent data events I have put together I inevitably run into new data engineers who are either finishing up college or looking to transition into a data engineer or data scientist position. In fact I have talked to several newly graduated engineers who are struggling to find work.

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Mr. Pavan’s Data Engineering Journey Drives Business Success

Analytics Vidhya

He is an experienced data engineer with a passion for problem-solving and a drive for continuous growth. Thus, providing valuable insights into the field of data engineering. Introduction We had an amazing opportunity to learn from Mr. Pavan.

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Data Engineering for Streaming Data on GCP

Analytics Vidhya

Real-time dashboards such as GCP provide strong data visualization and actionable information for decision-makers. Nevertheless, setting up a streaming data pipeline to power such dashboards may […] The post Data Engineering for Streaming Data on GCP appeared first on Analytics Vidhya.

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Modern Data Engineering with MAGE: Empowering Efficient Data Processing

Analytics Vidhya

Introduction In today’s data-driven world, organizations across industries are dealing with massive volumes of data, complex pipelines, and the need for efficient data processing.