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Data Engineering for Streaming Data on GCP

Analytics Vidhya

Introduction Companies can access a large pool of data in the modern business environment, and using this data in real-time may produce insightful results that can spur corporate success. Real-time dashboards such as GCP provide strong data visualization and actionable information for decision-makers.

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Interactive Exploratory Data Analysis On Petabyte Scale Data Sets With Arkouda

Data Engineering Podcast

Summary Exploratory data analysis works best when the feedback loop is fast and iterative. The Arkouda project is a Python interface built on top of the Chapel compiler to bring back those interactive speeds for exploratory analysis on horizontally scalable compute that parallelizes operations on large volumes of data.

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Data Engineering Weekly #167

Data Engineering Weekly

Discover how a universal semantic layer is transforming modern business intelligence, making data more accessible and reliable for organizations striving for informed business decisions. Large Language Models: Turning messy data into surprisingly coherent nonsense since 2023. High-quality data is the cornerstone of LLM.

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Data Engineer vs Data Analyst: Key Differences and Similarities

Knowledge Hut

Did you know that data is now an essential component of modern business operations? 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.

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Data Engineering Weekly #170

Data Engineering Weekly

In an ideal world, data should be thought of as “borrowed” (possibly unpermitted) and thus can be “returned,” and unlearning should enable such revocation. link] LinkedIn: LakeChime - A Data Trigger Service for Modern Data Lakes LinkedIn points out two critical flaws in a partitioned approach to data management.

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How to Become a Data Engineer in 2024?

Knowledge Hut

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. What is Data Science? What are the roles and responsibilities of a Data Engineer? What is Data Science?

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GPT-based data engineering accelerators

RandomTrees

GPT-based data engineering accelerators make the working of data more accessible. These accelerators use GPT models to do data tasks faster, fix any issues, and save a lot of time. GPT models change data in simple language and also provide summaries and explanations. One can rely on this information.