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30 Best Data Science Books to Read in 2023

Analytics Vidhya

Introduction Data science has taken over all economic sectors in recent times. To achieve maximum efficiency, every company strives to use various data at every stage of its operations.

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Data Science Blogathon 30th Edition- Women in Data Science

Analytics Vidhya

The Biggest Data Science Blogathon is now live! Martin Uzochukwu Ugwu Analytics Vidhya is back with the largest data-sharing knowledge competition- The Data Science Blogathon. Knowledge is power. Sharing knowledge is the key to unlocking that power.”―

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5 Big Data Challenges in 2024

Knowledge Hut

The year 2024 saw some enthralling changes in volume and variety of data across businesses worldwide. The surge in data generation is only going to continue. Foresighted enterprises are the ones who will be able to leverage this data for maximum profitability through data processing and handling techniques.

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Who is a Big Data Engineer? Skills, Responsibilities, Salary

Knowledge Hut

Wondering what is a big data engineer? As the name suggests, Big Data is associated with ‘bigdata, which hints at something big in the context of data. Big data forms one of the pillars of data science. Who Is a Big Data Engineer?

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Who is a Big Data Engineer? Skills, Responsibilities, Salary

Knowledge Hut

Wondering what is a big data engineer? As the name suggests, Big Data is associated with ‘bigdata, which hints at something big in the context of data. Big data forms one of the pillars of data science. Who Is a Big Data Engineer?

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Big Data Technologies that Everyone Should Know in 2024

Knowledge Hut

Big data in information technology is used to improve operations, provide better customer service, develop customized marketing campaigns, and take other actions to increase revenue and profits. It is especially true in the world of big data. It is especially true in the world of big data.

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GPT and LLMs from a Data Engineering Perspective

Jesse Anderson

There has been quite a bit of writing covering GPT and LLMs from data science and business perspectives. I haven’t seen much from the data engineering side. Let me share my perspective, having been in data and AI for a while and using LLMs before they became popular. How can we use LLMs in data engineering?