KDnuggets

JANUARY 7, 2020

An estimated 8,650% growth of the volume of Data to 175 zetabytes from 2010 to 2025 has created an enormous need for Data Engineers to build an organization's big data platform to be fast, efficient and scalable.

Data Engineering 400

Data Engineering Data Engineering Data Engineer Data Engineering 400

Flipboard

JUNE 16, 2025

Getting Started: You Don’t Need Expensive Hardware Let me get this clear, you don’t necessarily need an expensive cloud computing setup to win ML competitions (unless the dataset is too big to fit locally). The dataset for this competition contained 77 features and 443k rows, which is not small by any means.

Machine Learning 126

Machine Learning Machine Learning Data Science Artificial Intelligence 126

O'Reilly Media

NOVEMBER 26, 2024

Entirely new paradigms rise quickly: cloud computing, data engineering, machine learning engineering, mobile development, and large language models. To further complicate things, topics like cloud computing, software operations, and even AI don’t fit nicely within a university IT department.

Cloud Computing 115

Cloud Computing AWS Azure Machine Learning 115

Applied Data Science

AUGUST 2, 2021

Team Building the right data science team is complex. With a range of role types available, how do you find the perfect balance of Data Scientists , Data Engineers and Data Analysts to include in your team? The Data Engineer Not everyone working on a data science project is a data scientist.

Data Science 130

Data Science Data Scientist ML ML 130

Precisely

MARCH 20, 2025

When I joined the workforce, desktop computing, the Blackberry, email, and the dot-com boom were the catalysts that disrupted workplace norms. Today, we’re navigating the complexities of AI, machine learning, and cloud computing. And the challenge only grows as more data sources are added. That insight is critical.

Cloud Computing 69

Cloud Computing Data Analyst Data Scientist Artificial Intelligence 69

Towards AI

FEBRUARY 11, 2025

2020) Scaling Laws for Neural Language Models [link] First formal study documenting empirical scaling laws Published by OpenAI The Data Quality Conundrum Not all data is created equal. This method not only expands the available training data but also enhances model efficiency and problem-solving abilities.

Data Quality 53

Data Quality Data Engineering Data Engineering Data Engineer 53

Alation

OCTOBER 12, 2021

One may define enterprise data analytics as the ability to find, understand, analyze, and trust data to drive strategy and decision-making. Enterprise data analytics integrates data, business, and analytics disciplines, including: Data management. Data engineering. Evaluate and monitor data quality.

Analytics 52

Analytics Analytics Data Governance DataOps 52