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Analytics databases

Dataconomy

Analytics databases, also referred to as analytical databases, are specialized systems designed specifically for analyzing large volumes of historical data. Definition and functionality The primary purpose of analytics databases is to provide a platform for businesses to efficiently analyze historical metrics.

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Responsible AI at Scale: Women in Big Data & LinkedIn

Women in Big Data

Women in Big Data and LinkedIn hosted an empowering event The Responsible AI at Scale in LinkedIn HQ in Sunnyvale, CA on March 13 th , 2025, for people passionate about ethics, transparency and shaping the AI technologies of the future. I cant wait for the next Women in Big Data event!

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Ask HN: Who wants to be hired? (July 2025)

Hacker News

However there is definitely something new and profound about llms and diffusion models. id=44437019 I've been upskilling in machine learning using Math Academy's Mathematics for Machine Learning (top 5 in the top league last week), Andrew Ng's course and a handful of other resources.

Python 69
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Object-centric Process Mining on Data Mesh Architectures

Data Science Blog

New big data architectures and, above all, data sharing concepts such as Data Mesh are ideal for creating a common database for many data products and applications. The Event Log Data Model for Process Mining Process Mining as an analytical system can very well be imagined as an iceberg.

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Deciphering The Seldom Discussed Differences Between Data Mining and Data Science

Smart Data Collective

The Bureau of Labor Statistics estimates that the number of data scientists will increase from 32,700 to 37,700 between 2019 and 2029. Unfortunately, despite the growing interest in big data careers, many people don’t know how to pursue them properly. Definition: Data Mining vs Data Science.

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Business Intelligence for Fairs, Congresses and Exhibitions

Smart Data Collective

Advancement in big data technology has made the world of business even more competitive. The proper use of business intelligence and analytical data is what drives big brands in a competitive market. Main features include the ability to access and operationalize data through the LookML library.

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Data warehouse architecture

Dataconomy

Data warehouse architecture The data warehouse architecture is a very critical concept regarding big data. It could be defined as the layout and design of a data warehouse, which at other times could act as a central repository for all organization’s data.