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Predicting Employee Attrition using Orange(.ows) Visual Programming Software

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. ows) Visual Programming Software appeared first on Analytics Vidhya. Introduction If you want to know – How to use MACHINE LEARNING. The post Predicting Employee Attrition using Orange(.ows)

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Have we reached the end of ‘too expensive’ for enterprise software?

CIO Business Intelligence

Generative artificial intelligence ( genAI ) and in particular large language models ( LLMs ) are changing the way companies develop and deliver software. The future will be characterized by more in-depth AI capabilities that are seamlessly woven into software products without being apparent to end users. An overview.

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Everything About Apache Hive and its Advantages!

Analytics Vidhya

Hive, founded by Facebook and later Apache, is a data storage system created for the purpose of analyzing structured data. Operating under an open-source data platform called Hadoop, Apache Hive is a software application released in 2010 (October). What is Apache Hive? Introduced to […].

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AI agents: The next stage in the evolution of enterprise AI

CIO Business Intelligence

Software providers are already bringing corresponding applications to market. Ready-made AI agents offer decisive advantages: Once implemented, they provide turnkey performance, are supported by professional software developers and enable rapid deployment. Data layer: Divided into unstructured and structured data.

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CIOs contend with gen AI growing pains

CIO Business Intelligence

Soumya Seetharam, CDIO at Corning, said the manufacturer has been on its data journey for a few years, with more than 70% of its business transaction data being ingested into a data platform. But that’s only structured data, she emphasized.

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Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

In life sciences, simple statistical software can analyze patient data. While this process is complex and data-intensive, it relies on structured data and established statistical methods. Use traditional tools for structured data and reserve LLMs for the truly complex stuff. You get the picture.

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When is data too clean to be useful for enterprise AI?

CIO Business Intelligence

Good data governance has always involved dealing with errors and inconsistencies in datasets, as well as indexing and classifying that structured data by removing duplicates, correcting typos, standardizing and validating the format and type of data, and augmenting incomplete information or detecting unusual and impossible variations in the data.