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<p>As a data science consultancy, Jumping Rivers are already known for offering help and training to clients in all things data. But did you know that we also organise free, in-person data science meetups?<br />
In this post we will talk through the typic...</p></div>
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<strong>Continue reading</strong>: <a href="https://www.r-bloggers.com/2025/11/get-involved-in-the-data-science-community-at-our-free-meetups/">Get Involved in the Data Science Community at our Free Meetups</a>

تُعرف شركة Jumping Rivers، وهي استشارات في علم البيانات، بتقديم المساعدة والتدريب في جميع الأمور المتعلقة بالبيانات. كما أنهم ينظمون لقاءات مجانية حضورية في علم البيانات لإشراك المجتمع. توفر هذه اللقاءات فرصة للتواصل وتبادل المعرفة بين عشاق علم البيانات.

Jumping Rivers, una consultoría de ciencia de datos, es conocida por ofrecer ayuda y capacitación en temas relacionados con los datos. También organizan encuentros gratuitos en persona para involucrar a la comunidad. Estos encuentros brindan una oportunidad para el networking y el intercambio de conocimientos entre entusiastas de la ciencia de datos.

Jumping Rivers, une société de conseil en science des données, est reconnue pour son aide et sa formation dans le domaine des données. Ils organisent également des rencontres gratuites en personne pour impliquer la communauté. Ces rencontres offrent une occasion de réseautage et de partage de connaissances entre passionnés de science des données.

Jumping Rivers, a data science consultancy, is known for providing assistance and training in data-related matters. They also organize free, in-person data science meetups to engage the community. These meetups offer an opportunity for networking and knowledge sharing among data science enthusiasts.

Get Involved in the Data Science Community at our Free Meetups

arXiv:2506.11010v2 Announce Type: replace-cross 
Abstract: This manuscript provides a systemic and data-centric view of what we term essential data science, as a natural ecosystem with challenges and missions stemming from the fusion of data universe with its multiple combinations of the 5D complexities (data structure, domain, cardinality, causality, and ethics) with the phases of the data life cycle. Data agents perform tasks driven by specific goals. The data scientist is an abstract entity that comes from the logical organization of data agents with their actions. Data scientists face challenges that are defined according to the missions. We define specific discipline-induced data science, which in turn allows for the definition of pan-data science, a natural ecosystem that integrates specific disciplines with the essential data science. We semantically split the essential data science into computational, and foundational. By formalizing this ecosystemic view, we contribute a general-purpose, fusion-oriented architecture for integrating heterogeneous knowledge, agents, and workflows-relevant to a wide range of disciplines and high-impact applications.

يقدم مخطوط حديث نُشر على arXiv رؤية نظامية ومركزة على البيانات لعلم البيانات الأساسي، حيث يتم تصوره كنظام بيئي طبيعي يدمج تعقيدات متعددة ومراحل دورة حياة البيانات. يركز العمل على دور وكلاء البيانات والتحديات التي يواجهها علماء البيانات لتحقيق أهداف محددة.

Un manuscrito reciente publicado en arXiv presenta una visión sistémica y centrada en los datos de la ciencia de datos esencial, conceptualizándola como un ecosistema natural que integra diversas complejidades y fases del ciclo de vida de los datos. El trabajo enfatiza el papel de los agentes de datos y los desafíos que enfrentan los científicos de datos para lograr objetivos específicos.

Un récent manuscrit publié sur arXiv présente une vue systémique et centrée sur les données de la science des données essentielle, la conceptualisant comme un écosystème naturel qui intègre diverses complexités et phases du cycle de vie des données. Le travail met l'accent sur le rôle des agents de données et les défis auxquels font face les scientifiques des données pour atteindre des objectifs spécifiques.

A recent manuscript published on arXiv presents a systemic and data-centric view of essential data science, conceptualizing it as a natural ecosystem that integrates various complexities and phases of the data life cycle. The work emphasizes the role of data agents and the challenges faced by data scientists in achieving specific goals.

Data Science: a Natural Ecosystem

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