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Published February 8, 2024

Data & Metadata

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Edited By:

Editorial Salud, Ciencia y Tecnología

Title:

Data and Metadata

ISSN-L: 2953-4917

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2024-03-30 Original
Social Capital in Small Industrial Firms and Its Link with Innovation

By Edith Georgina Surdez Pérez, María del Carmen Sandoval Caraveo, Maribel Flores Galicia

Introduction: Social Capital in organizations is an intangible asset that represents the favourable relationships that exist between work teams, within an organization and externally, to different interest groups.
Objective: This study examined the link between internal relational social capital (RSC) and external RSC with innovation in small industrial firms in Tabasco, Mexico. There was also an inquiry into how much internal RSC and external RSC explain innovation.
Methods: The design was nonexperimental, cross-sectional, descriptive, correlational, and explanatory. Linear regression analysis was used.
Results: Significant positive relationships was identified between internal RSC and external RSC and innovation. The internal RSC and external RSC contributed significantly to the explaining of innovation. Areas of opportunity were identified for these firms in process design and formal research activities for new raw materials, production procedures and patent generation. Conclusion: To promote innovation, managers of small industrial companies must continue to establish strategies and practices to strengthen RSC.

2024-02-08 Reviews
Overview on Data Ingestion and Schema Matching

By Oumaima El Haddadi, Max Chevalier, Bernard Dousset, Ahmad El Allaoui, Anass El Haddadi, Olivier Teste

This overview traced the evolution of data management, transitioning from traditional ETL processes to addressing contemporary challenges in Big Data, with a particular emphasis on data ingestion and schema matching. It explored the classification of data ingestion into batch, real-time, and hybrid processing, underscoring the challenges associated with data quality and heterogeneity. Central to the discussion was the role of schema mapping in data alignment, proving indispensable for linking diverse data sources. Recent advancements, notably the adoption of machine learning techniques, were significantly reshaping the landscape. The paper also addressed current challenges, including the integration of new technologies and the necessity for effective schema matching solutions, highlighting the continuously evolving nature of schema matching in the context of Big Data.

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