{"id":14729,"date":"2026-04-16T13:46:59","date_gmt":"2026-04-16T11:46:59","guid":{"rendered":"https:\/\/blog.structuralia.com\/?p=14729"},"modified":"2026-04-16T14:00:26","modified_gmt":"2026-04-16T12:00:26","slug":"datasets","status":"publish","type":"post","link":"https:\/\/blog.structuralia.com\/en\/datasets","title":{"rendered":"Datasets"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_84 counter-hierarchy ez-toc-counter ez-toc-white ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\"><\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Contents\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/blog.structuralia.com\/en\/datasets\/#%C2%BFQue_son_los_datasets\" >What are datasets?<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/blog.structuralia.com\/en\/datasets\/#Diferencia_entre_dataset_y_dataframe\" >Difference Between a Dataset and a DataFrame<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/blog.structuralia.com\/en\/datasets\/#Tipos_de_Datasets\" >Types of Datasets<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/blog.structuralia.com\/en\/datasets\/#Datasets_estructurados\" >Structured Datasets<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/blog.structuralia.com\/en\/datasets\/#Datasets_no_estructurados\" >Unstructured datasets<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/blog.structuralia.com\/en\/datasets\/#Dataset_semiestructurado\" >Semi-structured dataset<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/blog.structuralia.com\/en\/datasets\/#Importancia_de_los_datasets\" >The Importance of Datasets<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/blog.structuralia.com\/en\/datasets\/#%C2%BFDonde_localizar_los_datasets\" >Where can I find the datasets?<\/a><\/li><\/ul><\/nav><\/div>\n\n<p class=\"wp-block-paragraph\">A <strong>dataset <\/strong>is a logical unit of persistent, structured information that serves as the basis for the analysis, experimentation, and training of algorithmic models. The <strong>dataset<\/strong> It serves as a historical and real-time record of the critical variables that enable an effective transition toward the digitization of infrastructure. This information is the result of a technical curation process that gives purpose to every stored bit.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"%C2%BFQue_son_los_datasets\"><\/span>What are datasets?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The\u00a0<strong>datasets<\/strong>\u00a0They are organized collections of curated information that enable data scientists to perform high-impact analyses. Unlike the\u00a0<em><a href=\"https:\/\/blog.structuralia.com\/en\/big-data-en-las-empresas\/\">big data<\/a><\/em>\u00a0Unlike raw data\u2014which is typically a chaotic jumble of records\u2014a dataset involves a predefined analytical purpose and a defined schema. It is the minimum viable infrastructure that enables the transformation of isolated facts into actionable knowledge for strategic decision-making in highly technically complex projects.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Financial Optimization:<\/strong>\u00a0It is establishing itself as the key asset for optimizing budgets and reducing operational risks throughout the region.<\/li>\n\n\n\n<li><strong>Global Interoperability:<\/strong>\u00a0It ensures technical compatibility in accordance with international standards, allowing a technical office in Madrid and a construction company in Mexico to share strength parameters without any discrepancies.<\/li>\n\n\n\n<li><strong>Structural Safety:<\/strong>\u00a0supports failure prediction by normalizing critical data.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"907\" src=\"https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/que-es-un-dataset-1024x907.png\" alt=\"\" class=\"wp-image-14735\" style=\"aspect-ratio:1.1290177904021528;width:485px;height:auto\" srcset=\"https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/que-es-un-dataset-1024x907.png 1024w, https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/que-es-un-dataset-300x266.png 300w, https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/que-es-un-dataset-768x680.png 768w, https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/que-es-un-dataset-1536x1360.png 1536w, https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/que-es-un-dataset-2048x1814.png 2048w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Diferencia_entre_dataset_y_dataframe\"><\/span>Difference Between a Dataset and a DataFrame<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The\u00a0<strong>dataset<\/strong>\u00a0is the physical data stored permanently on servers or in the cloud, generally in formats optimized for\u00a0<em>big data<\/em>. It is the original, immutable, and secure source that guarantees the integrity of historical technical records against any processing errors or human error during the active analysis phase.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Logical Abstraction:<\/strong>\u00a0the\u00a0<strong>dataframe<\/strong>\u00a0It is the representation of the dataset that is actively loaded into RAM for processing.<\/li>\n\n\n\n<li><strong>Dynamic Calculation:<\/strong>\u00a0It allows engineers to perform matrix operations and filtering in real time while the source remains at rest.<\/li>\n\n\n\n<li><strong>Ephemeral Nature:<\/strong>\u00a0Unlike persistent storage, the dataframe is destroyed at the end of the session to protect the integrity of the original database.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Tipos_de_Datasets\"><\/span>Types of Datasets<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The classification of the&nbsp;<strong>datasets<\/strong>&nbsp;determines the tools for&nbsp;<strong>data analysis<\/strong>&nbsp;required and the associated processing cost. In engineering, the&nbsp;<strong>dataset type<\/strong>&nbsp;guides specialists toward the optimal storage architecture, whether through traditional SQL systems or modern data lakes. This taxonomy allows information to be organized in a way that maximizes its operational utility and facilitates the integration of new variables throughout the project lifecycle.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Datasets_estructurados\"><\/span>Structured Datasets<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The <strong>structured datasets<\/strong> are the foundation of organized technical management; they are characterized by a rigid relational model or <em>Schema-on-write<\/em>. In this <strong>dataset type<\/strong>, each record fits into a <strong>table format<\/strong> with predefined columns and rows, ensuring complete consistency. It is the standard format in ERP systems and SQL databases used for cost control, construction site inventories, and laboratory test records, where numerical accuracy is non-negotiable.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Its greatest operational advantage is the speed of queries and the ease with which it can perform massive mathematical operations almost instantly. By working with fixed data types, data analysis algorithms can identify trends in historical performance without technical friction. In regional engineering projects, this structure is vital for ensuring that financial decision-making is based on robust and comparable metrics.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Datasets_no_estructurados\"><\/span>Unstructured datasets<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Unstructured datasets account for the largest volume of information generated in modern engineering, although their technical application is more complex. These are binary files without a defined schema, such as point clouds <strong>LiDAR<\/strong> (Light Detection and Ranging), inspection videos, or field audio recordings. For this dataset to be useful, it requires layers of artificial intelligence that translate the pixels or signals into structured metrics that an engineer can interpret.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Integrating this information into big data strategies makes it possible to monitor the actual progress of a construction project against the theoretical schedule with a level of accuracy that is impossible to achieve through manual reports. The technical analysis of unstructured data is what enables the detection of critical deviations in real time, increasing responsiveness and drastically reducing cost overruns caused by unforeseen execution errors.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Dataset_semiestructurado\"><\/span>Semi-structured dataset<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The <strong>semi-structured dataset<\/strong> It is the balance between tabular rigidity and the chaos of binary formats. This data uses hierarchical tags to organize information, with JSON files and models being <strong>BIM IFC<\/strong> the most powerful examples. This structure allows each structural element to contain a wealth of technical metadata that facilitates the lifecycle management of any infrastructure.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This flexibility is the key to technical compatibility in large-scale STEM projects involving multiple software platforms.  A file&nbsp;<strong>IFC<\/strong>&nbsp;allows material, supplier, and maintenance data to be integrated with the geometry without corrupting the&nbsp;<strong>database<\/strong>&nbsp;General. Mastering this&nbsp;<strong>dataset type<\/strong>&nbsp;asserts that the&nbsp;<strong>decision-making<\/strong>&nbsp;the technology is seamless and that the information remains accessible decades after the initial construction.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img decoding=\"async\" width=\"1024\" height=\"907\" src=\"https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/tipos-de-datasets-1024x907.png\" alt=\"\" class=\"wp-image-14734\" style=\"width:500px;height:auto\" srcset=\"https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/tipos-de-datasets-1024x907.png 1024w, https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/tipos-de-datasets-300x266.png 300w, https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/tipos-de-datasets-768x680.png 768w, https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/tipos-de-datasets-1536x1360.png 1536w, https:\/\/blog.structuralia.com\/wp-content\/uploads\/2026\/04\/tipos-de-datasets-2048x1814.png 2048w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Importancia_de_los_datasets\"><\/span>The Importance of Datasets<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The usefulness of a\u00a0<strong>dataset<\/strong>\u00a0The benefits are immediately apparent, as they eliminate unproductive hours spent searching for and validating scattered information. Having clean data makes it possible to identify operational bottlenecks in a matter of minutes, transforming the workflow from a reactive to a proactive approach. This efficiency frees up capacity for higher-value-added tasks, reducing calculation errors.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In the long term, the strategic accumulation of this data completely redefines infrastructure performance and the very nature of technical professions. The transition to predictive maintenance allows structures to \u00abspeak,\u00bb warning of fatigue before a catastrophic failure occurs. This shift moves the engineer\u2019s role from manual supervision to the orchestration of intelligent systems, where professional success will depend on the ability to interpret large datasets. Companies that invest today in the quality of their <strong>dataset<\/strong> will achieve levels of performance and scalability that are unattainable for traditional management models.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"%C2%BFDonde_localizar_los_datasets\"><\/span>Where can I find the datasets?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The difference between a rigorous analysis and a simple theoretical exercise lies in the source. The first step is to map the available data catalogs according to their operational usefulness and origin:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Kaggle (The Training Ground):<\/strong>&nbsp;A global leader in training and&nbsp;<em>benchmarking<\/em>&nbsp;algorithms. It is ideal for validating hypotheses against internationally curated data before applying them to real-world environments.<\/li>\n\n\n\n<li><strong>Google Dataset Search (The Universal Search Engine):<\/strong>&nbsp;It indexes millions of academic and technical datasets under a unified metadata standard, facilitating access to studies from prestigious universities.<\/li>\n\n\n\n<li><strong>IEEE DataPort (The Engineering Standard):<\/strong>&nbsp;A highly reliable repository offering academically validated datasets for electrical, electronic, and civil engineering projects.<\/li>\n\n\n\n<li><strong>Open Data Portals (The Reality on the Ground):<\/strong>&nbsp;Official resources of inestimable value for analyzing the local context and managing public works projects, including platforms such as:\n<ul class=\"wp-block-list\">\n<li><strong>datos.gob.es<\/strong>&nbsp;(Spain): Large-scale datasets on cartography, infrastructure, and services from the IGN.<\/li>\n\n\n\n<li><strong>datos.gov.co<\/strong>&nbsp;(Colombia): Key data for understanding the country's physical and topographical characteristics.<\/li>\n\n\n\n<li><strong>datos.gob.mx<\/strong>&nbsp;(Mexico): A critical resource for the analysis of infrastructure and social development.<\/li>\n<\/ul>\n<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>Un dataset es una unidad l\u00f3gica de informaci\u00f3n persistente y estructurada que sirve como base para el an\u00e1lisis, la experimentaci\u00f3n y el entrenamiento de modelos algor\u00edtmicos. El conjunto de datos constituye el registro hist\u00f3rico y en tiempo real de las variables cr\u00edticas que permiten la transici\u00f3n efectiva hacia la digitalizaci\u00f3n de infraestructuras. Esta pieza de [&hellip;]<\/p>\n","protected":false},"author":6,"featured_media":14732,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_ayudawp_aiss_exclude":false,"_ayudawp_aiss_summary":"","_ayudawp_aiss_summary_provider":"","_ayudawp_aiss_summary_hash":"","footnotes":""},"categories":[267],"tags":[],"class_list":["post-14729","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-educacion-stem-ingenieria"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Datasets: qu\u00e9 son, tipos y c\u00f3mo utilizarlos | Structuralia<\/title>\n<meta name=\"description\" content=\"Sin datos de calidad no hay IA. 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