Desarrollo de una plataforma de gestión de datos de clientes como herramienta para marketing dirigido por datos
| dc.contributor.advisor | Romero Alvarez, Fran Ernesto | |
| dc.contributor.author | Romero Mateus, Carlos Fernando | |
| dc.contributor.author | Castellano Correa, Rasbel Eduardo | |
| dc.contributor.author | Santos Cely, Omar Alejandro | |
| dc.date.accessioned | 2025-11-19T16:19:58Z | |
| dc.date.issued | 2025-11 | |
| dc.description.abstract | Prodigy Media S.A.S., agencia dedicada a operar y controlar campañas de marketing digital, sufría datos dispersos, reportes manuales y definiciones inconsistentes entre áreas, lo que generaba demoras, retrabajo y cifras contradictorias. Para resolverlo se diseñó e implementó una Plataforma de Datos de Clientes (CDP) en Google Cloud que centraliza la captura, estandarización y consumo analítico bajo el modelo Medallion (Bronze–Silver–Gold). La ingesta se automatiza con Cloud Scheduler + Cloud Run; Pub/Sub desacopla productores y consumidores; y Dataflow, en streaming, valida reglas de calidad, estandariza al esquema canónico y publica en BigQuery con gobierno y seguridad aplicados en tránsito. El consumo ocurre en Looker Studio mediante vistas versionadas con metadatos de “última actualización”, evitando cálculos en BI y asegurando una única interpretación de métricas. Sobre los datos consolidados se entrenó en BigQuery ML un agrupamiento no supervisado (k=4) que perfila campañas por gasto y rendimiento, apoyando decisiones tácticas de optimización y asignación de presupuesto. La solución reduce reconciliaciones en Excel, acorta la latencia entre evento y decisión, mejora la trazabilidad y habilita auditoría técnica y funcional. Como proyección, la CDP queda preparada para incorporar fuentes reales, ampliar controles de calidad y conectar con plataformas de activación para cerrar el ciclo dato–análisis–acción. | |
| dc.description.abstractenglish | Prodigy Media S.A.S., an agency dedicated to operating and monitoring digital marketing campaigns, suffered from scattered data, manual reporting, and inconsistent definitions across departments, leading to delays, rework, and contradictory figures. To resolve this, a Customer Data Platform (CDP) was designed and implemented on Google Cloud. This platform centralizes data capture, standardization, and analytical consumption using the Medallion model (Bronze–Silver–Gold). Data ingestion is automated with Cloud Scheduler and Cloud Run; Pub/Sub decouples producers and consumers; and Dataflow, in streaming, validates quality rules, standardizes to the canonical schema, and publishes to BigQuery with governance and security applied in transit. Consumption occurs in Looker Studio using versioned views with "last updated" metadata, eliminating calculations in BI and ensuring a single interpretation of metrics. An unsupervised clustering (k=4) was trained on the consolidated data in BigQuery ML to profile campaigns by spend and performance, supporting tactical optimization and budget allocation decisions. The solution reduces reconciliations in Excel, shortens the latency between event and decision, improves traceability, and enables technical and functional auditing. Looking ahead, the CDP is now ready to incorporate real-world data sources, expand quality controls, and connect with activation platforms to close the data-analysis-action cycle. | |
| dc.description.degreelevel | Pregrado | spa |
| dc.description.degreename | Ingeniero de Sistemas | spa |
| dc.format.mimetype | application/pdf | |
| dc.identifier.instname | instname:Universidad El Bosque | spa |
| dc.identifier.reponame | reponame:Repositorio Institucional Universidad El Bosque | spa |
| dc.identifier.repourl | repourl:https://repositorio.unbosque.edu.co | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12495/18173 | |
| dc.language.iso | es | |
| dc.publisher.faculty | Facultad de Ingeniería | spa |
| dc.publisher.grantor | Universidad El Bosque | spa |
| dc.publisher.program | Ingeniería de Sistemas | spa |
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| dc.rights | Attribution-NonCommercial-ShareAlike 4.0 International | en |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.rights.accessrights | https://purl.org/coar/access_right/c_abf2 | |
| dc.rights.local | Acceso abierto | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
| dc.source.url | https://youtu.be/kC2-KOb44aI?si=Q0XM7jU39fpqRhfh | |
| dc.subject | Computación en la nube | |
| dc.subject | Gobierno de datos | |
| dc.subject | Marketing basado en datos | |
| dc.subject | Plataforma de datos de clientes | |
| dc.subject | Segmentación de clientes | |
| dc.subject.ddc | 621.3 | |
| dc.subject.keywords | Cloud computing | |
| dc.subject.keywords | Data governance | |
| dc.subject.keywords | Data-driven marketing | |
| dc.subject.keywords | Customer data platform | |
| dc.subject.keywords | Customer segmentation | |
| dc.title | Desarrollo de una plataforma de gestión de datos de clientes como herramienta para marketing dirigido por datos | |
| dc.title.translated | Development of a customer data management platform as a tool for data-driven marketing | |
| dc.type.coar | https://purl.org/coar/resource_type/c_7a1f | |
| dc.type.coarversion | https://purl.org/coar/version/c_ab4af688f83e57aa | |
| dc.type.driver | info:eu-repo/semantics/bachelorThesis | |
| dc.type.hasversion | info:eu-repo/semantics/acceptedVersion | |
| dc.type.local | Tesis/Trabajo de grado - Monografía - Pregrado | spa |
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