CRISP-DM/SMEs: A Data Analytics Methodology for Non-profit SMEs

Montalvo-Garcia, Jhon; Quintero, Juan Carlos; Losada, Bell Manrique

doi:10.1007/978-981-15-0637-6_38

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Micro, Small, and Medium Enterprises (MSMEs) are a type of business characterized by their small to medium scale, limited workforce, and assets [1]. MSMEs play a vital role in the national economy and constitute the majority of employment in developing countries [2]. Sales are a crucial aspect for MSMEs, as they directly impact their performance and growth.…”

Section: Introductionmentioning

confidence: 99%

Development of Time-Series-Based Mlops Architecture for Predicting Sales Quantity in Micro, Small, and Medium Enterprises (Msmes)

Lesmarna,

Alzami,

Rizqa

et al. 2024

Transmisi J.Ilm. Tek. Elekt.

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Micro, Small, and Medium Enterprises (MSMEs) constitute a significant portion of the economy in many developing countries, playing a vital role in employment generation and economic growth. Sales performance is a critical factor for MSMEs, influenced by various internal and external factors. Time-series analysis offers a valuable tool to predict sales quantities by analyzing historical data and identifying patterns and trends. In this context, the SARIMAX (Seasonal Autoregressive Integrated Moving Average with Exogenous Variables) model emerges as a suitable method to forecast future sales, leveraging both historical data and external variables. This research explores the synergy between time-series analysis, specifically SARIMAX modeling, and MLOps (Machine Learning Operations). Finally, this research aims to provide a framework for the practical application of MLOps to enhance sales forecasting and decision-making processes within MSMEs, fostering their growth and sustainability in a competitive market landscape.

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Section: Introductionmentioning

confidence: 99%

Development of Time-Series-Based Mlops Architecture for Predicting Sales Quantity in Micro, Small, and Medium Enterprises (Msmes)

Lesmarna,

Alzami,

Rizqa

et al. 2024

Transmisi J.Ilm. Tek. Elekt.

View full text Add to dashboard Cite

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“…Por otro lado, por lo general, las organizaciones sin fines de lucro y ONG carecen de recursos o tienen capacidad limitada de adquisición respecto a tecnologías de información. Ergo, la relación costo beneficio en la implementación de TI debe aprovechar al máximo las alternativas que se adapten a la realidad de cada ONG (Montalvo-Garcia et al, 2020). 4.1.2 Casos de estudio de soluciones de BI 4.1.2.1 Caso 1 En esta implementación se destaca la importancia de poder integrar la información en sus diferentes fuentes (servidores, computadoras, dispositivos móviles, etc.)…”

Section: Revisión De La Literaturaunclassified

Solución de inteligencia de negocios para automatizar el proceso de selección y evaluación del proyecto 'Lectores de Paso'

Diaz¹,

Jacobo²

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El presente proyecto tiene como objetivo diseñar una solución de inteligencia de negocios (BI) aplicado a una organización sin fines de lucro; de ahora en adelante llamada ONG. El presente proyecto busca automatizar dos procesos dentro de la ONG. Estos procesos corresponden a la implementación de un proyecto de la ONG llamado 'Lectores de paso'. Así mismo, se busca que el entregable les permita tomar decisiones de manera más ágil y dinámica, dejando de lado cuellos de botella operativos. Para la realización de este proyecto se investigaron soluciones de inteligencia de negocios aplicadas a Pequeñas y Medianas Empresas (PYMEs). Esto debido a su gran similitud con la ONG respecto a términos de tamaño, capacidades y complejidad de la organización. A partir de este punto, se pudo identificar los principales retos y causas que impiden una implementación de este tipo dentro de la organización. La solución planteada emplea herramientas como Pentaho Data Integration Community Edition y Google Data Studio, ambas herramientas de acceso gratuito. Así mismo, empleando datos provistos por la organización se ejecutaron pruebas de concepto que nos permitieron validar la solución. Finalmente, una vez realizada una prueba de concepto, se logró reducir el tiempo operativo en los dos procesos objetivos. Además, se dotó a la organización de un flujo de trabajo que les permita exportar sus datos, tomar mejores decisiones y realizar cambios de alcance a la hora de implementar su proyecto ‘Lectores de paso’.

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The evolution of CRISP-DM for Data Science: Methods, Processes and Frameworks

Shimaoka,

Ferreira,

Goldman

2024

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The expansion of Data Science projects in organizations has been led by three factors: the growth in the amount of data generated, the evolution in storage capacity, and the increase in computational capabilities. However, most of these projects fail to deliver the expected value: 82% of the teams do not use any process model. Despite the popularity of Agile Methods, their adoption in Data Science projects is still scarce. Most of the existing research focuses on algorithms. There is a lack of studies on agility in Data Science. This Systematic Literature Review (SLR) was performed to identify and evaluate 16 studies that can answer how to adapt and apply CRISP-DM using different approaches — methods, frameworks, or process models. In addition, it shows how CRISP-DM has evolved over the last few decades, with derivations emerging from rigid processes to agile methods. This research then analyzes the 16 tailored models and examines the similarities and differences between CRISP-DM derivatives. As a result, it summarizes the CRISP-DM adaptation patters identified, such as phase addition, phase modification, features and tools addition, and integration with other approaches. Consequently, this SLR showcases how CRISP-DM is a robust, flexible, and highly adaptable model that can be extended to different business domains. Finally, it proposes a theoretical guide to modify and customize CRISP-DM for Data Science projects.

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CRISP-DM/SMEs: A Data Analytics Methodology for Non-profit SMEs

Cited by 3 publications

References 6 publications

Development of Time-Series-Based Mlops Architecture for Predicting Sales Quantity in Micro, Small, and Medium Enterprises (Msmes)

Development of Time-Series-Based Mlops Architecture for Predicting Sales Quantity in Micro, Small, and Medium Enterprises (Msmes)

Solución de inteligencia de negocios para automatizar el proceso de selección y evaluación del proyecto 'Lectores de Paso'

The evolution of CRISP-DM for Data Science: Methods, Processes and Frameworks

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