Data science employment opportunities of varied complexity and environment are in growing demand across the globe. Data science as a discipline potentially offers a wealth of jobs to prospective employees, while traditional information science-based roles continue to decrease as budgets get cut across the U.S. Since data is related closely to information historically, this research will explore the education of U.S. iSchool professionals and compare it to traditional data science roles being advertised within the job market. Through a combination of latent semantic analysis of over 1600 job postings and iSchool course documentation, it is our aim to explore the intersection of library and information science and data science. Hopefully these research findings will guide future directions for library and information science professionals into data science driven roles, while also examining and highlighting the data science techniques currently driven by the education of iSchool professionals. In addition, it is our aim to understand how data science could benefit from a mutually symbiotic relationship with the field of information science as statistically data scientists spend far too much time working on data preparation and not nearly enough time conducting scientific inquiry. The results of this examination will potentially guide future directions of iSchool students and professionals towards more cooperative data science roles and guide future research into the intersection between iSchools and data science and possibilities for partnership.

El presente trabajo tiene como objetivo encontrar el patrón de características del cliente Premium desertor de tarjetas de crédito, tomando como foco principal la oficina Chacarilla del banco BBVA puesto que, ayudará a identificar al cliente desertor usuario de tarjetas de crédito y, además podrá ser usada para mejorar la gestión del cliente y personalizar los productos según comportamiento. La metodología aplicada se basa en la ciencia de datos, tomando en cuenta diversos estudios de pronósticos de deserción, para luego correlacionar y analizar el conjunto de datos utilizado para este caso, que comprende 1174 datos. Así mismo, se valida las correlaciones e impacto significativo a la agencia para poder quedarnos con 217 clientes desertores, que pertenecen a una categoría premium. Así mismo, cabe mencionar que la deserción y fuga de usuarios de tarjetas de crédito incide con mayor frecuencia, a comparación de otros productos en todas las entidades financieras del Perú puesto que, las entidades bancarias ofrecen a los clientes mejores tasas y beneficios cada mes. / The purpose of this work is to find the pattern of characteristics of the Premium customer credit card defector, with the main focus of the Chacarilla office of the BBVA bank since, to identify the customer defending customer credit card user and, in addition, it can easily be to improve customer management and customize products based on behaviour. The methodology applied is based on data science, taking into account various studies of attrition analysis, to then correlate and analyse the set of data used for this case, which comprises 1174 of data. Likewise, the correlations and the significant impact on the agency are validated to be able to keep 217 defending clients, who belong to a premium category. Likewise, it is worth mentioning that the defection and leakage of credit card users affects more frequently, a comparison of other products in all financial entities of Peru since, banking entities offer customers better rates and benefits every month. / Trabajo de investigación

El presente trabajo consiste en el estudio de un conjunto de información comerciales de la compañía de telecomunicaciones Globalsat Perú y tiene la finalidad de identificar oportunidades de eficiencia en cuanto a los actuales planes de telefonía satelital. Los resultados del análisis permitirán a la compañía tener un sustento objetivo para la mejora del diseño de los productos que son parte del estudio. Esto a su vez, contribuirá con la mejora de la oferta comercial disponible en el mercado y, además, potencialmente tendrá un impacto en la rentabilidad de los planes analizados. En este estudio se utiliza como principal herramienta la metodología de ciencia de datos aprendida y sus fundamentos, poniendo en práctica de manera intensiva las técnicas de visualización desarrolladas a lo largo de los cursos pertenecientes a la especialización en ciencia de datos. / The following research consists in the analysis of a set of sales data from the telecom firm Globalsat Perú and has the main goal of identifying efficiency opportunities in the current satellite telephony plans. The results of this investigation will allow Globalsat to have objective proof for the improvement of the design of the products that are subject of this study. This will contribute with the development of the commercial offer available at the marketplace and will potentially have an impact in these plans’ profitability. This study uses as a main tool the data science methodology and its principles learnt, using intensively some of the visualization techniques worked during the courses of the data science specialization. / Trabajo de investigación

El presente trabajo tiene como objetivo identificar las variables que influyeron en la productividad de las emisiones de nuevas pólizas en el periodo del 2019 en las agencias de Lima, en las siguientes páginas se detalla de manera concreta y pormenorizada. Por otro lado, dicho estudio abarca temas tales como comprensión del negocio y enfoque analítico, compresión y preparación de los datos, producción, análisis e interpretación de los datos, modelado y evaluación de la data. Asimismo, la metodología utilizada para el estudio en mención está basada en la metodología de la ciencia de datos de IBM, que se espera contribuya a la obtención de resultados favorables de cara a responder la pregunta de investigación. El presente trabajo de investigación tiene un enfoque descriptivo que emplea la técnica de aprendizaje supervisado con la ayuda de regresión lineal. Por último, el propósito del presente proyecto de investigación no es el de brindar una solución en concreto para la organización en estudio, sino el de dar alternativas para posibles planes de acción y/o mejor toma de decisiones al problema identificado, los cuales puedan ser implementados en pro de la mejora departamental de la compañía. / The work purpose is to identify the variables that influenced the productivity of the issuance of new policies in the 2019 period in the Lima agencies, which is detailed in a concrete and detailed way in the following pages. On the other hand, this study covers topics such as business understanding and analytical approach, data compression and preparation, data production, analysis and interpretation, data modeling and evaluation. Likewise, the methodology used for the study in question is based on the IBM data science methodology, which is expected to contribute to obtaining favorable results in order to answer the research question. The present research work has a descriptive approach, the same one that uses the supervised learning technique with the help of linear regression. Finally, the purpose of this research project is not to provide a specific solution for the organization under study, but to provide alternatives for possible action plans and / or better decision-making to the identified problem, which may be implemented in favor of the departmental improvement of the company. / Trabajo de investigación

La industria de cuidado del hogar, en la categoría de lejía, implica la producción y comercialización de estas, utilizadas para la desinfección de superficies y alimentos. Sin embargo, durante el verano, entre los meses de enero y marzo, el consumo de este producto incrementa por su uso para la purificación de agua, sobre todo, en localidades propensas a huaicos. El presente trabajo no incluye uso de la lejía para el narcotráfico. Debido a la coyuntura mundial, el consumo de estos productos viene en aumento, debido a que, hoy en día, la limpieza juega un rol fundamental para protegerse a uno mismo, a la familia y a los hogares como método de prevención de contraer el Covid-19. Es por ello, por lo que consideramos que la salud y la higiene se han convertido en las principales prioridades de los consumidores en plena pandemia. El desarrollo del presente trabajo de investigación se realiza bajo la metodología de la ciencia de datos mediante un análisis híbrido, tanto exploratorio como explicativo, con el objetivo de identificar los principales factores que influyen en el consumo de lejía en el Perú durante el periodo 2015-2020. Los resultados de esta investigación estarán acompañados de gráficos que permitirán contar la historia y responder a la pregunta del problema de una manera clara y específica mediante las diferentes visualizaciones. / The home care industry, in the bleach category, involves the production and marketing of bleach, used for the disinfection of surfaces and food. However, during the summer, between the months of January and March, the consumption of this product increases due to its use for the purification of water, especially in localities prone to huaicos. This work does not include the use of bleach for drug trafficking. Due to the global situation, the consumption of these products is increasing, because, nowadays, cleaning plays a fundamental role to protect oneself, the family and homes as a method of prevention of contracting Covid- 19. That is why we believe that health and hygiene have become the top priorities for consumers during the pandemic. The development of this research work is carried out under the methodology of data science through a hybrid analysis, both exploratory and explanatory, with the aim of identifying the main factors that influence the consumption of bleach in Peru during the period 2015- 2020. The results of this investigation will be accompanied by graphics that will allow the story to be told and the problem question answered in a clear and specific way through the different visualizations. / Trabajo de investigación

El objeto de estudio del presente trabajo es la empresa Partners Technology S. A. C., donde se realizó un exhaustivo análisis interno y externo con el propósito de identificar el problema principal de la organización. Así pues, se determinó que su mayor dificultad es el inadecuado conocimiento de sus clientes. Por esta razón, la investigación se centra en reconocer las variables que influyen en el comportamiento de compra de los usuarios. Para lograr dicho objetivo se empleó la metodología de ciencia de datos mediante un análisis híbrido, es decir, exploratorio y explicativo. Los resultados obtenidos permitirán responder a las preguntas de Data Science formuladas. Es importante mencionar que para la creación de la base de datos utilizada se recurrió a fuentes internas y externas a la compañía, de las cuales se lograron dilucidar las variables que muestran las características de sus clientes. También cabe destacar que se realizó un análisis estadístico de todas las variables cuantitativas con el fin de encontrar correlaciones. De esta forma se hallaron importantes descubrimientos que aportarán valor a la compañía y permitirán el logro de sus objetivos, dado que en el presente trabajo se proponen soluciones al problema señalado y se sugieren las acciones que se deberán adoptar a corto plazo. / The object of study of this work is the company Partners Technology S.A.C. Therefore, an exhaustive internal and external analysis of the company was carrie out in order to identify their main problem. In this sense, it was determined that inadequate knowledge of customers is the greatest difficulty that the organization goes through. For this reason, the objective of this research is to identify the variables that influence the purchasing behavior of Partners Technology. To achieve the proposed objective, the Data Science methodology was develope through a hybrid analysis, that is, exploratory and explanatory. Likewise, the results obtained will allow answering the Data Science questions asked. It is important to mention that, for the creation of the database used in this work, internal and external sources were used from the company Partners Technology S.A.C. Likewise, the selected variables provide characteristics of their clients. It should be noted that a statistical analysis of all quantitative variables was carried out in order to find correlations. In this sense, by Data Science techniques, results were verifie are the main ones. Likewise, important discoveries were found that will add value to the company and enable it to achieve its objectives. This paper proposes solutions to the research problem and suggests actions to be taken in the short term. / Trabajo de investigación

Detecting anomalies in computer-based systems, including Cyber-Physical Systems (CPS), has attracted a large interest recently. Behavioral anomalies represent deviations from what is regarded as the nominal expected behavior of the system. Both Process science and Data science can yield satisfactory results in detecting behavioral anomalies. Within Process Mining, Conformance Checking addresses data retrieval and the connection of data to behavioral models with the aim to detect behavioral anomalies. Nowadays, computer-based systems are increasingly complex and require appropriate validation, monitoring, and maintenance techniques. Within complex computer-based systems, the European Rail Traffic Management System/European Train Control System (ERTMS/ETCS) represents the specification of a standard Railway System integrating heterogeneous hardware and software components, with the aim of providing international interoperability with trains seemingly interacting within standardized infrastructures. Compliance with the standard as well as expected behavior is essential, considering the criticality of the system in terms of performance, availability, and safety. To that aim, a Process Mining Conformance Checking process can be employed to validate the requirements through run-time model-checking techniques against design-time process models. A Process Mining Conformance Checking methodology has been developed and applied with the goal of validating the behavior exposed by an ERTMS/ETCS system during the execution of specific scenarios. The methodology has been tested and demonstrated correct classification of valid behaviors exposed by the ERTMS/ETCS system prototype. Results also showed that the Fitness metric developed in the methodology allows the detection of latent errors in the system before they can generate any failures.

El presente trabajo de investigación tiene como finalidad analizar el incremento de suscriptores de Netflix con respecto a la competencia desde el 2010 hasta lo que va del año 2020. Hemos determinado que el enfoque será predictivo para que la organización a cargo pueda hacer uso del modelo supervisado de la manera que más le favorezca y estos puedan tomar las mejores decisiones estratégicas. Para ello, se ha generado una base de datos recopilada de diversas fuentes públicas confiables para obtener las variables: “cantidad de suscriptores”, “costo de contenido original”, “covid-19” … y posterior a ello, con toda la data adquirida se procederá a realizar cada etapa de la metodología de la ciencia de datos descrita en el curso durante el programa de ciencia de datos. Para aclarar el panorama hemos optado por el uso de la técnica de correlación de Pearson, lo cual nos permitió determinar las variables que tenían mejor correlación entre ellas, esto advierte que la variable más adecuada para determinar futuros pronósticos y analizar el incremento de suscriptores es la del costo de contenido original. Finalmente, para mostrar los resultados de la investigación se ha decidido utilizar como herramienta de visualización Power BI para exponer el presente estudio y responder a los objetivos planteados. / The purpose of this research work is to analyze the increase in Netflix subscribers with respect to the competition from 2010 to so far in 2020. We have determined that the approach will be predictive so that the organization in charge can make use of the supervised model in the way that best suits them and they can make the best strategic decisions. For this, a database compiled from various reliable public sources has been generated to obtain the variables: "number of subscribers", "cost of original content", "covid-19" ... and after that, with all the data acquired Each stage of the data science methodology described in the course will be carried out during the data science program. To clarify the panorama we have opted for the use of the Pearson correlation technique, which allowed us to determine the variables that had the best correlation between them, this warns that the most appropriate variable to determine future forecasts and analyze the increase in subscribers is the of the cost of original content. Finally, to show the results of the research, it has been decided to use Power BI as a visualization tool to present the present study and respond to the objectives set. / Trabajo de investigación

En el siguiente trabajo de investigación se utilizó la metodología de Ciencia de datos para buscar posibles soluciones al problema que tiene el programa de Arizona de la Universidad de Ciencias Aplicadas (UPC) ya que no se logra llegar a la meta de alumnos inscritos y admitidos a pesar de presentar grandes beneficios en el aspecto profesional y educativo. Se analizó la data histórica de los años 2019, 2020 y 2021 la cual fue recolectada directamente de la universidad y se estableció el enfoque prescriptivo. Se identificaron las variables más relevantes de la base de datos como el nivel de inglés, la carrera elegida, el ingreso familiar promedio, entre otras, con la finalidad realizas el análisis descriptivo para crear visualizaciones y generar gráficos que muestren y nos ayuden a contar la historia. La arquitectura de datos se desarrolló con la finalidad de ver el proceso de análisis para que luego se pueda desarrollar e implementar un modelo que nos ayude a predecir el comportamiento de los alumnos frente al programa mediante el árbol de decisiones. Los resultados más resaltantes del estudio fueron que el nivel de inglés es una de las limitantes para la inscripción de los alumnos. Asimismo, el factor económico influye en la decisión, ya que es más probable que un alumno con ingreso promedio familiar mayor a 10,000.00 soles se matricule y, por último, que el modelo mediante el árbol de decisiones nos permite identificar si un alumno se matricula o no en el programa de Arizona. / In the following research work, the Data Science methodology was used to find possible solutions to the problem that the Arizona program of the University of Applied Sciences (UPC) has since it is not possible to reach the goal of students enrolled and admitted to despite presenting great benefits in the professional and educational aspect. The historical data of the years 2019, 2020 and 2021 was analyzed, which was collected directly from the university and the prescriptive approach was established. The most relevant variables of the database were identified such as the level of English, the chosen career, the average family income, among others, in order to carry out the descriptive analysis to create visualizations and generate graphs to help us to count the story. The data architecture was developed in order to see the analysis process so that later a model can be developed and implemented that helps us predict the behavior of students in front of the program through the decision tree. The most outstanding results of the study were that the level of English is one of the limitations for the enrollment of students. Likewise, the economic factor influences the decision, since it is more likely that a student with an average family income greater than 10,000.00 soles will enroll and, finally, that the model through the decision tree allows us to identify whether a student enrolls or not on the Arizona show. / Trabajo de investigación

<p>CO₂ concentration in the atmosphere poses a great threat to life on earth as we know it. The reduction of CO₂ concentration is key to avoid the critical turning point of 1.5^oC temperature increase highlighted by Intergovernmental Panel on Climate Change (IPCC). Gasification using CO₂ as reacting agent can potentially reduce the CO₂ concentration in the atmosphere. Naturally, biomass such as corn, uses great amounts of CO₂ for photosynthesis and produces O₂; hence, energy and fuel production using biomass can potentially be classified as carbon neutral. Moreover, if CO₂ is used as the gasifying agent, gasification can effectively be carbon-negative and collaborate to the reduction of CO2 in the atmosphere.</p> <p>The major setback of using CO₂ biomass gasification is the energy-intensive reaction between C + CO₂ -> 2CO. This reaction at atmospheric pressure and room temperature is heavily tilted towards producing char and CO2. The current investigation describes efforts to favor the right hand side of the reaction by using simple impregnation techniques and cost-effective catalysts to reduce the energy requirements of the reaction. Also, parameters such as pressure are explored to tilt the balance towards the production of CO. Corn stover is selected as the biomass for the present research due to its wide use and availability in the US.</p> <p>The results show that by using catalysts such as iron nitrate and sodium aluminate, the temperature required to achieve substantial char conversion is reduced. Also, increasing the pressure of the reactor, the temperature can be substantially decreased by 100 K and 150 K. The structure and chemical composition of the chars is studied to explain the differences in the reaction rate between chars. Further, chemical kinetics are calculated to compare the present work with previous work in the literature. Finally, data-driven analysis of the gasification data is explored. The appendices provide supplementary information on the application of deep learning to CO₂ recycling using turbulent flames and efforts to reduce the flame spread rate over a pool of Jet A by using Multi Walled Carbon Nanotubes (MWCNTS).</p>