DATA ANALYTICS AND VISUALIZATION OF COVID-19 PANDEMIC IN NIGERIA USING POWER BI (original) (raw)

Visual Exploratory Data Analysis of the Covid-19 Pandemic in Nigeria: Two Years after the Outbreak

arXiv (Cornell University), 2023

The outbreak of the coronavirus disease in Nigeria and all over the world in 2019/2020 caused havoc on the world's economy and put a strain on global healthcare facilities and personnel. It also threw up many opportunities to improve processes using artificial intelligence techniques like big data analytics and business intelligence. The need to speedily make decisions that could have far-reaching effects is prompting the boom in data analytics which is achieved via exploratory data analysis (EDA) to see trends, patterns, and relationships in the data. Today, big data analytics is revolutionizing processes and helping improve productivity and decision-making capabilities in all aspects of life. The large amount of heterogeneous and, in most cases, opaque data now available has made it possible for researchers and businesses of all sizes to effectively deploy data analytics to gain action-oriented insights into various problems in real time. In this paper, we deployed Microsoft Excel and Python to perform EDA of the covid-19 pandemic data in Nigeria and presented our results via visualizations and a dashboard using Tableau. The dataset is from the Nigeria Centre for Disease Control (NCDC) recorded between February 28th, 2020, and July 19th, 2022. This paper aims to follow the data and visually show the trends over the past 2 years and also show the powerful capabilities of these data analytics tools and techniques. Furthermore, our findings contribute to the current literature on Covid-19 research by showcasing how the virus has progressed in Nigeria over time and the insights thus far.

Analysis of COVID-19 Impact using Data Visualization

International Journal for Research in Applied Science and Engineering Technology IJRASET, 2020

The world has suffered from many crises and pandemics in the past but it's the creativity and inventiveness of its people and their rigorous efforts with the capacity to think out of the box which has made them combat and overcome those situations. The world is facing a similar situation with the inception of COVID-19. The deadly new coronavirus first detected in Wuhan; the capital of China's Hubei province has sat its foot across the globe by infecting millions of people worldwide. Nevertheless, tough times ask for draconian measures and smart solutions, so the objective of our research work is to analyse the data with the help of visualization using Python to delineate and bring out a result by comparing the COVID-19 outbreak in different continents and countries like the USA, China, India, Italy, and Taiwan. For differentiation, we have used the total number of confirmed cases, the total number of casualties, and the total number of recovered cases of the COVID-19. Additionally, we have also compared the total number of tests conducted by the countries mentioned above. Our research will also concentrate on what makes COVID-19 pandemic different from other epidemics like SARS (2003), MERS (2012), Ebola (2014) by comparing their mortality rate, contagiousness, and symptoms. For all the comparison we have used data visualization. This research provides a comprehensive understanding of COVID-19 and compares its impact on different regions of the world with the help of Data Visualization and it will also help to derive a better solution for future emergencies.

Data Visualization and Analyzation of COVID-19

Journal of Scientific Research and Reports

Since December 2019 the world is experiencing a deadly disease caused by a novel coronavirus termed as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease associated with this virus is known as COVID-19. This paper focuses on COVID-19 based on freely available datasets including the ones in Kaggle repository. Data analytics is provided on a number of aspects of COVID-19 including the symptoms of this disease, the difference of COVID-19 with other diseases caused by severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and swine flu. The impact of temperature on the spread of COVID-19 is also discussed based on the datasets. Moreover, data visualization is provided on the comparison of infections in males/females which shows that males are more prone to this disease and the older people are more at risk. Based on the data, the pattern in the increase of confirmed cases is found to be an exponential curve in nature. Finally, the relat...

Data analytics and visualization using Tableau utilitarian for COVID-19 (Coronavirus

Global Journal of Engineering and Technology Advances, 2020, 03(02), 028–050, 2020

In 2020 the world has generating 52 times the amount of data as in 2010, and 76 times the number of information sources. Being able to use this data provides huge opportunities and to turn these opportunities into reality, people need to use data to solve problems. Unfortunately in the midst of a global pandemic, when people throughout the world are looking for reliable, trustworthy information about COVID-19(Coronavirus). In this scenario tableau play the vital role, because Tableau is an extremely powerful tool for visualizing massive sets of data very easily. It has an easy to use drag and drop interface. You can build beautiful visualizations easily and in a short amount of time. Tableau supports a wide array of data sources. COVID-19(Coronavirus) analytics with Tableau, you will create dashboards that help you identify the story within our data, and we will better understand the impact of COVID-19 (Coronavirus). In this paper comprehensive review about Tableau. The Tableau are the tools which deals with the big data analytics also it generates the output in visualization technique i.e., more understandable and presentable. Its features include data blending, real-time reporting and collaboration of data. In the end, this paper gives the clear picture of growing COVID-19(Coronavirus) data and the tools which can help more effectively, accurately and efficiently.

Visual Exploratory Data Analysis of the Covid-19 Vaccination Progress in Nigeria

2022

The coronavirus outbreak in 2020 devastated the world's economy, including Nigeria, even resulted in a severe recession. Slowly the country is building back again, and the vaccines are helping to reduce the spread of COVID-19. Since the COVID-19 vaccine came to Nigeria in March, 2021; 18,728,188 people have been fully vaccinated as at May 31st, 2022. This is roughly 10% of the Nigerian population estimated at 206.7 million [1]. This paper presents a visual Exploratory Data Analysis of the COVID-19 vaccination progress in Nigeria using the R-tidyverse package in R studio IDE for data cleaning & analysis, and Tableau for the visualizations. Our dataset is from the Nigerian National Primary Health Care Development Agency (NPHCDA) in charge of the vaccines. The data used for this research contain the state-by-state breakdown of COVID-19 vaccine distribution recorded between March 5th, 2021, and May 31st, 2022. This paper aims to show how these data analytics tools and techniques can be useful in finding insights in raw data by presenting the results of the EDA visually thus reducing the ambiguity and possible confusions that is associated with data in tables. Furthermore, our findings contribute to the growing literature on COVID-19 research by showcasing the COVID-19 vaccination trend in Nigeria and the state by state distribution.

Interactive Data Driven Visualization for COVID-19 with Trends, Analytics and Forecasting

2020 24th International Conference Information Visualisation (IV)

Interactive dashboards process and present raw data in the form of visuals, graphs, and text along with various options for user interactions. The dashboards allow for extracting valuable information and showcase the data in an intuitive and easy to understand manner. As the world is battling with the COVID-19 pandemic, we developed an interactive data-driven dashboard to not only view the current trends, but to also display important analytics and projections for the upcoming week. Built using python modules Dash and Plotly for visualization, the proposed dashboard utilizes the data analytic capabilities of the Pandas python library to structure and organize the raw data efficiently. Our dashboard is lightweight and designed for optimal performance. It can update values dynamically and be loaded onto any web server. Moreover, our proposed solution performed the best when compared to three other COVID-19 solutions, in terms of performance and speed, page size, and the number of HTTP requests.

Implementation of Dashboard Power Bi for Data Visualization of Graduates During Covid-19 Pandemic in The Faculty of Tarbiyah and Teaching Sciences IAIN Palopo

Journal of Information Technology and Its Utilization

This study presents information regarding the distribution of graduates and the number of students who graduated during the pandemic of Covid-19 at the Faculty of Tarbiyah and Teaching Sciences IAIN Palopo through visualization of data depicted during the Covid19 pandemic, namely in a vulnerable time in 2020 to early 2022. This visualization is done by distributing graduate data into the Microsoft Power BI application and depicted in the form of a diagram, after that the data is visualized in the form of diagrams and numbers based on the categories that have been collected in the form of an Excel file which is then saved in a CSV file type so that the files obtained lighter than before so that the distribution of data in the form of information for graduates of the Faculty of Tarbiyah and Teaching Sciences at IAIN Palopo can be easily observed by policymakers in making decisions.

Visualisation System of COVID-19 Data in Malaysia

Trends in Undergraduate Research, 2021

Pandemics are highly unlikely events, therefore, we need a system to understand the statistics about the pandamic. Machine learning algorithms can analyse the data and then we can plan for handling the pandamic. To date, many people are suffering because of the lack of reliable information system. The problem is that there is no integrated system to use the data and plan for pandemic management to minimise social panic. This study aims to provide a system, using COVID-19 data as a sample to visualise and analyse cases, deaths, discharged ICU cases updates in Malaysia as a whole state wise of COVID-19 daily statistics. The results provide visualisation and case comparison among states in Malaysia to easily and quickly understand the situation. This will help and assist the management in decision-making.

Building a statistical surveillance dashboard for COVID-19 infection worldwide

Quality Engineering

When a pandemic like the current novel coronavirus (COVID-19) breaks out, it is important that authorities, healthcare organizations and official decision makers, have in place an effective monitoring system to promptly analyze data, create new insights into problematic areas and generate actionable knowledge for fact-based decision making. The aim of this article is to describe an initial work focused on building a comprehensive statistical surveillance dashboard for the epidemic of COVID-19, which can be exploited also for future needs. We propose novel ways of exploring, analyzing and presenting data, using metrics that have not been used previously. We also show the steps necessary to build and operate such a dashboard. As a result of this this work, a set of data exploration and data visualization tools have been proposed which can be instrumental in providing information necessary to manage a crisis like COVID-19 pandemic in a systematic and effective way. The proposed statistical surveillance dashboard can provide formal authorities and other decision makers with valuable insights into problematic areas and help them make critical decisions based on facts and an in-depth data analysis. The dashboard is implemented in an online dedicated website, freely accessible to the readership of this journal.

Tableros de impacto de los datos de Coronavirus Covid-19 en América Latina y el mundo utilizando Power BI como herramienta de visualización

REICE: Revista Electrónica de Investigación en Ciencias Económicas, 2020

La presente investigación describe la evolución del nuevo coronavirus Covid-19 a través de la creación de dos tableros de impacto para los datos de este tanto a nivel global como en detalle para la región de América Latina y el Caribe. El brote del nuevo coronavirus comenzó en Wuhan, una ciudad de 11 millones de habitantes de la provincia central china de Hubei. Para poder describir la evolución del virus a través de la creación de tableros de impacto se implementó la herramienta de inteligencia de negocios de Microsoft Power BI, donde se llevaron 4 etapas entre ellas el análisis de requerimientos de sistema del caso, diseño de la arquitectura a utilizar, integración de datos y como etapa final la visualización y analítica de los datos. Tras la creación de los tableros de impacto se mostró los números de casos confirmados, fallecidos, casos recuperados y casos activos por región, país y a nivel mundial, la creación de estos tableros permite la buena de decisiones basada en datos com...