Businesses run on data, and data offers little value without analytics. The ability to process data to make predictions about the behavior of individuals or markets, to diagnose systems or situations, or to prescribe actions for people or processes drives business today. Increasingly many businesses are striving to become “data-driven”, proactively relying more on cold hard information and sophisticated algorithms than upon the gut instinct or slow reactions of humans.
Este curso forma parte de Programa especializado: Introduction to Business Analytics and Information Economics
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Programa especializado: Introduction to Business Analytics and Information EconomicsUniversidad de Illinois en Urbana-ChampaignAcerca de este Curso
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Fechas límite flexibles
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Certificado para compartir
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100 % en línea
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Nivel intermedio
Aprox. 17 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Aprox. 17 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
ofrecido por
Universidad de Illinois en Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
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Este curso es parte del Master of Science in Accountancy (iMSA) completamente en línea de Universidad de Illinois en Urbana-Champaign.
Si te aceptan en el programa completo, tus cursos cuentan para tu título de grado.
Programa - Qué aprenderás en este curso
6 horas para completar
Course Overview & Module 1 Analytics Beyond the Spreadsheet
This first module exposes and explains key data and analytics concepts from Big Data to data warehousing to natural language query, and everything in-between. Next we will explore various analytic techniques, types of visualizations, and types of analytics solutions. The course will continue with identifying and learning about key data and analytics roles and organization structures, including chief data and analytics officers, data scientists, and analytics centers of excellence. Alternatives to direct hiring, such as outsourcing and crowdsourcing, will also be covered. Finally, the course will scrutinize analytic trends and futures.
6 horas para completar
18 videos (Total 98 minutos), 8 lecturas, 2 cuestionarios
3 horas para completar
Module 2 Industry and Business Function Analytics
Over the course of the module, you will also see how data and analytics in each of these organizations can be used in similar ways, in similar business functions. Accordingly, you will appreciate that to be truly data-driven, you need not only look to examples in your own industry, but, also learn and apply analytics concepts from organizations in other fields.
3 horas para completar
11 videos (Total 66 minutos), 2 lecturas, 1 cuestionario
4 horas para completar
Module 3 Staffing and Organizing for Analytics
In this module you will learn a bunch of crucial analytical roles and the emergence of new roles in organizations from the C-suite down to various analyst roles. You will take a brief look at the job descriptions and the responsibilities. You will also put yourself in either a job seeker’s or a recruiter’s shoes to see what kind of skill sets are the most important and which position fits you the best. For example, it will introduce you to the three core skills of the data scientist and the crucial soft skills required to be a successful data scientist.
4 horas para completar
11 videos (Total 74 minutos), 2 lecturas, 2 cuestionarios
3 horas para completar
Module 4 Analytics Success Today and Tomorrow
This module explores telling stories, through data, that connect emotionally with your audience. It will also review examples and figures that make the concept easy to understand. You will learn the major do’s and don’ts of creating dataviz and rules that lead to the clear depiction of your findings. This unit specifically focuses on Dona Wong’s guidelines for good data visualization and charts. The last leg of Module 4 teaches the three tests that help you improve your visualization. In the final step of dataviz execution, you will learn the McCandless Method for presenting visualizations. This five-step process produces the most effective communication of the graphics to your audience.
3 horas para completar
15 videos (Total 57 minutos), 4 lecturas, 1 cuestionario
Reseñas
- 5 stars71,37 %
- 4 stars22,58 %
- 3 stars4,03 %
- 2 stars0,80 %
- 1 star1,20 %
Principales reseñas sobre BUSINESS ANALYTICS EXECUTIVE OVERVIEW
por CJ14 de mar. de 2021
For a person who does not have much knowledge about Data Analytics, it was very well explained and presented.
por JM25 de jun. de 2022
Liked everything except the peer-reviewed assignment. Four reviews is too many. It took several weeks to get submissions to review after I had finished everthing else.
por AT1 de jul. de 2020
The course is great overall, but sometimes the language as in the English of the lecture is difficult to understand.
por JU21 de ene. de 2020
Overall a good introduction course into how data is becoming an important addition and will continue to grow in making business decisions.
Acerca de Programa especializado: Introduction to Business Analytics and Information Economics
This specialization targets learners who seek to understand the opportunities that data and analytics present for their organization and those interested in the value of and implications for data as an asset to their organization. Individuals who manage data and make decisions about how data can be leveraged in their organization will find this specialization of particular value.
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