Business Analytics from Coursera

Hoy en día los datos son fundamentales en el entorno empresarial para tener una visión global de la situación de una organización y poder tomar mejores decisiones. En este contexto, el Big Data es un sector en auge en múltiples ámbitos que nos abre distintas oportunidades laborales, como el rol de analista de datos (Data Analyst).

Este curso es una introducción al análisis de datos con un enfoque empresarial, centrado en la relevancia de basar la toma de decisiones estratégicas en el conocimiento que nos aportan los datos.

A lo largo del mismo descubrirás las fases del ciclo de vida de un proyecto basado en datos, así como la importancia de asegurar la calidad de los mismos en las organizaciones. Además, aprenderás los conceptos básicos de estadística descriptiva e inferencial que todo analista de datos debe conocer. Por último, conocerás algunas estrategias para compartir información sacando el máximo rendimiento a las visualizaciones de datos.

Todo ello, con el objetivo de crear impacto en las organizaciones a través de la generación de dashboards más efectivos y el empleo del storytelling a partir de los datos.

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What's inside

Syllabus

Introducción al Big Data

En este módulo haremos una introducción al fenómeno del Big Data. También descubriremos la importancia de los datos en la sociedad actual y las principales tendencias en el entorno empresarial, centrándonos en la importancia de tomar decisiones basadas en datos.

El análisis de datos

A lo largo de este módulo hablaremos del papel, las responsabilidades y las habilidades necesarias para ser un analista de datos. También haremos un pequeño recorrido por la infraestructura, el análisis y las aplicaciones que se usan para capturar y analizar datos.

Proyectos basados en datos

En este módulo conoceremos las fases del ciclo de un proyecto basado en datos, poniendo el foco en aquellas en las que participa de una manera más activa el analista de datos.

La calidad de los datos

En este módulo nos centraremos en las características que deben cumplir los datos de calidad. Además, conoceremos las principales causas y consecuencias de utilizar datos de baja calidad, poniendo el foco en establecer buenas prácticas para mejorar la calidad de los mismos.

Introducción a la estadística descriptiva

En este módulo vamos a tratar los conceptos básicos de estadística descriptiva que todo analista de datos debería conocer para desarrollar de forma eficiente su trabajo.

Introducción a la estadística inferencial

En este módulo nos centraremos en la distribución Normal, sus propiedades y principales usos. Conoceremos también los conceptos de población y muestra, estimación de parámetros (puntual y por intervalo). Además, daremos una definición de lo que es un contraste de hipótesis y descubriremos otros conceptos de estadística inferencial que seguro te serán de gran utilidad.

Creando historias a través de los datos

En este módulo vamos a conocer la importancia de saber transmitir la información obtenida de los datos de una forma clara y concisa para atraer el interés de nuestros interlocutores.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Presenta una introducción a los conceptos básicos del análisis de datos enfatizando su relevancia en el contexto empresarial

Desarrolla habilidades analíticas esenciales que son altamente demandadas en el mercado laboral actual, particularmente en el rol de analista de datos

Proporciona una comprensión integral del ciclo de vida de un proyecto basado en datos, destacando las funciones del analista de datos

Abarca conceptos estadísticos descriptivos e inferenciales fundamentales para el análisis de datos, lo que fortalece la base de los estudiantes en este campo

Enfatiza la importancia de la calidad de los datos y proporciona estrategias para gestionarla y mejorarla, asegurando la precisión y confiabilidad de los resultados analíticos

Incorpora técnicas de visualización de datos para transmitir información de manera clara y atractiva, mejorando la comunicación de los resultados

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Business Analytics with these activities:

Organize your course notes and materials

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Organize your course materials effectively to support your learning journey.

Browse courses on Note-Taking

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Review your notes and materials
Identify key concepts and topics
Organize your materials into folders or binders
Create a study schedule

Complete the 'Data Analysis with Python' tutorial on DataCamp

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Learn the basics of data analysis using Python through interactive tutorials.

Browse courses on Python

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Create a DataCamp account
Enroll in the 'Data Analysis with Python' course
Complete the tutorials and exercises

Read 'Big Data: A Revolution That Will Transform How We Live, Work, and Think'

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Review the fundamental concepts and applications of big data as described in this book.

View La reinvención de la economía: El capitalismo... on Amazon

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Read the introduction and first three chapters
Summarize the key takeaways from each chapter
Identify examples of how big data is used in different industries

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Attend a 'Data Analysis for Business' workshop

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Gain exposure to practical data analysis techniques and learn from industry experts.

Browse courses on Data Analysis

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Research and identify relevant workshops
Register for a workshop
Attend the workshop and participate actively

Solve data analysis problems on Kaggle

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Practice applying data analysis techniques and algorithms to solve real-world problems.

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Create a Kaggle account
Choose a data analysis competition or dataset
Explore the data and identify patterns
Build a model to solve the problem or predict outcomes
Submit your solution for evaluation

Write a blog post on a data analysis topic

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Share your knowledge and insights on a data analysis topic by writing a blog post.

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Publish the post on a relevant platform
Choose a topic
Research the topic
Write the blog post
Proofread and edit the post

Create a data visualization dashboard

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Apply data visualization techniques to create a dashboard that communicates insights from a given dataset.

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Choose a dataset
Clean and prepare the data
Identify the key metrics and insights to communicate
Select appropriate visualization types
Design and develop the dashboard

Build a personal data analysis portfolio

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Develop a portfolio of data analysis projects to showcase your skills and knowledge.

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Identify potential data sources and project ideas
Collect and clean the data
Explore the data and identify patterns
Apply data analysis techniques to solve problems or gain insights
Create data visualizations and dashboards to present your findings

Career center

Learners who complete Business Analytics will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts play a crucial role in organizations that leverage data to make informed decisions. This course provides a solid foundation in data analysis techniques, including statistical analysis and data visualization. By understanding the principles behind data analysis, you can effectively extract insights from data, identify trends, and make data-driven recommendations, enhancing your potential as a Data Analyst.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts help organizations improve their performance by analyzing data and recommending solutions. This course will equip you with the skills to gather, analyze, and interpret data, enabling you to identify areas for improvement and develop strategies for growth. It provides a comprehensive understanding of data analysis techniques and their application in a business context, making it highly relevant for aspiring Business Analysts.

See salaries and explore the career path for Business Analyst

Data Scientist

Data Scientists use scientific methods and algorithms to extract knowledge and insights from data. While this course does not cover advanced data science techniques, it provides a solid foundation in data analysis principles and statistical methods. By understanding the fundamentals of data analysis, you can contribute to data science projects and build a pathway towards a career as a Data Scientist.

See salaries and explore the career path for Data Scientist

Market Research Analyst

Market Research Analysts conduct research to understand market trends and consumer behavior. This course provides a strong foundation in data analysis techniques, which are essential for analyzing market data and drawing meaningful conclusions. By mastering these techniques, you can effectively interpret market data, identify opportunities, and support decision-making as a Market Research Analyst.

See salaries and explore the career path for Market Research Analyst

Financial Analyst

Financial Analysts use data analysis techniques to evaluate financial performance and make investment recommendations. This course introduces statistical analysis, which is fundamental for understanding financial data and making informed decisions. By gaining proficiency in data analysis, you can enhance your skills as a Financial Analyst and contribute to the success of investment strategies.

See salaries and explore the career path for Financial Analyst

Software Engineer

Software Engineers design, develop, and maintain software systems. While this course does not teach software engineering, it provides a foundation in data analysis principles and logical thinking, which are valuable skills for Software Engineers. Understanding data structures and algorithms, as well as the ability to analyze and interpret data, can enhance your problem-solving abilities and contribute to your success as a Software Engineer.

See salaries and explore the career path for Software Engineer

Data Engineer

Data Engineers design and build data pipelines and infrastructure to manage and analyze large volumes of data. This course may be helpful as it provides an introduction to data analysis principles and techniques. By understanding the basics of data analysis, you can better collaborate with data analysts and contribute to the efficient management and analysis of data.

See salaries and explore the career path for Data Engineer

Statistician

Statisticians apply statistical principles to collect, analyze, and interpret data. This course provides a foundation in statistical analysis, which is essential for understanding and applying statistical methods. By mastering statistical techniques, you can enhance your ability to analyze data, draw inferences, and contribute to decision-making as a Statistician.

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Database Administrator

Database Administrators manage and maintain databases to ensure data integrity and performance. While this course does not cover database management, it introduces data analysis principles and techniques, which are valuable skills for Database Administrators. Understanding data structures and algorithms, as well as the ability to analyze and interpret data, can enhance your ability to optimize database performance and troubleshoot issues.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to optimize business processes and solve complex problems. While this course does not cover operations research, it provides a foundation in data analysis and statistical methods, which are valuable skills for Operations Research Analysts. By understanding the principles behind data analysis, you can contribute to the development of data-driven solutions and enhance your potential in this field.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course may be helpful as it provides an introduction to statistical analysis and data interpretation techniques. By understanding the basics of data analysis, you can gain a better understanding of financial data and contribute to the development of investment strategies as a Quantitative Analyst.

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Actuary

Actuaries use mathematical and statistical techniques to assess and manage risk. While this course does not cover actuarial science, it provides a foundation in statistical analysis, which is essential for understanding and applying actuarial methods. By mastering statistical techniques, you can enhance your ability to analyze data, calculate risks, and contribute to the development of risk management strategies.

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Risk Analyst

Risk Analysts identify, assess, and manage risks within organizations. This course may be helpful as it provides an introduction to data analysis and statistical methods, which are valuable skills for Risk Analysts. By understanding the principles behind data analysis, you can contribute to the identification and assessment of risks, as well as the development of risk management strategies.

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Project Manager

Project Managers plan, execute, and monitor projects to ensure successful outcomes. While this course does not cover project management, it provides a foundation in data analysis techniques, which can be valuable for Project Managers. Understanding data analysis principles can enhance your ability to track project progress, analyze risks, and make data-driven decisions throughout the project lifecycle.

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Consultant

Consultants provide expert advice and guidance to organizations. While this course does not cover consulting, it provides a foundation in data analysis techniques, which can be valuable for Consultants. Understanding data analysis principles can enhance your ability to gather and analyze data, identify insights, and develop recommendations for clients.

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Business Analytics

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