What is a data analyst?

A data analyst is a person whose job is to gather and interpret data in order to solve a specific problem. The role includes plenty of time spent with data, but entails communicating findings too. A data analyst gathers, cleans, and studies data sets to help solve problems. Read our career guide article about what data analysts do .

Why is it valuable to learn how to be a data analyst?

It is valuable to learn about how to be a data analyst because companies in almost every industry would benefit from the work done by data analysts. The insights brought forth by data analysts are extremely valuable to employers who want to learn more about customers, marketing trends, and future scenarios. Data analysts are responsible for the ground-level work of seeing trends and patterns that help businesses eventually decide to make major organizational moves.

What are typical career opportunities available for a data analyst?

Typical career opportunities for data analysts are in major insurance companies; large technology companies like Oracle, IBM, and Siemens; financial credit bureaus; consumer and B2B technology firms; financial firms; and cloud data companies. Data analysts can find jobs in a variety of roles in creative fields as well, as data is researched and used in the marketing, advertising, broadcasting, and film industries too.

How can taking online courses help me learn to be a data analyst?

When you take online courses to be a data analyst, you have the opportunity to learn how to use statistical techniques to acquire data from key sources. You might also uncover key data analysis concepts in Python programming, data science, pivot tables, data visualization, and more. Online courses can expose you to new insights on how to identify, analyze, filter, clean, and report on data that show trends or patterns that have been researched in complex data sets.

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2340 resultados referentes a "data analyst"

University of California, Davis
Data Visualization with Tableau
Habilidades que você terá: Analysis, Analytics, Business Analysis, Communication, Data Analysis, Data Analysis Software, Data Visualization, Data Visualization Software, Exploratory Data Analysis, Interactive Data Visualization, Principle, Probability & Statistics, Research and Design, Software, Storytelling, Tableau Software, Visual Design
4.5
(6.8k avaliações)
Beginner · Specialization · 3-6 Months
IBM Skills Network
Advanced Data Science with IBM
Habilidades que você terá: Algorithms, Apache, Apache Spark, Applied Machine Learning, Artificial Neural Networks, Basic Descriptive Statistics, Bayesian Statistics, Big Data, Change Management, Cloud Computing, Computer Architecture, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Correlation And Dependence, Data Analysis, Data Management, Data Model, Data Structures, Data Visualization, Databases, Deep Learning, Dimensionality Reduction, Distributed Computing Architecture, Econometrics, Estimation, Experiment, Extract, Transform, Load, General Statistics, IBM Cloud, Leadership and Management, Machine Learning, Machine Learning Algorithms, Natural Language Processing, Plot (Graphics), Probability & Statistics, Probability Distribution, Process, Programming Principles, Python Programming, Regression, SQL, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Strategy and Operations, Tensorflow, Theoretical Computer Science
4.3
(2.9k avaliações)
Advanced · Specialization · 3-6 Months
University of Michigan
Applied Data Science with Python
Habilidades que você terá: Algorithms, Applied Machine Learning, Artificial Neural Networks, Computational Logic, Computer Graphics, Computer Networking, Computer Programming, Data Analysis, Data Mining, Data Visualization, Econometrics, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Mathematical Theory & Analysis, Mathematics, Natural Language, Natural Language Processing, Network Analysis, Network Model, Plot (Graphics), Probability & Statistics, Programming Principles, Python Programming, Regression, Statistical Machine Learning, Statistical Programming, Statistical Tests, Theoretical Computer Science
4.5
(32.1k avaliações)
Intermediate · Specialization · 3-6 Months
IBM Skills Network
Data Analysis with Python
Habilidades que você terá: General Statistics, Exploratory Data Analysis, Probability & Statistics, Spreadsheet Software, Mathematical Theory & Analysis, Python Programming, Correlation And Dependence, Regression Analysis, Machine Learning, Data Mining, Statistical Analysis, Statistical Machine Learning, Regression, Analysis, Data Analysis, Econometrics, Linear Regression, Algebra, Business Analysis, Computer Programming Tools, Computer Programming, Statistical Programming, Linearity
4.7
(15.3k avaliações)
Beginner · Course · 1-3 Months
Johns Hopkins University
Data Science
Habilidades que você terá: Algorithms, Application Development, Applied Machine Learning, Business Analysis, Computer Programming, Data Analysis, Data Management, Data Visualization, Econometrics, Exploratory Data Analysis, Extract, Transform, Load, General Statistics, Interactive Data Visualization, Knitr, Machine Learning, Machine Learning Algorithms, Modeling, Natural Language, Natural Language Processing, Plot (Graphics), Probability, Probability & Statistics, Probability Distribution, R Programming, Regression, Regression Analysis, Software Engineering Tools, Statistical Analysis, Statistical Programming, Statistical Tests, Theoretical Computer Science
4.5
(49.2k avaliações)
Beginner · Specialization · 3-6 Months
Imperial College London
Mathematics for Machine Learning
Habilidades que você terá: Algebra, Algorithms, Analysis, Artificial Neural Networks, Basic Descriptive Statistics, Calculus, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Analysis, Deep Learning, Differential Equations, General Statistics, Lambda Calculus, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Matrices, Probability & Statistics, Probability Distribution, Python Programming, Regression, Statistical Programming, Theoretical Computer Science
4.6
(12.8k avaliações)
Beginner · Specialization · 3-6 Months
Google
Foundations of User Experience (UX) Design
Habilidades que você terá: Data Analysis, Investment Management, Research and Design, Communication, Entrepreneurship, User-Centered Design, Brand, Business Psychology, Social Media, Leadership and Management, Design Thinking, Financial Analysis, User Experience Design, Experience, Problem Solving, Marketing, User Experience, Design Sprint, Web Development, Personal Branding, Brand Management, Business Analysis, Finance, Web Design, Personal Advertisement, Human Computer Interaction, Accounting
4.8
(33.6k avaliações)
Beginner · Course · 1-4 Weeks
University of Illinois at Urbana-Champaign
Data Mining
Habilidades que você terá: Algorithms, Applied Machine Learning, Bayesian Statistics, Bioinformatics, Business Psychology, Calculus, Computer Graphics, Computer Programming, Data Analysis, Data Management, Data Mining, Data Structures, Data Visualization, Databases, Documents, Entrepreneurship, General Statistics, Geovisualization, Machine Learning, Machine Learning Algorithms, Mathematics, Natural Language Processing, Probability & Statistics, Project Management, Python Programming, Recommender Systems, SQL, Software, Statistical Programming, Strategy and Operations, Theoretical Computer Science
4.5
(2.7k avaliações)
Intermediate · Specialization · 3-6 Months
Gratuito
Stanford University
Introduction to Statistics
Habilidades que você terá: Data Visualization, Regression, Experiment, Basic Descriptive Statistics, Bayesian Statistics, Markov Model, Hypothesis Testing, Machine Learning, Statistical Analysis, Data Analysis, Probability, Plot (Graphics), Probability & Statistics, Statistical Hypothesis Testing, Correlation And Dependence, General Statistics, Econometrics, Statistical Inference, Probability Distribution, Statistical Tests
4.5
(1.2k avaliações)
Beginner · Course · 1-3 Months

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Em resumo, aqui estão 10 dos nossos cursos mais populares data analyst

Data Visualization with Tableau: University of California, Davis
Advanced Data Science with IBM: IBM Skills Network
Applied Data Science with Python: University of Michigan
Analyzing Company Performance using Ratios: Coursera Project Network
Data Analysis with Python: IBM Skills Network
Getting Started in Google Analytics: Coursera Project Network
Data Science: Johns Hopkins University
Mathematics for Machine Learning: Imperial College London
Foundations of User Experience (UX) Design: Google
Data Mining: University of Illinois at Urbana-Champaign

Perguntas frequentes sobre Data Analyst

It is valuable to learn about how to be a data analyst because companies in almost every industry would benefit from the work done by data analysts. The insights brought forth by data analysts are extremely valuable to employers who want to learn more about customers, marketing trends, and future scenarios. Data analysts are responsible for the ground-level work of seeing trends and patterns that help businesses eventually decide to make major organizational moves.‎
Typical career opportunities for data analysts are in major insurance companies; large technology companies like Oracle, IBM, and Siemens; financial credit bureaus; consumer and B2B technology firms; financial firms; and cloud data companies. Data analysts can find jobs in a variety of roles in creative fields as well, as data is researched and used in the marketing, advertising, broadcasting, and film industries too.‎
When you take online courses to be a data analyst, you have the opportunity to learn how to use statistical techniques to acquire data from key sources. You might also uncover key data analysis concepts in Python programming, data science, pivot tables, data visualization, and more. Online courses can expose you to new insights on how to identify, analyze, filter, clean, and report on data that show trends or patterns that have been researched in complex data sets.‎

Este conteúdo de Perguntas frequentes foi disponibilizado apenas para fins informativos. Os aprendizes são aconselhados a realizar pesquisas adicionais para garantir que os cursos e outras credenciais buscadas atendam a seus objetivos pessoais, profissionais e financeiros.