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.

Обзор
Data Analyst

Фильтр

Результатов для запроса ''data analyst': 2292

Databricks
Data Science Fundamentals for Data Analysts
Получаемые навыки: General Statistics, Data Mining, Machine Learning, Data Structures, Analysis, Statistical Programming, Supply Chain and Logistics, Algebra, SQL, Supply Chain Systems, Data Management, Apache, Theoretical Computer Science, Mathematics, Data Analysis, Databases, Regression, Probability & Statistics, Big Data
4.0
(рецензий: 28)
Intermediate · Course
Databricks
Applied Data Science for Data Analysts
Получаемые навыки: General Statistics, Machine Learning, Data Management, Hyperparameter, Data Structures, Mathematical Theory & Analysis, Feature Engineering, Algorithms, Machine Learning Algorithms, Applied Machine Learning, Statistical Programming, Computer Programming, Theoretical Computer Science, Probability & Statistics, Data Clustering Algorithms, Mathematics
4.3
(рецензий: 29)
Intermediate · Course
IBM
Introduction to Data Science
Получаемые навыки: Communication, Computer Programming, Data Analysis, Data Management, Data Mining, Database Administration, Database Application, Databases, General Statistics, Machine Learning, Marketing, Probability & Statistics, Python Programming, R Programming, Regression, SPSS, SQL, Statistical Programming
4.6
(рецензий: 68.8k)
Beginner · Specialization
IBM
Data Science Fundamentals with Python and SQL
Получаемые навыки: Basic Descriptive Statistics, Computational Logic, Computer Programming, Data Analysis, Data Management, Data Visualization, Database Administration, Database Application, Databases, Extract, Transform, Load, General Statistics, Hypothesis, Hypothesis Testing, Machine Learning, Mathematical Theory & Analysis, Mathematics, Probability & Statistics, Python Programming, R Programming, SPSS, SQL, Statistical Hypothesis Testing, Statistical Programming, Theoretical Computer Science, Web
4.5
(рецензий: 46.2k)
Beginner · Specialization
IBM
Applied Data Science
Получаемые навыки: Algebra, Analysis, Business Analysis, Cloud API, Cloud Computing, Computational Logic, Computer Programming, Computer Programming Tools, Correlation And Dependence, Data Analysis, Data Management, Data Mining, Data Visualization, Databases, Econometrics, Exploratory Data Analysis, Extract, Transform, Load, General Statistics, Machine Learning, Mathematical Theory & Analysis, Mathematics, Plot (Graphics), Probability & Statistics, Python Programming, Regression, SQL, Spreadsheet Software, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Theoretical Computer Science, Web
4.6
(рецензий: 37.8k)
Beginner · Specialization

Результаты поиска, связанного с data analyst

data analyst career guide and interview preparation

ibm data analyst professional certificate

ibm data analyst

ibm data analyst capstone project

wrangling data for data analysts with python

data science fundamentals for data analysts

applied data science for data analysts

apache spark (tm) sql for data analysts

10 самых популярных курсов по запросу data analyst

Getting Started with Power BI Desktop: Coursera Project Network
Tools for Data Science: IBM
IBM Data Analyst Capstone Project: IBM
Apache Spark (TM) SQL for Data Analysts: Databricks
Wrangling Data for Data Analysts with Python: Coursera Project Network
Data Science Fundamentals for Data Analysts: Databricks
Getting Started with BigQuery GIS for Data Analysts: Google Cloud
Applied Data Science for Data Analysts: Databricks
Scatter Plot for Data Scientists & Big Data Analysts-Visuals: Coursera Project Network
Introduction to Data Science: IBM

Часто задаваемые вопросы на тему 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.‎

Часто задаваемые вопросы предоставляются в ознакомительных целях. Учащимся рекомендуется дополнительно убедиться в том, что интересующие их курсы и другие материалы соответствуют их личным, профессиональным и финансовым потребностям.