Analytics is the system of applying certain methods and techniques to understand the performance of data, generally in an organization or industry. The application of analytics can be used to uncover and interpret relevant patterns of data, which can be later used to make better decisions. Analytics relies on good data as part of its usefulness, as well as the aspects of statistics, computer programming, and operations research to quantify performance. Analytics exists in business when companies use statistics and software processes in assessing how a particular product, service, or project measures up in scope. Businesses perform analytics to pinpoint strengths, identify challenges or weaknesses that may exist, and pull out key data points to help make decisions regarding future growth for the organization.

Learning analytics is a key skill that helps you solve problems to existing challenges. When you use analytics tools to research data patterns, you use methods of analyzing performance characteristics that are essential to a business organization. This is important in today's world of big data. Understanding analytics can make you a valuable asset when assessing areas rich with recorded information, performance indicators, and target goals.

What are typical careers that use analytics?

Analytics is found in a wide range of careers, including business analyst, budget analyst, financial controller, data scientist, and operations researcher. Individuals who move into these and other careers in data analytics often work with raw data and algorithms through mechanical processes to make assumptions and theories. Essentially, with knowledge of analytics, you can move into a job that requires a familiarity with numeric relationships, data structures, and trends and metrics relevant to an organization.

How can taking online courses on Coursera help me learn analytics?

When you take online courses in analytics, you can gain a new understanding of key concepts like data analysis and visualization, mathematical optimization, regression analysis, predictive modeling, and other areas focused on business analytics. Taking online courses about analytics can help you achieve basic data literacy to help you make more informed decisions in any area you work in, like finance, operations, or marketing. As you branch out, you may advance your analytics understanding to include how to extract and manipulate data points, how to use different statistical analysis methods to break down the data, and how to eventually interpret and present your findings.

검색
Analytics

필터링 기준

"analytics"에 대한 3999개의 결과

Google
Google Data Analytics
획득할 기술: Data Analysis, Statistical Programming, Data Science, Business Analysis, SQL, Spreadsheet Software, Data Visualization, Business, Data Management, Data Visualization Software, R Programming, Leadership and Management, Exploratory Data Analysis, Statistical Visualization, Change Management, Strategy and Operations, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Tableau Software, Big Data, Cloud Computing, Critical Thinking, Customer Analysis, General Statistics, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget Management, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Mining, Data Model, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, Full-Stack Web Development, Interactive Data Visualization, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Problem Solving, Product Design, Programming Principles, Project Management, Research and Design, Security Engineering, Security Strategy, Software Engineering, Software Security, Storytelling, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development
4.8
(94.3k개의 검토)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Analyst
획득할 기술: Data Analysis, Python Programming, Data Visualization, Exploratory Data Analysis, Business Analysis, Basic Descriptive Statistics, Data Structures, Data Science, Statistical Programming, Microsoft Excel, Spreadsheet Software, Data Management, General Statistics, Plot (Graphics), SQL, Statistical Visualization, Databases, Data Mining, Statistical Analysis, Programming Principles, Probability & Statistics, Regression, Machine Learning, Algebra, Data Analysis Software, Data Visualization Software, Database Theory, Probability Distribution, Applied Machine Learning, Statistical Tests, Big Data, Correlation And Dependence, Database Application, Estimation, NoSQL, Geovisualization, ArcGIS, Cloud Computing, Computer Programming, Data Warehousing, Database Administration, Extract, Transform, Load, HTML and CSS, Knitr, Mathematics, Minitab, PostgreSQL, R Programming, SAS (Software), SPSS, Apache, Computational Logic, Computer Programming Tools, Econometrics, Leadership and Management, Mathematical Theory & Analysis, Operating Systems, Professional Development, Statistical Machine Learning, System Programming, Theoretical Computer Science
4.6
(59k개의 검토)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
Introduction to Data Analytics
획득할 기술: Data Analysis, Data Management, Data Science, Big Data, Databases, NoSQL, Python Programming, SQL, Statistical Programming, Basic Descriptive Statistics, Cloud Computing, Data Mining, Data Structures, Data Visualization, Data Warehousing, General Statistics, Machine Learning, Mathematics, Probability & Statistics, Apache, Business Analysis, Data Visualization Software, Extract, Transform, Load, Leadership and Management, Microsoft Excel, Professional Development
4.8
(9.6k개의 검토)
Beginner · Course · 1-3 Months
University of Pennsylvania
Business Analytics
획득할 기술: Business Analysis, Data Analysis, Probability & Statistics, Statistical Analysis, General Statistics, Research and Design, Forecasting, Strategy and Operations, Correlation And Dependence, Financial Analysis, Accounting, Human Resources, Marketing, Operational Analysis, Operations Management, Operations Research, Probability Distribution, Spreadsheet Software, Supply Chain and Logistics, Customer Analysis, Financial Accounting, Market Analysis, Market Research, Basic Descriptive Statistics, Exploratory Data Analysis, Finance, People Management, Performance Management, Regulations and Compliance, Statistical Tests, Talent Management, Collaboration, Communication, Critical Thinking, Data Management, Data Mining, Data Model, Data Visualization, Generally Accepted Accounting Principles (GAAP), HR Tech, Leadership Development, Leadership and Management, MarTech, Marketing Management, Media Strategy & Planning, Microsoft Excel, Organizational Development, Plot (Graphics), Process Analysis, Recruitment, Statistical Programming, Statistical Visualization, Applied Mathematics, Big Data, Business Psychology, Computational Logic, Computer Programming, Computer Programming Tools, Data Analysis Software, Data Structures, Decision Making, Entrepreneurship, Estimation, Mathematics, Network Analysis, People Analysis, People Development, Regression, Sales, Strategy, Theoretical Computer Science
4.6
(17.1k개의 검토)
Beginner · Specialization · 3-6 Months
무료

analytics과(와) 관련된 검색

analytics for decision making

analytics as a service for data sharing partners

analytics en las organizaciones

data analytics

business analytics

google analytics

marketing analytics

hr analytics

요약하자면, 여기에 가장 인기 있는 analytics 강좌 10개가 있습니다.

Google Data Analytics: Google
Identifying the Right Role for Yourself: University of California, Irvine
IBM Data Analyst: IBM Skills Network
Human Resources Analytics: University of California, Irvine
Introduction to Data Analytics: IBM Skills Network
Business Analytics: University of Pennsylvania
Interviewing for DS/AI Roles: University of California, Irvine
Getting Started in Google Analytics: Coursera Project Network
MBA Business Analytics: O.P. Jindal Global University
Empathy and Data in Risk Management: University of Illinois at Urbana-Champaign

Business Essentials에서 학습할 수 있는 스킬

분석에 대한 자주 묻는 질문

Analytics is the system of applying certain methods and techniques to understand the performance of data, generally in an organization or industry. The application of analytics can be used to uncover and interpret relevant patterns of data, which can be later used to make better decisions. Analytics relies on good data as part of its usefulness, as well as the aspects of statistics, computer programming, and operations research to quantify performance.
Analytics exists in business when companies use statistics and software processes in assessing how a particular product, service, or project measures up in scope. Businesses perform analytics to pinpoint strengths, identify challenges or weaknesses that may exist, and pull out key data points to help make decisions regarding future growth for the organization.‎
Learning analytics is a key skill that helps you solve problems to existing challenges. When you use analytics tools to research data patterns, you use methods of analyzing performance characteristics that are essential to a business organization. This is important in today's world of big data. Understanding analytics can make you a valuable asset when assessing areas rich with recorded information, performance indicators, and target goals.‎
Analytics is found in a wide range of careers, including business analyst, budget analyst, financial controller, data scientist, and operations researcher. Individuals who move into these and other careers in data analytics often work with raw data and algorithms through mechanical processes to make assumptions and theories. Essentially, with knowledge of analytics, you can move into a job that requires a familiarity with numeric relationships, data structures, and trends and metrics relevant to an organization.‎
When you take online courses in analytics, you can gain a new understanding of key concepts like data analysis and visualization, mathematical optimization, regression analysis, predictive modeling, and other areas focused on business analytics.
Taking online courses about analytics can help you achieve basic data literacy to help you make more informed decisions in any area you work in, like finance, operations, or marketing. As you branch out, you may advance your analytics understanding to include how to extract and manipulate data points, how to use different statistical analysis methods to break down the data, and how to eventually interpret and present your findings.‎