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    • Data Visualization
    Related topics:데이터 분석excel 대시보드데이터데이터 분석가비즈니스 분석데이터 마이닝

    필터링 기준

    "data visualization"에 대한 599개의 결과

    • Google

      Google

      Google Data Analytics

      획득할 기술: Algorithms, Analysis, Application Development, Big Data, Budget Management, Business Analysis, Business Communication, Change Management, Cloud Computing, Communication, Computational Logic, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Model, Data Structures, Data Visualization, Data Visualization Software, Database Administration, Database Design, Databases, Decision Making, Design and Product, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, General Statistics, Interactive Data Visualization, Leadership and Management, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Plot (Graphics), Privacy, Probability & Statistics, Problem Solving, Product Design, Programming Principles, Project Management, R Programming, Research and Design, SQL, Security Engineering, Security Strategy, Small Data, Software Engineering, Software Security, Spreadsheet Software, Statistical Analysis, Statistical Programming, Storytelling, Strategy and Operations, Theoretical Computer Science, Visual Design

      4.8

      (63.9k개의 검토)

      Beginner · Professional Certificate

    • University of California, Davis

      University of California, Davis

      Data Visualization with Tableau

      획득할 기술: Analysis, Analytics, Business Analysis, Communication, Data Analysis, Data Analysis Software, Data Visualization, Data Visualization Software, Exploratory Data Analysis, Interactive Data Visualization, Probability & Statistics, Research and Design, Software, Storytelling, Visual Design

      4.5

      (6.7k개의 검토)

      Beginner · Specialization

    • IBM

      IBM

      Data Analysis and Visualization Foundations

      획득할 기술: Analysis, Analytics, Apache, Big Data, Business Analysis, Cleaning, Computer Programming, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Structures, Data Visualization, Data Visualization Software, Data Warehousing, Databases, Extract, Transform, Load, General Statistics, Leadership and Management, Microsoft Excel, NoSQL, Operating Systems, Plot (Graphics), Professional Development, Software, Spreadsheet Software, Statistical Visualization, System Programming

      4.7

      (9.6k개의 검토)

      Beginner · Specialization

    • New York University

      New York University

      Information Visualization

      획득할 기술: Communication, Data Visualization, Geovisualization, HTML and CSS, Interactive Data Visualization, Research and Design, Visual Design, Web Development

      4.5

      (384개의 검토)

      Beginner · Specialization

    • PwC

      PwC

      Data Analysis and Presentation Skills: the PwC Approach

      획득할 기술: Analytics, Big Data, Business Analysis, Business Communication, Communication, Computer Programming, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Visualization, Data Visualization Software, Databases, Decision Making, Entrepreneurship, General Statistics, Leadership and Management, Presentation, Probability & Statistics, Regression, Spreadsheet Software, Statistical Analysis

      4.6

      (10k개의 검토)

      Beginner · Specialization

    • University of Illinois at Urbana-Champaign

      University of Illinois at Urbana-Champaign

      Data Visualization

      획득할 기술: Data Analysis, Software, Data Visualization

      4.5

      (1.3k개의 검토)

      Mixed · Course

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      University of Colorado Boulder

      University of Colorado Boulder

      Fundamentals of Data Visualization

      획득할 기술: Data Visualization

      4.8

      (10개의 검토)

      Intermediate · Course

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      Macquarie University

      Macquarie University

      Excel Skills for Data Analytics and Visualization

      획득할 기술: Analysis, Business Analysis, Chart, Data Analysis, Data Analysis Software, Data Management, Data Model, Data Visualization, Extract, Transform, Load, Interactive Data Visualization, Interactivity, Microsoft Excel, Modeling, Spreadsheet Software

      4.8

      (2.8k개의 검토)

      Intermediate · Specialization

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      IBM

      IBM

      Data Visualization with Python

      획득할 기술: Probability & Statistics, Computer Programming, Python Programming, Statistical Visualization, Data Visualization, Statistical Programming, Geovisualization, Plot (Graphics), General Statistics, Map, Matplotlib

      4.5

      (10.2k개의 검토)

      Intermediate · Course

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      Johns Hopkins University

      Johns Hopkins University

      Data Visualization & Dashboarding with R

      획득할 기술: Computer Programming, Data Management, Data Visualization, Interactive Data Visualization, Plot (Graphics), R Programming, Statistical Programming

      4.8

      (227개의 검토)

      Beginner · Specialization

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      Johns Hopkins University

      Johns Hopkins University

      Getting Started with Data Visualization in R

      획득할 기술: Plot (Graphics), Data Visualization, R Programming, Statistical Programming, Data Management

      4.8

      (155개의 검토)

      Beginner · Course

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      Università di Napoli Federico II

      Università di Napoli Federico II

      Data Visualization: Analisi dei dati con Tableau

      획득할 기술: Analysis, Business Analysis, Data Analysis, Data Analysis Software, Data Visualization, Data Visualization Software

      4.4

      (7개의 검토)

      Beginner · Specialization

    data visualization과(와) 관련된 검색

    data visualization and communication with tableau
    data visualization with tableau
    data visualization with python
    data visualization with r
    data visualization in excel
    data visualization with advanced excel
    data visualization in microsoft powerpoint
    data visualization in r with ggplot2
    1234…50

    요약하자면, 여기에 가장 인기 있는 data visualization 강좌 10개가 있습니다.

    • Google Data Analytics: Google
    • Data Visualization with Tableau: University of California, Davis
    • Data Analysis and Visualization Foundations: IBM
    • Information Visualization: New York University
    • Data Analysis and Presentation Skills: the PwC Approach: PwC
    • Data Visualization: University of Illinois at Urbana-Champaign
    • Fundamentals of Data Visualization: University of Colorado Boulder
    • Excel Skills for Data Analytics and Visualization: Macquarie University
    • Data Visualization with Python: IBM
    • Data Visualization & Dashboarding with R: Johns Hopkins University

    데이터 시각화에 대한 자주 묻는 질문

    • Data visualization, which is sometimes called information visualization, is the representation of datasets through graphical means such as charts, maps, visual analytics interfaces such as dashboards, and interactive visualizations. A picture is worth a thousand words - or a thousand lines of a spreadsheet - and the ability to convey key relationships within complex datasets and insights from data analysis in a visually compelling way is critically important to making sense of our world.

      While data visualizations may be as simple as a bar graph created in Microsoft Excel, the complexity, size, and velocity of datasets in the big data era often demand more powerful approaches. Specialized programs such as Tableau Software and the D3.js JavaScript library are widely used in the business world to create dynamic data visualizations, which may even incorporate real-time data streams. For particularly complex tasks, data virtualization software may also be used as middleware to integrate multiple sources and types of data into a format suitable for use with these visualization programs.‎

    • The ability to create data visualizations are increasingly expected in a variety of jobs, making these skills highly valuable as well as portable. Whether you’re a financial analyst at a hedge fund displaying a real-time dashboard of portfolio risk or a data journalist creating an interactive visualization map of the spread of Covid-19, compelling data visualizations can increase the impact of your work and give you an edge in your career.

      Management analysts are particularly attuned to the value of good data visualizations. These consultants must make convincing recommendations for organizational changes to upper-level management and busy executives, and powerful graphics can be essential to making these cases effectively. According to the Bureau of Labor Statistics, management analysts earned a median annual wage of $85,260 as of 2019, and these jobs are expected to grow much faster than average as more and more companies seek advice on navigating today’s fast-changing business world.‎

    • Yes! Coursera lets you learn remotely about data visualization and related topics with courses and Specializations from top-ranked schools like New York University, University of California, Davis, and the University of Illinois at Urbana-Champaign. You can also take courses from industry leaders like IBM and PwC, one of the top management consultancies in the world. Online learning with Coursera is an especially good fit for mid-career professionals seeking to add data visualization capabilities to their skill set, as you can complete coursework on a flexible schedule that fits into your existing work life.‎

    • Some skills you might want to have before learning data visualization include mathematics, Excel, and some coding experience. Specifically, learning popular programming languages like R and Python can be useful for analyzing the data you want to present in a visual format. Strong data analysis skills are usually essential because you should be able to interpret data accurately to avoid misleading the people viewing the final product. In addition to technology skills, you can put to use other skills in a data visualization role, such as problem-solving, artistic skills, and communication skills.‎

    • The right kind of person for a role in data visualization has a combination of technology, business, and communication skills. They typically know how to collect, analyze, and interpret data quickly and accurately using programming languages like R, Python, and JavaScript and tools such as Tableau, PowerBI, or Microsoft Excel. Someone with strong communication skills also tends to work well in this field. Being able to listen to the needs of the client and create a data visualization tool that accurately represents the data in a way that the audience understands is useful.‎

    • If you're comfortable working with large amounts of data and are passionate about making sure people understand the available data about a project, program, or concern, learning data visualization may be a good choice for you. You'll likely have opportunities to help others by sharing important data in a format that’s visually appealing and easy to interpret. Learning data visualization can add to your skillset if you've previously studied or worked as a graphic designer or data analyst. You may choose to learn a programming language so you can develop your own data warehouse or another visualization tool to showcase the data you analyze, or you can decide to explore the variety of methods used to create visual displays of data.‎

    이 FAQ 콘텐츠는 정보 전달 목적만으로 사용할 수 있습니다. 학습자는 과정 및 기타 학점 정보가 개인적, 직업적 및 재정적 목표에 부합하는지 확인하기 위해 추가 조사를 수행하는 것이 좋습니다.
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